Since the publication of the first edition of this chapter in 1992 and the second in 2007, there has been a major shift in focus within the food industry, in response to both new consumer dynamics and technological advances in processing, along with demographic and economic societal changes. In recent years, there has been a continually incr easing consumer demand for not only high-quality foods with nutritional benefits, but also products that would substantiate “clean labels” (i.e., “chemical-, hormone-, GMO-free”, “organic”, “natural”, etc.) and products that would address changes in life-style logistics (e.g., fresh and refrigerated snacking occasions and complete meals, single portions, etc.) (Sloan, 2015, 2017). In addition, advances in more efficient and versatile methods of food processing and preservation have occurred exponentially over the past few decades, such that food scientists also need to adjust their focus on new and improved models to aid the development process for new product generation. With the advances in scientific findings concerning stability and bioavailability of vitamins and various pigments/nutrients, and updated analyses, these models may be impacted. These factors all play a part in new and sometimes complex challenges in predicting the best approaches to producing high quality food. However, there will still be constants; the quality of processed foods will still depend upon the integrity of the raw materials, changes occurring during processing and subsequent storage that may result in potential losses and decreased bioavailability, and above all, microbiological safety standards.
Since the publication of the first edition of this chapter in 1992 and the second in 2007, there has been a major shift in focus within the food industry, in response to both new consumer dynamics and technological advances in processing, along with demographic and economic societal changes. In recent years, there has been a continually incr easing consumer demand for not only high-quality foods with nutritional benefits, but also products that would substantiate “clean labels” (i.e., “chemical-, hormone-, GMO-free”, “organic”, “natural”, etc.) and products that would address changes in life-style logistics (e.g., fresh and refrigerated snacking occasions and complete meals, single portions, etc.) (Sloan, 2015, 2017). In addition, advances in more efficient and versatile methods of food processing and preservation have occurred exponentially over the past few decades, such that food scientists also need to adjust their focus on new and improved models to aid the development process for new product generation. With the advances in scientific findings concerning stability and bioavailability of vitamins and various pigments/nutrients, and updated analyses, these models may be impacted. These factors all play a part in new and sometimes complex challenges in predicting the best approaches to producing high quality food. However, there will still be constants; the quality of processed foods will still depend upon the integrity of the raw materials, changes occurring during processing and subsequent storage that may result in potential losses and decreased bioavailability, and above all, microbiological safety standards.
A particular emphasis on nutraceuticals and fortified “high-energy” foods has been observed (Sloan, 1999, 2005; Molyneau and Lee, 1998; Giese, 1995; Ohr, 2017). Trends also indicate that fortification of food products has increased tremendously in the past years in multiple categories, including beverages, meals, biscuits, etc. Not only nutritional quality is important to the food processor, but also the general appearance of the food, its flavor, color and texture, factors which are highly dependent upon the target consumer. It is, therefore, of critical importance to the food industry to minimize losses of quality in food products during processing and subsequent storage. It is through the development of mathematical models to predict behavior of food components and optimization of processes for maximum product quality that continued advancement can be achieved. To obtain these goals, extensive information is needed on the rates of destruction of quality parameters and their dependence on variables such as temperature, pH, light, oxygen, and moisture content. A food engineer can then develop new processing techniques to achieve optimum product quality based on an understanding of reaction rates and mechanisms of destruction of individual quality factors combined with heat and mass transfer information. The need for this type of information is becoming critically important to the food industry with increased required nutritional labeling practices for food products (IDFA, 2016).
Chemical kinetics encompasses the study of the rates at which chemical reactions proceed. The area of kinetics in food systems has received a great deal of attention in past years, primarily due to efforts to optimize or at least maximize the quality of food products during processing and storage. Moreover, a good understanding of reaction kinetics can provide a better idea of how to formulate or fortify food products in order to preserve the existing nutrients or components in a food system or, on the other hand, minimize the appearance of undesirable breakdown products. Unfortunately, limited kinetic information is available at present for food systems or ingredients that would facilitate the development of food products with improved stability or the optimization of processing conditions. A major consideration, however, is that indirectly some of the information available may be used to predict kinetic trends and thus establish major guidelines in formulation, storage, and process conditions. Thus, it is within the scope of this chapter to (a) present a general discussion on general kinetics, outlining some of the fundamental principles, (b) provide information on a variety of food systems, indicating their reactivity and reported kinetic behavior, and (c) provide an understanding of current changes resulting from external influences, including updated analytical methodologies and technological advances. It is considered that a better understanding of kinetics in food systems will facilitate the development of a more complete and sound database.
It should be emphasized that the level of accuracy of kinetic data is dependent upon its final application. For instance, if mathematical models are developed to optimize retention of a particular attribute in a given food system, it is evident that more sophisticated techniques are required than for those where the measurement is used for routine quality control. This is an area where careful judgement needs to be exerted. In fact, many of the major drawbacks existing in current kinetic data have originated in the analytical techniques selected to compile kinetic information. Not only sensitivity but also selectivity in the assay procedure needs to be taken into account when monitoring individual compounds in highly complex food systems.
There are three main areas of concern when dealing with reaction kinetics: (1) the stoichiometry, (2) the order and rate of reaction and (3) the mechanism. For simple reactions, the stoichiometry is probably the first consideration. Once this is clarified or elucidated, the mechanisms involved in the reaction are determined. It should be mentioned that based on kinetic data, our idea of the stoichiometry may change. In highly complex reactions, as in the case of many reactions occurring in food systems, a great deal of overlap exists among the three aforementioned areas. Thus, it is of critical importance to take a close and analytical look at the overall system to be able to better characterize reaction pathways.
The determination of the order of the reaction is of particular significance to the area of kinetics. Understanding of the mechanisms involved in the reaction is important to properly obtain and report meaningful kinetic information, select reaction conditions leading to a desired end product, and/or minimize the appearance of undesirable compounds. Unfortunately, very seldom has effort been dedicated to clearly understanding the mechanisms involved in the reaction in complex systems, as in the cases with food and biological materials. Most information available has been oversimplified. In fact, most investigators have often tried to adapt fairly simple zero- or first-order reaction kinetics to complex situations without trying to understand the actual pathways involved. Although, from a practical point of view it is clear that simplifications may be taken, applicability of the information may be restricted only to the conditions encompassed by the experimental design, and thus one may incorrectly predict trends by directly extrapolating reported information.
The reaction pathway, also called reaction mechanism, may be determined through proper experimentation. A chemical reaction may take place in a single step, as in the case of elementary reactions, or in a sequence of steps, as would be the case of most reactions occurring in food systems. Conditions such as temperature, oxygen availability, pressure, initial concentration, and the overall composition of the system may affect the mechanism of the reaction. For instance, the degradation of folic acid and ascorbic acid can be affected by the presence of oxygen, resulting in modifica tion of the reaction pathway and thus the type of breakdown products. Moreover, the rate at which these parent compounds disappear may be highly influenced by the presence and concentration of the breakdown products generated. It is true that the level of complexity involved in these reactions may be of such magnitude that a complete understanding of the mechanism of deterioration cannot always be easily determined or identified or, even more, may hinder the development of simple techniques to rapidly evaluate the stability of a given system. Nevertheless, it should be stressed that more reliable information is obtained when understanding of the reaction pathways is achieved.
A basic approach for the determination of the reaction order for a simple reaction, taking into consideration its initial rate is as follows:
which after taking the natural logarithm on both sides of the equation results in:
where C is the concentration; k is the reaction rate constant; n is the order of the reaction; and t is time.
According to this approach, a plot of the ln (−dC/dt) vs. ln C will give a straight line, whose slope corresponds to the reaction order (n), as shown in Figure 3.1. Although the intercept should correspond to the reaction rate constant (k), it is normally considered that, for the sake of accuracy, this would not be the preferred approach for its estimation. Rather, once the reaction order has been determined, the rate constant can be calculated by applying the corresponding equation for that reaction order.
Figure 3.1 Graphical representation for determining reaction order (n) of a reaction.
The method of least squares can also be used to determine the order of the reaction with respect to the reactants and products involved in the reaction. For instance, for a given reaction A + B → P, where A and B are the reactants and P is the product, the reaction rate (r) can be defined by an equation such that:
where [A] and [B] are the respective concentrations, and a and b are the respective reaction orders of the reactants A and B. By taking the natural log on each side, the equation becomes:
which is of the form:
where a 0, a and b are constants. Thus, by the least squares approach, the coefficients a and b, corresponding to the order of the reaction, can be determined.
For the particular case of complex reactions, such as in the case of lipid oxidation, many investigators have tried to apply simple reaction kinetics to describe their behavior. In this particular situation it is obvious that a clear understanding of the overall chain reaction including initiation, propagation, and termination stages may reach levels of complexity unwanted from a practical point of view and extremely difficult to express in simple mathematical terms. Complex reaction kinetics will be discussed in a subsequent section.
When dealing with food systems, a common approach to report reaction rates is as the change in concentration of a reactant as a function of time. The reaction rate thus provides a measurement of the reactivity and stability of a given system. A number of variables have been observed to influence the reaction rate. Major factors include: (a) concentration of reactants, products, and catalysts; (b) environmental factors such as temperature, pressure, and oxygen availability; (c) wavelength and intensity of light; and (d) physicochemical properties such as viscosity, ionic strength, and conductivity. Depending upon the type of reaction and the components, other factors will also be influential in controlling reaction kinetics.
Although traditionally one can apply reaction kinetics to monitor chemical changes occurring in a system, other physicochemical changes may also be described using a kinetic approach. For instance, textural and color changes occurring in food systems can be described using reaction rates. It is obvious that the numbers obtained represent the final effect ca used by other complex reaction mechanisms leading to an overall result. For instance, color changes in a product containing carotenoids may be an indication of the stability of the system, and in particular, stability of the carotenoids as related to environmental conditions. Another example is the textural changes in starch-based systems as a function of time, which may be the result of starch retrogradation mechanisms as well as lipid-amylose interactions as influenced by environmental conditions.
A key issue becomes how to properly measure the changes occurring in a system as influenced by different factors. Changes may be measured by monitoring, for instance, the disappearance of a compound, the appearance of a breakdown product, or changes in the physicochemical properties of the system such as in thermal conductivity. Colored species may be monitored through their appearance and disappearance by using spectrophotometric techniques. Depending very much on the final application of the kinetic data, one may need to actually monitor the reaction rate in such a way that the reaction does not proceed to any significant extent during the analytical test. Quenching of the reaction may be accomplished in many different ways, such as by lowering the temperature of the system or by addition of the reaction mixture to a system that provides stability. For most cases in food systems, the rates of chemical reactions that proceed slowly can be easily studied through convenient methods. Since nutrient retention is of primary concern in food systems subjected to deleterious conditions, a great deal of attention has been given to the study of vitamin degradation. A number of different techniques have been developed for their analyses, a brief summary of which is presented in Table 3.1. Although this table has been updated with the focus on more reliable instrumental techniques, many of these, however, still suffer from the lack of differentiation of intermediate compounds that may form, thus resulting in erroneous conclusions. For instance, the transformation of trans-carotenoids into their cis-form is difficult to detect unless a very specific technique is utilized. Since isomerization causes losses of the provitamin activity, it is critical to be able to identify the different isomers. Most techniques utilized thus far to monitor kinetics of carotenoid degradation have not taken this factor into account. Some of the research presented in this chapter has made great progress in this area, however. A great deal of effort has recently been directed towards more conclusive methods such as high-performance liquid chromatography (HPLC) and supercritical fluid chromatography, which afford separation of the individual compounds, thus enabling the collection of proper kinetic information to elucidate mechanisms of deterioration and characterize kinetic parameters. Other methods include the use of liquid chromatography in combination with mass spectrometry (LC-MS) for the quantitative determination of 5-methyltetrahydrofolic and folic acids (Thomas et al., 2003; Pawlosky and Flanagan, 2001) and capillary zone electrophoresis for the separation of L-ascorbic and D-isoascorbic acids (Liao et al., 2000). Eitenmiller et al. (2008) have reviewed in detail many of the instrumental techniques for vitamin analysis, including extraction procedures, instrumentation, and detector systems currently in use as applied to foods and pharmaceuticals.
Instrumental Analysis | |||||
---|---|---|---|---|---|
Vitamin |
Sample Preparation |
Separation |
Detection |
Microbiological Assay |
Other Methods |
Vitamin C |
Acid hydrolysis |
HPLC; IEC; MECC |
Fluorescence (Ex λ = 335–365/Em λ = 426–440); UV absorption (λ = 254–265 nm) |
Indophenol Method (using Tillman’s Reagent – titration or photometric); monitors color changes due to 2,6-dichloroindophenol reduction; 2,4-dinitrophenylhydrazine (DNPH), monitors total ascorbic acid (AA) based on oxidation of AA to dehydroascorbic acid (DHAA) followed by coupling with DNPH to form red-colored osazones; Microfluorometric (based on reaction of DHAA with o-phenylenediamine); Polarographic; Oxidation-Reduction Methods (with iodine, bromine, iron, copper, mercury, or selenious acid); Capillary Zone Electrophoresis (separation of L- and D-isoascorbic acids). |
|
Vitamin B1 (Thiamine) |
Acid hydrolysis; enzymatic hydrolysis |
IEC; GLC; HPLC |
Fluorescence (Ex λ = 360–378/Em λ = 425–435), UV absorption (UV/VIS λ = 254–280 nm), FID |
Lactobaccillus viridescens (12706): [intact thiamine-specific] |
Fluorometric Thiochrome (alkaline oxidation of thiamine to fluorescent thiochrome); Animal (rat, pigeon, chick). |
Vitamin B2 (Riboflavin) |
Acid hydrolysis |
HPLC, MECC |
Fluorescence (Ex λ = 370–378/Em λ = 425–565), UV absorption (UV/VIS λ = 254–280 nm) |
Lactobaccilus casei subsp. rhamnsus (7469); Enterococcus fecalis (10100); Tetrahymena pyriformis [B2-specific]; Lactobacillus casei [non-specific] |
Polarographic; Animal (rat, chick) |
Niacin |
Alkaline hydrolysis |
HPLC, IEC, GLC, MECC |
Fluorescence (Ex λ = 260–322/Em λ = 380–542); UV absorption (Ex λ = 260–322/Em λ = 380–542), FID |
Lactobaccillus plantarum (8014); Luconostoc mesenteroides (9135); Lactobacillus plantarum |
Radiometric Assay; Spectrophotometric: based on König reaction (niacin + cyanogen bromide pyridinium compound + aromatic amine glutaconic dialdehyde derivative [colored]); niacinimide in potassium dihydrogen phosphate + cyanogen bromide + barbituric acid purple color; |
Metabolite Measurement: N1-methyl nicotinamide (NMN) and 6-pyridone of N1-methyl nicotinamide; NMN + ketones in alkali solution green fluorescent compound; NMN + ketones in alkali solution green fluorescent compound; Animal (dog, chick, weanling rat). |
|||||
Vitamin B6 |
Acid hydrolysis |
HPLC, IEC, GLC, MECC |
Fluorescence (Ex λ = 290/Em λ = 395), UV absorption (UV/VIS λ = 254–280 nm), FID |
Saccharomyces carlbergensis (9080); Saccharomyces uvarum |
Animal (chick and rat growth). |
Pantothenic acid |
Alkaline hydrolysis; enzymatic hydrolysis |
GLC |
FID; UHPLC |
Lactobaccillus plantarum (8014); Saccharomyces carlsbergensis, S. cerivisiae |
Fluorometric: alkaline hydrolysis + o-phthalaldehyde + 2-mercaptoethanol in boric acid solution fluorogenic compound; Radioimmunoassay; Enzyme-linked immunosorbent assay (ELISA); Animal (chick). |
Folate |
Enzymatic hydrolysis |
IEC; HPLC |
UV/VIS detector (λ = 270–283/550 nm); post derivitization fluorescence (Ex λ = 360–378/Em λ = 425–435) |
Lactobaccilus casei subsp. Rhamnus (7469); Enteroccus hirae (8043); Pediococcus cerivisiae |
Radiometric Assay (competitive binding radioassay using liquid or dry skim milk as binder); Electrophoretic (polyglutamyl chain-length determination). |
Biotin |
Acid hydrolysis; enzymatic hydrolysis |
Fluorescence detector (Ex λ = 340–490/Em λ = 395–520) |
Lactobaccillus plantarum (8014) |
Animal (chick, rat); Radiometric (not for general use); Fluorometric (for non-biological materials). |
|
Vitamin B12 |
Direct solvent extraction |
MECC |
Fluorescence (Ex λ = 250–275/Em λ = 305–312); UV/VIS absorption (λ = 254/365/546 nm) |
Lactobacillus delbrueckii, subsp. lactis (4797); Lactobacillus leichmennii |
Radioassays (competitive inhibition assay based on isotope-dilution principle); Protozoan assays (Euglena gracilis, Ochromonas malhamensis); Stable isotope LC-MS method; Polarographic; Animal (chick and rat). |
Vitamin A |
Direct solvent extraction; alkaline hydrolysis (saponification), extraction into organic solvents |
UV/VIS |
UV/VIS: carotene: 445–455 retinol: 325–340 retinyl palmitate: 452 xanthophylls: 436 |
Supercritical Fluid Chromatography (direct measurement). |
|
Vitamin D |
Alkaline hydrolysis with extraction into organic solvents |
HPLC; GLC |
UV absorption (254–265 nm) |
Colorimetric (Vit. D + SbCl3 in ethylene dichloride pink complex); Saponification followed by EtOH extraction, purification, LC/MS; Animal (rat [“line test”]; chick [bone ash]). |
|
Vitamin E |
Alkaline hydrolysis with extraction into organic solvents |
HPLC |
Fluorescence (Ex λ = 290–296/Em λ = 320–330); UV absorption (290 nm) |
Colorimetric (based on Emmerie & Engel’s Reaction: tocopherols + bathophenanthroline + FeCl3 + orthophosphoric acid pink-colored complex); GLC (native or trimethylsilyl derivatives); Animal (rat, chick, duckling). |
|
Vitamin K |
Direct solvent extraction; supercritical fluid extraction; enzymatic hydrolysis |
HPLC; GLC |
UV absorption (247–256 nm); fluorescence (Ex λ = 243–325/Em λ = 418–430) |
Reduction-Oxidation Method; Animal (chick prothrombin time determinations); Ethylcyanoacetate Method; 2,4-Dinitrophenylhydrazine Method. |
FID: Flame ionization detector; Em λEmmission wavelength; Ex λExcitation wavelength; GLC: Gas–liquid chromatography; IEC: Ion exchange chromatography; HPLC: High pressure liquid chromatography; MECC: Micellar electrokinetic capillary electrophoresis; UHPLC: Ultra-high pressure liquid chromatography.
Since reactions in food systems are normally complex and a combination of several elementary steps, additional basic information may be necessary to postulate reaction rate expressions. Identification of intermediates and previous knowledge of rate equations to fit data for other systems may provide assistance in properly characterizing a given reaction. Additional factors that may affect reaction rates are the type of energy and/or conditions surrounding the process to which the food is subjected such as those associated with nontraditional techniques including high pressure, irradiation, and ohmic and pulsed electric field processing.
In the following paragraphs, a short summary of the mathematical description of concentration vs. time for single irreversible and complex reactions will be presented. The most commonly found reactions in food and biological systems are the zero-, first-, and second-order reactions.
In zero-order reactions, the rate is independent of the concentration. This may occur in two different situations: (a) when intrinsically the reaction rate is independent of the concentration of reactants and (b) when the concentration of the reacting compound is so large that the overall reaction rate appears to be independent of its concentration. Many catalyzed reactions fall in the category of zero-order reactions with respect to the reactants. On the other hand, the reaction rate may depend upon the catalyst concentration or other factors unrelated to the concentration of the compound under investigation.
Thus, for a zero-order reaction at constant density, the overall expression would be as follows:
where C is the concentration; t is time; k 0 is the zero-order reaction rate constant, which by integration would result in:
where C is the concentration at time (t) and C 0 is the initial concentration.
According to this mathematical expression, a distinguishing feature for this type of reaction is a linear decrease in concentration as a function of time as illustrated in Figure 3.2.
Figure 3.2 Graphical representation for the determination of a zero-order rate constant (k 0).
Typical reactions that have been represented by zero-order reactions include some of the autooxidation and non-enzymatic browning reactions. It is clear that zero-order reactions do not appear to occur as frequently in food systems as other reaction orders. In most cases, it is evident that the most common situation for this type of reaction is when the concentration of the reactants is so large that the system appears to be independent of concentration.
A large number of reactions occurring in food systems appear to follow a first-order reaction. A mathematical expression for this behavior would be as follows:
where k 1 is the first-order reaction rate constant. By integration, this equation becomes:
Thus, according to this mathematical expression ln C vs. time will be a linear function where the slope corresponds to –k 1 as shown in Figure 3.3. The half-life (t 1/2) is given by:
Figure 3.3 Graphical representation for the determination of a first-order rate constant (k 1).
The mathematical expressions above clearly indicate that the half-life and the reaction rate for a true first-order reaction are independent of the initial concentration. However, although in a number of systems this may be the case, formulated products will not necessarily follow true first-order reaction kinetics, but rather a pseudo-first-order reaction. In fact, in formulated systems the presence of breakdown products may strongly influence the order of the reaction; however, the reaction may follow apparent first-order kinetics for only a given value of initial concentration. To determine if a given reaction does indeed follow a pseudo-first-order kinetics, conditions for the kinetic study can be chosen to follow the technique of flooding. Through this approach, all but one of the concentrations are set sufficiently high that, compared to the one reagent present at lower concentration, the others are effectively constant during the time of the experiment. Since only one of the concentrations changes appreciably during the run, the effective kinetic order is reduced to the reaction order with respect to that one substance. If the order of the reaction is determined to be one, the reaction is said to follow a pseudo-first-order reaction. The degradation of ascorbic acid, for instance, has been primarily found to follow first-order kinetics in food systems. On the contrary, degradation of ascorbic acid in model systems has frequently been found to follow pseudo-first-order kinetics. It appears that the presence of breakdown products modifies the kinetics of deterioration of ascorbic acid and thus its initial concentration will influence its rate of degradation.
Two types of second-order reaction kinetics are of importance:
Type I: A + A → P
and Type II: A + B → P
where C A is the concentration of reactant species (A) at time (t), C B is the concentration of reactant species (B) at time (t), and k 2 is the second-order reaction rate constant. For Type I, the integrated kinetic expression yields:
which in terms of the half-life becomes:
For Type II, the integrated form yields:
where C A0 and C B0 are the respective initial concentrations and C A and C B are the respective concentrations at time (t). It should be stressed, however, that Type II reactions do not necessarily have to follow a second-order reaction. For instance, for the particular case where component A is present in large amounts as compared with component B, the reaction may follow first-order kinetics with respect to B. A typical plot of second order kinetics is presented in Figure 3.4.
Figure 3.4 Graphical representation for the determination of a second-order rate constant (k 2) for a type I reaction.
To characterize the kinetics of nonelementary reactions, one can assume a series of individual elementary reactions taking place. In these reactions, intermediates may not be observed or quantitated, either because they are present in very small amounts or because they are unstable. Such reactions would fall under three main categories: (1) consecutive or series reactions, (2) reversible or opposing reactions, which attain a finite equilibrium, and (3) parallel or competitive reactions. The types of intermediates postulated may fall in any one of the following categories, namely, (a) free radicals, (b) ions and polar substances, (c) molecules, and (d) transition complexes (chain reactions and non-chain reactions). The following are examples of the various mechanisms proposed.
Free atoms or fragments of stable molecules containing one or more unpaired electrons are called free radicals. For these compounds, a standard convention is to designate the unpaired electron by a dot (·). Some of these radicals are stable as in the case of ascorbic acid, where its hydroxyl on the C-3 readily ionizes (pK1 = 4.04 at 25°C) and may undergo degradation to dehydroascorbic acid in the presence of oxygen. Other free radicals are unstable as in the case of lipid oxidation. For instance, when a hydroperoxide decomposes to form RO• radicals, such compounds can participate in other reactions, thus being capable of continuing the chain propagation process and forming several products. Hydroxy acids, keto acids, and aldehydes have been isolated from oxidizing lipid systems. The formation of protein free radicals in systems undergoing lipid oxidation is another example of reactions involving unstable radicals. Free radicals may form on the α-carbons of the proteins, while cysteil radicals may form in proteins containing cysteine or cystine (Karel, 1973).
Electrically charged atoms, molecules, or fragments of molecules, such as Na+, , I− and , are called ions, which may serve as reactive intermediates in a variety of reactions.
In reactions such as: A → B → C, where compound B is highly reactive or its concentration in a given reaction mixture is very small, such compound B acts as an intermediate.
Chain-Reactions:
Catalyzed reactions may fall in the category of chain reactions. In these reactions an intermediate is formed in the initiation step. Such an intermediate then interacts with the reactant to obtain a product and more intermediate to participate in the reaction. A key consideration is that the intermediate may catalyze a series of reactions before being destroyed.
A classic example for the case of chain reactions is the degradation of β-carotene, an autooxidation reaction involving three main periods: (1) induction (formation of free radicals), (2) propagation (free radical-chain reactions), and (3) termination (formation of non-radical products). According to this pathway, the reaction may be expressed as follows:
Although different approaches have been taken to mathematically describe the kinetic behavior of β-carotene, a simplified free-radical recombination has been suggested by a number of authors (Alekseev et al., 1968; Gagarina et al.; 1970; Finkel’shtein et al., 1973, 1974).
According to this approach, the rate of consumption of a hydrocarbon, i.e. carotenes, in a chain process with a second-order chain termination can be described by:
By replacing the value corresponding to w i , the rate of formation of free radicals, the rate of consumption of the hydrocarbon can be expressed as being:
where C is the carotenoid concentration at time (t); C 0 is the initial carotenoid concentration; a is the constant derived from Equation 3.19; b is the initiation rate constant of the products; b 0 is the initiation rate constant of unoxidized carotenoids; and t is time.
The initiation rate is considered to be the sum of the initiation rates of radicals formed by the unreacted carotene and by the intermediate products. The value of the constant “a” can be represented by:
where k p , k t , and k are rate constants as previously shown; K s is the solubility coefficient of oxygen in carotenoids; and PO2 is the partial pressure of oxygen. Integrating Equation (3.19) using the dimensionless variables suggested by Gagarina et al. (1970) yields:
If all the constants on the right side of the previous equation are lumped together to denote the effective rate constant, namely (σ),
Equation (3.20) can be simplified to yield:
which corresponds to the equation for a straight line. It is evident that the slope of a graph of vs. t will give the value corresponding to the effective rate constant.
The aforementioned simplified models have been successfully used by various investigators to describe the reaction kinetics of carotenoids assuming a scheme of an unbranched chain as previously described. It is obvious that in systems where oxygen accessibility is limited due to the density of the material, higher rates of oxidation will take place close to the surface. Hence, different rates of degradation of the carotenoids will take place simultaneously, thus, highly complicating the analysis of the kinetics for the overall system.
Non-Chain Reactions:
Non-chain catalyzed reactions may involve the interaction of the substrate with the catalyst to form a complex, followed by its decomposition to form the product. Upon decomposition, the catalyst is then regenerated and is capable of taking part in the reaction once again. A typical example of this behavior is the acid-catalyzed hydrolysis of pyranosides according to the pathways presented in Figure 3.5. According to this diagram, the mechanism involves rapid reversible protonation of the glycosidic oxygen atom to produce a protonated oligosaccharide (2), which undergoes a slow unimolecular decomposition to a stable monosaccharide and an acyclic carbonium ion (3). It is considered that the carbonium ion is stabilized by resonance with the oxonium ion (4). Nucleophilic addition of water would yield a protonated reducing sugar (5), which through the loss of a proton would result in the hydrolytic products (6) and reappearance of the catalyst.
Figure 3.5 Illustration of a non-chain catalyzed reaction: the acid-catalyzed hydrolysis of pyranosides.
Enzyme Kinetics:
Another example of transition complex reactions is that of enzyme catalyzed reactions. It should be mentioned that most of the reactions occurring in biological systems are catalytic in nature. The basic principles for enzyme-catalyzed reactions have been presented by Michaelis-Menten, who proposed the theory of complex formation according to the following equation:
where E is the enzyme; S is the substrate; ES is the enzyme-substrate complex; and P is the product. Both reactions are considered to be reversible. In this equation, k 1, k –1, k 2, and k –2 are the specific constants for the designated reactions.
Although the general principle of chemical kinetics may apply to enzymatic reactions, the phenomenon of saturation with substrate is unique to enzymatic reactions. In fact, at low substrate concentrations the reaction velocity is proportional to the substrate concentration, and thus the reaction is first-order with respect to the substrate. As the substrate conc entration increases, the reaction progressively decreases, being no longer proportional to the concentration of the substrate and deviating from any first-order kinetics. The reaction follows zero-order reaction kinetics, due to saturation with the substrate (Figure 3.6).
Figure 3.6 Illustration of reaction rate dependence on substrate concentration for the initial phase of an enzyme-catalyzed reaction, indicating maximum velocity (V max ), ½V max and Michaelis constant (K m ).
For the particular case of enzyme kinetics, the cases of competitive and noncompetitive inhibition need to be considered. In the first case, the competitive inhibitor (I) is able to interact with the enzyme to generate a complex (EI), according to the reaction:
In this type of reaction, the complex EI does not break down to create products. However, the reaction can be reversed by increasing the substrate concentration.
On the other hand, in the case of noncompetitive inhibition, the inhibitor may bind to the enzyme on a locus different from the active site of the enzyme, and thus it may bind to the free enzyme or to the complex according to the equations presented below:
where the forms EI and ESI are inactive.
The most common type of competitive inhibition is that created by compounds that bind reversibly with the sulfhydryl groups of cysteine residues that are essential for the catalytic activity of some enzymes. Such groups may be located at or near the active site. In this second case, the catalytic activity may be related to stearic hindrance or the ability to maintain the three-dimensional conformation of the enzyme.
It is of critical importance to be able to identify competitive and irreversible inhibition. For the particular case of irreversible inhibition, the inhibitor binds to the enzyme irreversibly, and some may modify its molecular structure. It is obvious that for this particular case the use of the Michaelis-Menten equation is not possible since this approach assumes that the interaction between the enzyme and the inhibitor is reversible. A typical case of irreversible reactions would be the case of the trypsin inhibitors found in soybeans, namely, the Kunitz and the Bowman-Birk inhibitors. Chymotrypsin has been found to be strongly inhibited by the Bowman-Birk inhibitor, while only weakly inhibited by the Kunitz inhibitor. Both inhibitors have also been shown to be active against bovine trypsin. The activity of human trypsin has been observed to be inhibited to a significant extent by the Kunitz inhibitor.
Consecutive reactions form another category of reactions of importance in food products. Intermediates are formed in such reactions, which may decompose or react to create other compounds. In many cases, the intermediate may have a short life, and thus simplifications may be taken to describe their kinetics. Since decomposition of the intermediates may proceed under different reaction kinetics, complex situations may arise.
For the particular case of reactions in sequence, following first-order or pseudo-first-order kinetics:
and for the particular case where the aforementioned reactions are not reversible, the rate of disappearance of A can be expressed as follows:
which becomes:
The concentration of the intermediate can be determined by:
By substituting Equation 3.24 into Equation 3.25 and multiplying each term by exp (k 2 t), the following expression is derived:
Integration of this equation with [B] = 0 at t = 0 yields:
It can be easily illustrated that the final product (C) does not form immediately as A is decomposed due to the formation of B. This period is normally termed an induction period.
It is evident that the aforementioned case is a simple case for these particular types of reactions. More complicated situations correspond to the cases for consecutive reactions with a reversible step or when the individual steps do not follow the same order reaction kinetics. If the rate of disappearance of B is fairly rapid, it is evident that if one monitors the appearance of C only based on the concentration of A, inaccuracies may be introduced in the kinetic analysis.
For the most part, we have considered reactions whose rate constant consists of a single value with an integral reaction order. However, now we will consider the reaction:
in which the rate of disappearance of A is given by:
To solve this equation, two considerations are to be taken into account: (1) from the stoichiometry:
and (2) from the condition −d[A]/dt = 0 at equilibrium:
Through substitution and rearrangement:
Integration between the corresponding limits will give:
According to this equation, a plot of ln ([A]−[A∞]) vs. time will be a straight line, whose slope corresponds to −(k 1 + k −1). Figure 3.7 describes the concentration of reactant A as a function of time for two different situations. In the first case, the reaction will reach certain equilibrium with retention values leveling off. On the other hand, if a reactant is added to rapidly consume B, this will prevent its return to A. In this situation, only the forward reaction controls –d[A]/dt with a continuous depletion of reactant A. For both cases, the initial rate of the reaction is the same. Although this type of behavior may be possible in food systems, as in the interconversion of pyridoxamine and pyridoxal, where these compounds may undergo further degradation, most information reported in the literature will consider the rate for the overall reaction with no simultaneous information for the forward and the reverse reactions. Huang and von Elbe (1985), however, developed a kinetic reaction model accounting for the forward and reverse reactions for the degradation and regeneration of betanine in solution and its degradation products, betalamic acid, and cyclodopa-5-O-glycoside. This model could predict the amount of betanine remaining before and after regeneration of the pigment under different experimental conditions. Since in most practical situations dealing with food products the majority of investigators have not explored the mechanisms of degradation of the compound under question to minimize the amount of work involved, it becomes simple to visualize the limitations of available kinetic information if one tries to extrapolate to other systems.
Figure 3.7 Illustration of time dependence of a hypothetical reversible first-order reaction.
In reference to complex reactions, another case of significance corresponds to the degradation of a single compound to different products, following different pathways. The degradation of ascorbic acid is a typical example of a complex reaction where several pathways may operate simultaneously. Seldom have investigators taken the time to identify the contribution of each pathway to the degradation of this vitamin, but rather have reported an overall value. In the case of chlorophylls, Heaton et al. (1996a,b) developed a general mechanistic model for rates of chlorophyll degradation to pheophorbides via either pheophytins or chlorophyllides. Depending upon the contribution of each pathway when dealing with competitive reactions, variable levels of inaccuracy may result since each reaction will proceed at a different rate. Thus, if the reaction is expressed by the following mechanism:
where P1, P2,…, P n = products; and k 1, k 2,…k n = rate constants. The rate of disappearance of A is given by:
which by integration results in:
where
Since the products are generated with different yields, it is obvious that information on product formation is needed to evaluate the rates of the reaction. Moreover, it is evident that solely monitoring the rate of disappearance of A and assigning an overall reaction rate may be highly inaccurate, since each pathway may have a different reaction order and a different associated rate constant. This approach has been commonly taken by many investigators in determining reaction rates for the degradation of vitamins, pigments, etc. This discussion should emphasize the need for a better understanding of the reaction mechanisms to properly report kinetics. Since this is a more time-consuming approach, it is understandable why many investigators circumvented the complexity of the reaction kinetics.
When considering reaction rates, it is clear that these values may be influenced by a large number of parameters, including temperature and pressure. In fact, equilibrium yields, chemical reaction rates, and product distribution may be drastically influenced by temperature. Since chemical reactions are accompanied by heat effects, if these are large enough to cause a significant change in temperature of the reaction mixture, these effects also need to be taken into consideration. This would be particularly important in reactor design. The effect of temperature for an elementary process may follow, in most cases, the Arrhenius equation:
where k o is the frequency or collision factor; E a is the activation energy; R is the gas constant (1.987 cal/mol·°K); and T is the absolute temperature (°K). It is obvious that if the frequency factor and the activation energy could be evaluated from molecular properties of the reactants, it would be possible to estimate the values corresponding to the reaction rate. Unfortunately, our knowledge of kinetics is limited, particularly for complex systems, as would be the case of food systems or products.
It is, however, important to mention the collision theory as an approach to deal with kinetics. In Figure 3.8, the energy levels involved in a reaction are illustrated. According to the collision theory, upon the collision of reactive molecules, enough energy is generated to provide the necessary activation energy. Such a theory was used as the foundation for the determination of rate expressions based on the frequency of molecular collision required to generate a minimum energy.
Figure 3.8 Representation of potential energy levels during the process of a given endothermic reaction.
Another theory, the activated-complex or transition-state theory, has also been suggested. According to this approach, which still relies on reactions occurring due to collision between reactive molecules, an activated complex is formed from the reactants, which eventually decomposes to generate products. The activated complex is in thermodynamic equilibrium with the reactants. Complex decomposition is, then, the limiting step. Regardless of the theory considered, these approaches do not provide the means to rapidly and easily calculate activation energies from simple thermodynamic information. Thus, in practical terms, one has to obtain basic kinetic information to be able to determine the effect of temperature as affecting reaction kinetics. Based on the Arrhenius equation it is clear that if one plots the ln k vs. 1/T, the slope would correspond to the activation energy divided by the gas constant. Moreover, this value will not provide by itself any idea of the reactivity of a given system, only information on temperature dependence of the reaction.
Although the Arrhenius equation is commonly used to describe temperature dependence of the reaction rate in most food systems, deviations may occur as reported by several authors including Labuza and Riboh (1982) and Taoukis et al. (1997). In fact, a large number of factors may contribute to deviations. Changes in reaction mechanisms may occur for a large temperature range. For instance, it is highly possible that mechanisms of deterioration may change at conditions below the freezing point due to a concentration effect. On the other hand, at high temperatures, changes in the physical state of some compounds including fats and sugars may occur. Lipids may change from a solid to a liquid state, while sugars may change from an amorphous to a crystalline or to a liquid state. Because of the high complexity of food systems, it is also possible that when various mechanisms of deterioration operate simultaneously, the effect of temperature may alter the rates of one, thus causing inhibition or catalysis in the other mechanisms. Finally, irreversible changes such as starch hydrolysis or protein denaturation may occur due to temperature, thus modifying the reactivity of the system. In fact, although enzyme catalyzed reactions will have an increasing reaction rate upon an increase in temperature, a decrease will be observed beyond a certain temperature due to enzyme inactivation. Typical values for activation energies for a number of reactions are summarized in Table 3.2.
Activation Energy (Kcal/mole) |
|||||
---|---|---|---|---|---|
Reaction |
MIN |
MAX |
AVG |
MED |
CT |
Vitamins: a | |||||
Vitamin C |
3 |
46 |
16 |
16 |
66 |
Thiamine |
8 |
31 |
25 |
28 |
24 |
Riboflavin |
7 |
50 |
18 |
15 |
16 |
B6 |
14 |
30 |
22 |
24 |
6 |
Folates |
8 |
23 |
14 |
18 |
19 |
PA |
20 |
38 |
27 |
25 |
8 |
Carotene |
1 |
29 |
16 |
17 |
30 |
Vitamin E |
3 |
13 |
7 |
9 |
22 |
Tocopherols HighTemp |
3 |
14 |
8 |
8 |
12 |
Trienols |
0.5 |
27 |
13 |
12 |
10 |
Pigments:a | |||||
Total chlorophyll (as measured) |
5 |
62 |
15 |
11 |
6 |
Chlorophyll a |
5 |
27 |
17 |
17 |
15 |
Chlorophyll b |
7 |
35 |
17 |
16 |
14 |
Pheophytin a |
21 |
25 |
23 |
– |
– |
Pheophytin b |
16 |
17 |
16 |
– |
– |
Anthocyanins |
5 |
30 |
18 |
20 |
76 |
Carotenoids (pigments) |
1 |
23 |
10 |
10 |
15 |
Betanines |
5 |
29 |
15 |
15 |
53 |
Phycocyanins |
10 |
136 |
32 |
23 |
20 |
Browning |
7 |
58 |
23 |
13 |
93 |
Miscellaneous: | |||||
Enzyme reactionsb |
9 |
111 |
45 |
36 |
30 |
Hydrolysis of disaccharides |
10 |
15 |
12.5 |
– |
– |
Lipid oxidation |
10 |
25 |
17.5 |
– |
– |
Protein denaturationb |
6 |
135 |
40 |
26 |
40 |
Moisture diffusivityc (dehydration) |
3 |
26 |
10 |
8 |
30 |
Microbial inactivation: b |
6 |
198 |
76 |
75 |
240 |
Vegetative cell destructiond |
50 |
150 |
100 |
– |
– |
Spore destructiond |
60 |
80 |
70 |
– |
– |
Note: MIN = minimum; MAX = maximum; AVG = average; MED = median values; CT = count total calculated from the following sources: (a) current chapter tables; (b) Okos, M.R., 1986; (c) Heldman, D.R. and Lund, D.B., 1992; (d) Fennema, O.R., 1975.
Traditionally, processing of foods has involved thermal treatments with the specific goal of making the foods microbiologically safe. With greater concerns over the nutritional benefits of the foods as well as qualitative aspects such as texture and color, investigation into advancing food processing has resulted in the emergence of various new technologies within the food industry. One area of recent interest is the use of ultra-high pressure (UHP) processing of foods, also referred to as high hydrostatic pressure (HHP) and high pressure processing (HPP). According to the Le Chatelier principle, any reaction, conformational change, or phase change that is accompanied by a decrease in volume will be favored at high pressure, while reactions involving an increase in volume will be inhibited (Williams, 1994).
The kinetics of reactions as influenced by pressure may be best approached from the Eyring (activated complex or absolute theory) where reaction rates are based on the formation of an unstable intermediate complex, which is in quasi-equilibrium with the reactants. For instance, in a bimolecular reaction, reactants A and B form an intermediary complex (AB)*, with an equilibrium rate constant (k 1), which may further decompose at a rate constant (k 2) to form product(s).
The overall reaction rate is therefore controlled by the rate of formation of the activated complex which is a function of the change in “Gibbs free energy” (ΔG) going from the normal to the activated state, similar to the previous discussion (Section 2.3.4.1.). In the case with the effect of changing temperature, the relationship was given by the Arrhenius equation, assuming pressure was held constant. The influence of pressure on reaction rate, however, may be described by the basic thermodynamic relationship, as shown in Equation (3.36) as applied to the Eyring Equation (3.37):
where ΔG o is the standard free energy associated with the formation of one mole of substance at 25°C and 1 atmosphere (molal free energy); P is pressure; and ΔV o is the associated volume at constant temperature (T). The Eyring equation, where ΔG * = ΔH *– ΔS * T:
where ΔG * is the change in free energy; ΔS * is the entropy; ΔH * is the enthalpy; k B is the Boltzman constant; h is Plank’s constant; and R is the gas constant. Combining these equations results in the following expression at constant temperature:
By integration this gives the expression for the rate constant, k:
where k o is a constant dependent on the s ystem; ΔV * is the volume of activation; and T is temperature (°K). The activation volume relates the change in volume between that of the reactants and that of the activated complex. Basically, this expression indicates that the rate constant increases with increasing pressure if ΔV * is negative. In other words, the molar volume of the activated complex is smaller than that of the reactants together. From a practical point of view, the activation volume can be determined from the slope (−ΔV */RT) of the plot of ln k versus P at constant temperature. This is similar to the method of determination of the activation energy (E a ) from the slope (−E a /R) from a plot of ln k versus 1/T at constant pressure. It is also important for the rate constant (k) to be measured above the “critical” or “threshold” pressure in order for activation volume constants to be meaningful.
It should be pointed out that in the process of pressure treating foods, there is an increase in temperature due to the work of compression. It is therefore, critical to maintain a constant temperature during the pressure treatment in order to obtain meaningful kinetic data. Farkas and Hoover (2000) pointed out several critical process factors to take into account when conducting pressure related studies. These factors include maintaining constant composition, pH, water activity, come-up-times and pressure release times, change in temperature due to compression, and in the case of microorganism testing, the type, age, culturing, and growth conditions should all be kept the same for comparison.
Limited work on the effect of pressure on kinetics of vitamin and pigment degradation has been reported in the literature. Thus far, most of the emphasis has been placed on the microbiological aspects, as would be expected. A further discussion on effects of pressure will be addressed in a later section of this chapter.
In the following section, a brief discussion of the mechanisms of deterioration of food components including vitamins and pigments, and some of the most relevant kinetic information will be presented.
Over the past years, many reviews on the stability of various nutrients and pigments have been published (Harris and von Loesecke, 1960; Harris and Karmas, 1975; DeRitter, 1976; Archer and Tannenbaum, 1979; Thompson, 1982; Villota and Hawkes, 1986; Clydesdale et al., 1991; Delgado-Vargas et al., 2000; Dionísio et al, 2009; Rickman et al., 2007; Riaz et al., 2009; Nayak et al., 2015); they discuss the concerns over nutrient and general quality losses during different types of processing and storage conditions. With regard to mathematical modelling of quality changes in foods, additional reviews have been published (Van Boekel, 2008; Ling et al., 2015); they discuss the potential for new and improved mathematical models, facilitated through the advancements in computer technology, where more complex models may be required to more accurately identify and quantify factors to predict quality. However, despite the large numbers of kinetic studies on the stability of nutrients, pigments, textural properties, and potential new predictive modelling techniques, etc., it is still evident that systematic studies geared to elucidate mechanisms of reactions to provide information on developing comprehensive kinetic models remain scarce. In addition, a great deal of research over the past decade has resulted in many new findings for vitamins and their derivatives, as well as other nutraceuticals, elucidating their reaction mechanisms relevant to metabolic pathways, and thus reestablishing the importance of fortification in foods and further emphasizing the significance of understanding their stability during processing and storage. Moreover, it is also clear that although work carried out in model systems contribute to our understanding of reactions, the actual kinetic information obtained may not be readily applicable to highly complex systems such as foods. Thus, information compiled for this review, considers primarily the biochemistry and stability of bioactive ingredients in real food products, with limited emphasis given to model systems.
Vitamin C (ascorbic acid) is chemically known as L-3-keto-threo-hexuronic acid lactone, is naturally found as the L-isomer in various citrus fruits, hip berries, and fresh tea leaves. It also exists in a stereoisomeric form referred to as D-isoascorbic acid (also called D-araboascorbic or erythorbic acid) and has only a twentieth of the bioavailability of L-ascorbic acid. L-ascorbic acid can reversibly convert to dehydroascorbic acid in the presence of mild oxidants and may subsequently and irreversibly convert to 2,3-diketogulonic acid, which has no bioavailability. This makes it important for proper differentiation during its analysis for nutritional purposes. Originally discovered for its ability to cure scurvy, ascorbic acid is currently well known as a biological cofactor that plays an essential role in a broad array of physiological pathways, fundamental to cellular functions. Its biochemical actions as an antioxidant and universal reducing agent in vivo have been well documented and reviewed (Eitenmiller et al., 2008; Johnston et al., 2014). Considerable amounts of ascorbic acid may be lost during processing and storage of food products. In fact, ascorbic acid is readily destroyed by heating and oxidation, and its protection is particularly difficult to achieve. Other factors influencing the degradation of this vitamin include water activity or moisture content, pH, and metal traces, especially copper and iron. In general, it has been observed for a wide number of products containing ascorbic acid that the reaction appears to follow first-order kinetics. It should be mentioned, however, that different pathways exist for the degradation of ascorbic acid. Such pathways give origin to different breakdown products, and, therefore, affect the overall rates of vitamin degradation. In fact, the reaction may proceed under aerobic or anaerobic conditions, or through catalyzed or uncatalyzed aerobic pathways (Figure 3.9). Understanding of the mechanisms involved facilitates the handling of kinetic data. However, because of the fact that many parameters will influence the kinetics of ascorbic acid decomposition, it is difficult to establish a precursor–product relationship, except for the earlier part of the reactions. For instance, in stored canned products, the reaction may occur at the beginning through catalyzed or uncatalyzed aerobic mechanisms. Upon storage after the disappearance of the free oxygen, subsequent losses may be due to anaerobic decomposition of the compound. It is also possible that various mechanisms of deterioration can operate simultaneously, thus highly complicating the treatment of the kinetic data. For instance, in the presence of oxygen, it is possible that the anaerobic pathway will take place, although its contribution appears to be less significant than even the pathway for uncatalyzed degradation. Eison-Perchonok and Downes (1982) used second-order kinetics to describe the degradation of ascorbic acid under limiting oxygen concentrations. Finholt et al. (1963) indicated a maximum rate for anaerobic degradation of ascorbic acid at pH 4 and attributed this behavior to a 1:1 complex of ascorbic acid molecules and hydrogen ascorbate ions which would be present at the highest concentration at a pH near 4.0. Since at normal temperatures the anaerobic degradation proceeds at low rates, normally its contribution can be considered insignificant in the presence of excess oxygen.
Figure 3.9 Degradation pathways of ascorbic acid (adapted from Bauernfeind and Pinkert, 1970 and Tannenbaum et al., 1985).
It is a well-known fact that the autooxidation of ascorbic acid to dehydroascorbic acid is a reversible process, which takes place in two steps with the formation of a free radical as an intermediate. Early studies of ascorbic acid radicals, reported by Yamazaki et al. (1959 and 1960) and Yamazaki and Piette (1961), indicated its decay according to second-order reaction kinetics. Bielski et al. (1971) indicated that complex reactions occur for the decay of ascorbic acid radicals, despite the fact that the decay follows strictly second-order reaction kinetics. Huelin (1953) investigated the stability of ascorbic acid in a variety of food products. The author observed that decomposition of the compound proceeded faster in the pH range of 3–4. Under anaerobic conditions, it has been observed that a maximum degradation occurs at approximately pH 4, followed by a rate decrease upon a decrease in pH to 2.0 (Huelin et al., 1971). Van Bree et al. (2012) looked at the effect of oxygen headspace on oxidation rates of ascorbic acid in fruit juice model systems and the subsequent formation and breakdown of dehydroascorbic acid during storage at 22°C up to 60 days. The authors found ascorbic acid degradation to be successfully described by a first-order kinetic model across the entire oxygen range tested (0.03–20.9%), but only at low oxygen levels below 0.63% O2 when using a zero-order reaction; similar results were found for both fruit juice model systems and commercial orange juice. More recently, the affinity of ascorbic acid for free radicals was shown by Giroux et al. (2001) to improve the color stability of beef during storage, following gamma irradiation treatment. The vitamin C-scavenging of free radicals (such as •OH and •SH) showed a reduction of pigment oxidation in meats. Similarly, addition of ascorbic acid was found to improve stability of color of dry chili powder (carotenoids) during storage at different water activities (Bera et al., 2001).
With regard to metal-catalyzed reactions of ascorbic acid, it has been found that the reaction can be catalyzed by transition metals such as copper, iron, and vanadium, both free and bound in complex compounds (Khan and Martell, 1967a,b, 1968). The reaction may also be catalyzed by the copper containing metal enzyme, ascorbate oxidase. Two different mechanisms have been proposed for the non-enzyme catalyzed degradation of ascorbic acid by free and complex ions. Differences in their reaction order, rate limiting step, and products of oxygen reduction were observed. Schwertnerová et al. (1976) reported that the autooxidation of ascorbic acid, catalyzed by copper ions, followed the Michaelis-Menten law in the presence of an inhibitor. Pekkarinen (1974) observed that the autooxidation of ascorbic acid catalyzed by iron salts in citric acid solutions had a clear induction period, particularly at lower concentrations. Although the addition of copper salt decreased the induction period, it was also observed that the rate of the reaction slowed down at a later stage. It is possible, according to the author, that the copper salt may destroy radicals produced by the reaction catalyzed by the iron salts. Spanyár and Kevei (1963) had previously reported that copper was very destructive to ascorbic acid in air but had an insignificant effect in nitrogen. The authors also indicated that although iron had a prooxidant activity, iron and copper combined accelerated the degradation of ascorbic acid at a lower rate than either of the two acting alone.
In most situations it has been observed that an increase in temperature also increases the destruction rates of ascorbic acid. On the other hand, contradicting results have been suggested for conditions at sub-freezing temperatures. Grant and Alburn ( 1965a,b) studied the degradation of ascorbic acid in frozen and unfrozen solutions containing 10−4 M ascorbic acid in a 0.02 M acetate buffer at pH values of 5.0 and 5.5. At both pH values, the rates of ascorbic acid oxidation were observed to be significantly higher at −11°C as compared to the system at 1°C, and more pronounced for the system at pH 5.5. A number of factors have been suggested to be responsible for the observed trends. An increase in concentration of the reactants occurs upon freezing of the system (Pincock and Kiovsky, 1966). Other factors, such as a catalytic effect exerted by the ice crystals, favorable orientation of the reactants in the partially frozen system, and a decrease in dielectric constant or an increase in proton mobility, have also been given as possible reasons for the enhanced rates of ascorbic acid degradation at sub-freezing temperatures. It is also possible that oxygen availability is another factor to be taken into consideration. Results reported by Thompson and Fennema (1971) indicated that, in fact, an increase in reactant concentration, pH, and oxygen availability could explain higher rates of degradation or a smalle r than expected decrease in rate in partially frozen systems. Changes of pH as a result of freezing should also be taken into consideration. In fact, Van den Berg and Rose (1959) reported significant changes in pH during the freezing of well-buffered phosphate solutions upon freezing from 0 to −10°C.
In general, taking into consideration the possible reaction pathways, as summarized by Bauernfeind and Pinkert (1970), the specific kinetic parameters may be dependent on more factors than normally accounted for. In fact, it is a common assumption to measure the rate of degradation of ascorbic acid in food products, natural or formulated, for only a given initial concentration. Work done by various investigators, indicates that for the case of this particular vitamin the degradation may follow pseudo-first-order reaction kinetics. In fact, the presence of breakdown products will alter the kinetic rates and, possibly, the mechanisms of degradation (Villota, 1979). In fact, depending on the composition of the system and considering that some of the steps involved in the degradation of ascorbic acid are reversible, it is clear that although the reaction may still follow first-order reaction kinetics the rates of degradation will vary depending on the equilibrium created in the system and the levels of breakdown products. Lavelli and Giovanelli (2003) further exemplified the effect of initial concentration in tomato products. They found higher rates of degradation of ascorbic acid at lower initial concentration levels (Table 3.3).
Commodity |
Process/Conditions |
r2 |
kT value (min−1) |
Ea (kcal/mol) |
Reaction Order |
r2 |
Temp. Range (°C) |
t1/2 (min) |
References |
---|---|---|---|---|---|---|---|---|---|
Water Soluble Vitamins: |
|||||||||
Ascorbic acid (Vitamin C) |
|||||||||
Apricots |
Canned |
0.94 |
k26.7 = 53.236 × 10−8 |
1.30 × 106 |
Cameron et al. (1955) |
||||
0.82 |
k18.3 = 9.079 × 10−8 |
23.7 |
1 |
0.91 |
10–26.7 |
7.64 × 106 | |||
0.84 |
k10 = 5.043 × 10−8 |
13.75 × 106 | |||||||
Asparagus |
Canned |
0.75 |
k26.7 = 12.967 × 10−8 |
5.35 × 106 |
Cameron et al. (1955) |
||||
0.72 |
k18.3 = 7.769 × 10−8 |
8.1 |
1 |
0.97 |
10–26.7 |
8.92 × 106 | |||
0.85 |
k10 = 5.808 × 10−8 |
11.95 × 106 | |||||||
Raw, whole in crushed ice; room temperature |
0.91 |
k0 = 0.0001065 |
– |
1 |
– |
~0 |
6.51 × 103 | ||
0.92 |
k20 = 0.0002394 |
– |
1 |
– |
~20 |
2.90 × 103 | |||
Ascorbic acid |
|||||||||
Asparagus | |||||||||
Bud segment |
Blanching |
0.986 |
k100 = 30.4 × 10−2 |
2.28 |
Zheng et al. (2011) |
||||
Dimensions: |
0.986 |
k95 = 15.9 × 10−2 |
4.35 | ||||||
Base: 0.8–1.0 cm |
0.986 |
k90 = 7.34 × 10−2 |
9.44 | ||||||
Length: 20 cm |
0.986 |
k85 = 4.60 × 10−2 |
15.10 | ||||||
0.986 |
k80 = 2.67 × 10−2 |
24.24 |
1 |
0.965 |
60–100 |
25.96 | |||
0.986 |
k75 = 1.39 × 10−2 |
49.87 | |||||||
4 sampling time intervals, based on temp: |
0.986 |
k70 = 1.12 × 10−2 |
61.89 | ||||||
0.986 |
k65 = 0.86 × 10−2 |
80.60 | |||||||
0.986 |
k60 = 0.59 × 10−2 |
121.60 | |||||||
Upper segment |
100°C: 2–8 min |
0.986 |
k100 = 27.5 × 10−2 |
2.52 | |||||
95°C: 3–12 min |
0.986 |
k95 = 15.1 × 10−2 |
4.59 | ||||||
90°C: 5–20 min |
0.986 |
k90 = 7.63 × 10−2 |
9.08 | ||||||
85°C: 7–28 min |
0.986 |
k85 = 4.68 × 10−2 |
14.81 | ||||||
80°C: 10–40 min |
0.986 |
k80 = 2.81 × 10−2 |
24.68 |
1 |
0.986 |
60–100 |
24.67 | ||
75°C: 15–60 min |
0.986 |
k75 = 1.63 × 10−2 |
42.52 | ||||||
70°C: 20–80 min |
0.986 |
k70 = 1.09 × 10−2 |
63.59 | ||||||
65°C: 25–100 min |
0.986 |
k65 = 0.81 × 10−2 |
85.57 | ||||||
60°C: 30–120 min |
0.986 |
k60 = 0.46 × 10−2 |
150.68 | ||||||
Middle segment |
0.986 |
k100 = 25.8 × 10−2 |
2.69 |
Zheng et al. (2011) |
|||||
0.986 |
k95 = 15.0 × 10−2 |
4.63 | |||||||
Assay: |
0.986 |
k90 = 6.09 × 10−2 |
11.38 | ||||||
Indophenol method |
0.986 |
k85 = 3.62 × 10−2 |
19.15 | ||||||
0.986 |
k80 = 2.16 × 10−2 |
28.70 |
1 |
0.988 |
60–100 |
32.09 | |||
0.986 |
k75 = 1.02 × 10−2 |
67.96 | |||||||
0.986 |
k70 = 0.74 × 10−2 |
93.67 | |||||||
0.986 |
k65 = 0.39 × 10−2 |
177.73 | |||||||
0.986 |
k60 = 0.25 × 10−2 |
277.26 | |||||||
Middle segment |
0.986 |
k100 = 24.5 × 10−2 |
2.83 | ||||||
0.986 |
k95 = 13.0 × 10−2 |
5.34 | |||||||
0.986 |
k90 = 5.46 × 10−2 |
12.70 | |||||||
0.986 |
k85 = 3.45 × 10−2 |
20.09 | |||||||
0.986 |
k80 = 2.17 × 10−2 |
27.56 |
1 |
0.983 |
60–100 |
31.94 | |||
0.986 |
k75 = 1.06 × 10−2 |
65.39 | |||||||
0.986 |
k70 = 0.61 × 10−2 |
113.63 | |||||||
0.986 |
k65 = 0.42 × 10−2 |
165.04 | |||||||
0.986 |
k60 = 0.29 × 10−2 |
239.02 | |||||||
Ascorbic acid |
|||||||||
Beef |
Laing et al. (1978) |
||||||||
Model system (40% soy flour, 25% beef, 20% sucrose, 10% propylene glycol) |
aw = 0.69 |
– |
– |
3.3 |
0 |
– |
61–100 |
– | |
aw = 0.80 |
– |
– |
4.1 |
0 |
– |
61–100 |
– | ||
aw = 0.90 |
– |
– |
3.8 |
0 |
– |
61–100 |
– | ||
Ascorbic acid |
|||||||||
Breakfast cereal |
Packaging: |
Kirk et al. (1977) |
|||||||
Model system (soy protein/fat/carbohydrate/salt/sugar) |
208 × 006 | ||||||||
TDT cans | |||||||||
aw = 0.10 |
– |
k37 = 0.681 × 10−5 |
10.18 × 104 | ||||||
Total ascorbic acid |
– |
k30 = 0.632 × 10−5 |
8.1 |
1 |
0.956 |
10–37 |
10.97 × 104 | ||
– |
k20 = 0.313 × 10−5 |
22.15 × 104 | |||||||
– |
k10 = 0.215 × 10−5 |
32.24 × 104 | |||||||
aw = 0.24 |
– |
k37 =0.479 × 10−5 |
1.99 × 104 |
Kirk et al. (1977) |
|||||
– |
k30 = 1.236 × 10−5 |
15.9 |
1 |
0.971 |
10–37 |
5.61 × 104 | |||
– |
k20 = 0.660 × 10−5 |
10.50 × 104 | |||||||
– |
k10 =0.257 × 10−5 |
26.97 × 104 | |||||||
aw = 0.40 |
– |
k37 = 4.882 × 10−5 |
1.42 × 104 | ||||||
– |
k30 = 2.174 × 10−5 |
17.6 |
1 |
0.997 |
10–37 |
3.19 × 104 | |||
– |
k20 = 0.889 × 10−5 |
7.80 × 104 | |||||||
– |
k10 = 0.292 × 10−5 |
23.74 × 104 | |||||||
aw = 0.50 |
– |
k37 = 6.417 × 10−5 |
1.08 × 104 | ||||||
– |
k30 = 2.771 × 10−5 |
19.2 |
1 |
0.986 |
10–37 |
2.50 × 104 | |||
– |
k20 =0.778 × 10−5 |
8.91 × 104 | |||||||
– |
k10 = 0.340 × 10−5 |
20.39 × 104 | |||||||
aw = 0.65 |
– |
k37 = 10.931 × 10−5 |
0.634 × 104 | ||||||
– |
k30 = 3.313 × 10−5 |
19.2 |
1 |
0.984 |
10–37 |
2.09 × 104 | |||
– |
k20 = 1.000 × 10−5 |
6.93 × 104 | |||||||
– |
k10 = 0.347 × 10−5 |
19.98 × 104 | |||||||
Reduced ascorbic acid |
aw = 0.10 |
– |
k37 = 0.854 × 10−5 |
8.12 × 104 | |||||
– |
k30 = 0.771 × 10−5 |
7.1 |
1 |
0.979 |
10–37 |
8.99 × 104 | |||
– |
k20 = 0.451 × 10−5 |
15.37 × 104 | |||||||
– |
k10 = 0.299 × 10−5 |
23.18 × 104 | |||||||
aw = 0.24 |
– |
k37 = 3.083 × 10−5 |
2.25 × 104 | ||||||
– |
k30 = 1.597 × 10−5 |
14.2 |
1 |
0.985 |
10–37 |
4.34 × 104 | |||
– |
k20 = 0.931 × 10−5 |
7.45 × 104 | |||||||
– |
k10 = 0.312 × 10−5 |
22.22 × 104 | |||||||
aw = 0.40 |
– |
k37 = 5.465 × 10−5 |
1.27 × 104 | ||||||
– |
k30 = 2.667 × 10−5 |
17.8 |
1 |
0.994 |
10–37 |
2.60 × 104 | |||
– |
k20 = 1.174 × 10−5 |
5.90 × 104 | |||||||
– |
k10 = 0.326 × 10−5 |
21.26 × 104 | |||||||
Reduced ascorbic acid |
aw = 0.50 |
– |
k37 = 6.181 × 10−5 |
1.12 × 104 |
Kirk et al. (1977) |
||||
– |
k30 = 3.251 × 10−5 |
18.1 |
1 |
0.989 |
10–37 |
2.16 × 104 | |||
– |
k20 = 0.903 × 10−5 |
7.68 × 104 | |||||||
– |
k10 = 0.403 × 10−5 |
17.20 × 104 | |||||||
aw = 0.65 |
– |
k37 = 11.701 × 10−5 |
0.592 × 104 | ||||||
– |
k30 = 3.674 × 10−5 |
21.1 |
1 |
0.989 |
10–37 |
1.89 × 104 | |||
– |
k20 = 1.340 × 10−5 |
5.17 × 104 | |||||||
– |
k10 = 0.382 × 10−5 |
18.154 × 104 | |||||||
Packaging: cardboard boxes/w/wax paper liners | |||||||||
Total ascorbic acid |
aw = 0.10 |
– |
k30 = 1.701 × 10−5 |
– |
1 |
– |
30 |
4.07 × 104 | |
aw = 0.40 |
– |
k30 = 2.521 × 10−5 |
– |
1 |
– |
30 |
2.75 × 104 | ||
aw = 0.85 |
– |
k30 = 4.868 × 10−5 |
– |
1 |
– |
30 |
1.45 × 104 | ||
Reduced ascorbic acid |
aw = 0.10 |
– |
k30 = 1.847 × 10−5 |
– |
1 |
– |
30 |
3.75 × 104 | |
aw = 0.40 |
– |
k30 = 2.618 × 10−5 |
– |
1 |
– |
30 |
2.65 × 104 | ||
aw = 0.85 |
– |
k30 = 4.903 × 10−5 |
– |
1 |
– |
30 |
1.41 × 104 | ||
Packaging: 303 cans/w/XS headspace | |||||||||
Total ascorbic acid |
aw = 0.24 |
– |
k30 = 2.507 × 10−5 |
– |
1 |
– |
30 |
2.76 × 104 | |
aw = 0.40 |
– |
k30 = 5.944 × 10−5 |
– |
1 |
– |
30 |
1.17 × 104 | ||
Reduced ascorbic acid |
aw = 0.24 |
– |
k30 = 2.625 × 10−5 |
– |
1 |
– |
30 |
2.64 × 104 | |
aw = 0.40 |
– |
k30 = 5.313 × 10−5 |
– |
1 |
– |
30 |
1.30 × 104 | ||
Breakfast cereal model system [similar to Kirk et al. (1977)] |
Dennison and Kirk (1978) |
||||||||
Packaging: 303 cans | |||||||||
Total ascorbic acid |
aw = 0.10 |
– |
k37 = 1.229 × 10−5 |
5.64 × 104 | |||||
– |
k30 = 0.944 × 10−5 |
10.7 |
1 |
0.963 |
10–37 |
7.34 × 104 | |||
– |
k20 = 0.597 × 10−5 |
11.61 × 104 | |||||||
– |
k10 = 0.229 × 10−5 |
30.27 × 104 | |||||||
aw = 0.24 |
– |
k20 = 0.764 × 10−5 |
– |
1 |
– |
20 |
9 .07 × 104 | ||
aw = 0.40 |
– |
k37 = 5.035 × 10−5 |
1.38 × 104 |
Dennison and Kirk (1978) |
|||||
– |
k30 = 2.542 × 10−5 |
16.0 |
1 |
0.998 |
10–37 |
2.73 × 104 | |||
– |
k20 = 1.014 × 10−5 |
6.84 × 104 | |||||||
– |
k10 = 0.417 × 10−5 |
16.62 × 104 | |||||||
aw = 0.65 |
– |
k37 = 8.382 × 10−5 |
0.827 × 104 | ||||||
– |
k30 = 3.854 × 10−5 |
18.3 |
1 |
0.999 |
10–37 |
1.80 × 104 | |||
– |
k20 = 1.410 × 10−5 |
4.92 × 104 | |||||||
– |
k10 = 0.479 × 10−5 |
14.47 × 104 | |||||||
Packaging: 303 cans/w/XS headspace | |||||||||
Reduced ascorbic acid |
aw = 0.10 |
– |
k37 = 1.129 × 10−5 |
5.36 × 104 | |||||
– |
k30 = 0.896 × 10−5 |
10.7 |
1 |
0.977 |
10–37 |
7.74 × 104 | |||
– |
k20 = 0.583 × 10−5 |
11.89 × 104 | |||||||
– |
k10 = 0.236 × 10−5 |
29.377 × 104 | |||||||
aw = 0.24 |
– |
k20 = 0.715 × 10−5 |
– |
1 |
– |
20 |
9.69 × 104 | ||
aw = 0.40 |
– |
k37 = 5.271 × 10−5 |
1.32 × 104 | ||||||
– |
k30 = 2.167 × 10−5 |
15.5 |
1 |
0.984 |
10–37 |
3.20 × 104 | |||
– |
k20 = 1.021 × 10−5 |
6.79 × 104 | |||||||
– |
k10 = 0.438 × 10−5 |
15.83 × 104 | |||||||
aw = 0.65 |
– |
k37 = 8.104 × 10−5 |
0.885 × 104 | ||||||
– |
k30 = 3.549 × 10−5 |
16.9 |
1 |
0.994 |
10–37 |
1.95 × 104 | |||
– |
k20 = 1.417 × 10−5 |
4.89 × 104 | |||||||
– |
k10 = 0.563 × 10−5 |
12.31 × 104 | |||||||
Corn (yellow) |
Canned |
0.92 |
k26.7 = 18.768 × 10−8 |
3.693 × 106 |
Cameron et al. (1955) |
||||
0.74 |
k18.3 = 10.867 × 10−8 |
9.7 |
1 |
0.99 |
10–26.7 |
6.378 × 106 | |||
0.76 |
k10 = 7.183 × 10−8 |
9.650 × 106 | |||||||
Ascorbic acid |
|||||||||
Fruit juice |
% O2 Concentration: |
k1 |
Van Bree et al. (2012) |
||||||
Juice Model |
0.03 |
0.94 |
k22 = 1.22 × 10−5 |
5.70 × 104 | |||||
(25 g glucose, 25 g fructose, 40 g sucrose, 9.2 g citric acid, 0.45 g ascorbic acid, 1.27 g L-asparagine, 0.7 g L-arginine/liter) |
0.63 |
0.94 |
k22 = 2.08 × 10−5 |
3.34 × 104 | |||||
1.17 |
0.96 |
k22 = 3.04 × 10−5 |
2.28 × 104 | ||||||
2.78 |
0.99 |
k22 = 5.36 × 10−5 |
– |
1 |
– |
22 |
1.29 × 104 | ||
4.84 |
0.98 |
k22 = 8.19 × 10−5 |
0.846 × 104 | ||||||
10.02 |
0.90 |
k22 = 18.1 × 10−5 |
0.382 × 104 | ||||||
20.90 |
0.99 |
k22 = 27.1 × 10−5 |
0.256 × 104 | ||||||
k1 | |||||||||
Commercial orange |
0.03 |
0.79 |
k22 = 0.701 × 10−5 |
9.88 × 104 | |||||
0.98 |
0.91 |
k22 = 1.37 × 10−5 |
– |
1 |
– |
22 |
5.07 × 104 | ||
2.91 |
0.99 |
k22 = 2.15 × 10−5 |
3.23 × 104 | ||||||
10.8 |
0.96 |
k22 = 7.01 × 10−5 |
0.988 × 104 | ||||||
k1 | |||||||||
Juice model |
0.03 |
0.98 |
k22 = 1.21 × 10−5 |
k1 |
5.74 × 104 |
Van Bree et al. (2012) |
|||
0.63 |
0.97 |
k22 = 2.06 × 10−5 |
consecutive irreversible |
3.37 × 104 | |||||
1.17 |
0.99 |
k22 = 2.83 × 10−5 |
2.45 × 104 | ||||||
2.78 |
0.99 |
k22 = 5.03 × 10−5 |
– |
1 |
– |
22 |
1.38 × 104 | ||
4.84 |
0.98 |
k22 = 7.78 × 10−5 |
0.891 × 104 | ||||||
10.02 |
0.92 |
k22 = 18.2 × 10−5 |
0.380 × 104 | ||||||
20.90 |
0.98 |
k22 = 21.7 × 10−5 |
0.319 × 104 | ||||||
k1 | |||||||||
Commercial orange |
0.03 |
0.99 |
k22 = 0.694 × 10−5 |
k1 |
9.98 × 104 | ||||
0.98 |
0.99 |
k22 = 1.35 × 10−5 |
consecutive irreversible |
5.15 × 104 | |||||
2.91 |
0.99 |
k22 = 2.07 × 10−5 |
– |
1 |
– |
22 |
3.35 × 104 | ||
10.8 |
0.96 |
k22 = 6. 83 × 10−5 |
1.01 × 104 | ||||||
k3 | |||||||||
Juice model |
0.03 |
0.98 |
k22 = 15.3 × 10−5 |
k3 |
0.452 × 104 | ||||
0.63 |
0.97 |
k22 = 19.1 × 10−5 |
consecutive irreversible |
0.363 × 104 | |||||
1.17 |
0.99 |
k22 = 20.6 × 10−5 |
0.337 × 104 | ||||||
2.78 |
0.99 |
k22 = 21.7 × 10−5 |
– |
1 |
– |
22 |
0.320 × 104 | ||
4.84 |
0.98 |
k22 = 23.3 × 10−5 |
0.298 × 104 | ||||||
10.02 |
0.92 |
k22 = 24.8 × 10−5 |
0.280 × 104 | ||||||
20.90 |
0.98 |
k22 = 29.3 × 10−5 |
0.237 × 104 | ||||||
k3 |
Van Bree et al. (2012) |
||||||||
Commercial orange |
0.03 |
0.99 |
k22 = 1.03 × 10−5 |
k3 |
0.700 × 104 | ||||
0.98 |
0.99 |
k22 = 1.45 × 10−5 |
consecutive irreversible |
0.478 × 104 | |||||
2.91 |
0.99 |
k22 = 1.76 × 10−5 |
– |
1 |
– |
22 |
0.393 × 104 | ||
10.8 |
0.96 |
k22 = 2.56 × 10−5 |
0.271 × 104 | ||||||
k1 | |||||||||
Juice model |
0.03 |
0.98 |
k22 = 1.31 × 10−5 |
k1 |
5.28 × 104 | ||||
0.63 |
0.97 |
k22 = 2.06 × 10−5 |
consecutive reversible |
3.37 × 104 | |||||
1.17 |
0.99 |
k22 = 3.06 × 10−5 |
2.26 × 104 | ||||||
2.78 |
0.99 |
k22 = 5.03 × 10−5 |
– |
1 |
– |
22 |
1.38 × 104 | ||
4.84 |
0.98 |
k22 = 7.78 × 10−5 |
0.891 × 104 | ||||||
10.02 |
0.92 |
k22 = 18.3 × 10−5 |
0.380 × 104 | ||||||
20.90 |
0.98 |
k22 = 21.7 × 10−5 |
0.319 × 104 | ||||||
k1 | |||||||||
Commercial orange |
0.03 |
0.99 |
k22 = 0.757 × 10−5 |
k1 |
9.16 × 104 | ||||
0.98 |
0.99 |
k22 = 1.50 × 10−5 |
consecutive irreversible |
4.62 × 104 | |||||
2.91 |
0.99 |
k22 = 2.07 × 10−5 |
– |
1 |
– |
22 |
3.35 × 104 | ||
10.8 |
0.96 |
k22 = 6.83 × 10−5 |
1.01 × 104 | ||||||
k2 | |||||||||
Juice model |
0.03 |
0.98 |
k22 = 1.31 × 10−5 |
k2 |
5.28 × 104 | ||||
0.63 |
0.97 |
k22 = 0 |
– | ||||||
1.17 |
0.99 |
k22 = 2.03 × 10−5 |
consecutive reversible |
3.42 × 104 | |||||
2.78 |
0.99 |
k22 = 0 |
– |
1 |
– |
22 |
– | ||
4.84 |
0.98 |
k22 = 0 |
– | ||||||
10.02 |
0.92 |
k22 = 0 |
– | ||||||
20.90 |
0.98 |
k22 = 0 |
– | ||||||
k2 | |||||||||
Commercial orange |
0.03 |
0.99 |
k22 = 0.757 × 10−5 |
k2 |
9.16 × 104 | ||||
0.98 |
0.99 |
k22 = 1.50 × 10−5 |
consecutive irreversible |
4.62 × 104 | |||||
2.91 |
0.99 |
k22 = 0 |
– |
1 |
– |
22 |
– | ||
10.8 |
0.96 |
k22 = 0 |
– | ||||||
Juice model |
0.03 |
0.98 |
k22 = 15.1 × 10−5 |
k3 |
0.460 × 104 |
Van Bree et al. (2012) |
|||
0.63 |
0.97 |
k22 = 19.1 × 10−5 |
consecutive reversible |
0.363 × 104 | |||||
1.17 |
0.99 |
k22 = 20.6 × 10−5 |
0.336 × 104 | ||||||
2.78 |
0.99 |
k22 = 21.7 × 10−5 |
– |
1 |
– |
22 |
0.320 × 104 | ||
4.84 |
0.98 |
k22 = 23.3 × 10−5 |
0.298 × 104 | ||||||
10.02 |
0.92 |
k22 = 24.8 × 10−5 |
0.280 × 104 | ||||||
20.90 |
0.98 |
k22 = 29.3 × 10−5 |
0.237 × 104 | ||||||
k3 | |||||||||
Commercial orange |
0.03 |
0.99 |
k22 = 10.3 × 10−5 |
k3 |
0.670 × 104 | ||||
0.98 |
0.99 |
k22 = 14.5 × 10−5 |
consecutive irreversible |
0.478 × 104 | |||||
2.91 |
0.99 |
k22 = 17.6 × 10−5 |
– |
1 |
– |
22 |
0.393 × 104 | ||
10.8 |
0.96 |
k22 = 25.6 × 10−5 |
0.271 × 104 | ||||||
Grapefruit segments |
Canned |
0.99 |
k26.7 = 76.141 × 10−8 |
0.910 × 106 |
Cameron et al. (1955) |
||||
0.90 |
k18.3 = 22.558 × 10−8 |
20.7 |
1 |
0.99 |
10–26.7 |
3.073 × 106 | |||
0.73 |
k10 = 9.810 × 10−8 |
7.066 × 106 | |||||||
Grapefruit juice |
Thermal concentration | ||||||||
Solids |
11.2 oBx |
0.937 |
k96 = 0.002642 |
262 |
Saguy et al. (1978b) |
||||
0.996 |
k95 = 0.002503 |
4.98 |
1 |
0.998 |
61–96 |
277 | |||
0.966 |
k80 = 0.001899 |
(apparent) |
365 | ||||||
0.937 |
k61 = 0.001276 |
543 | |||||||
31.2 oBx |
0.978 |
k91 = 0.002701 |
257 | ||||||
0.956 |
k82 = 0.002165 |
5.33 |
1 |
0.997 |
60–91 |
320 | |||
0.974 |
k75 = 0.001874 |
370 | |||||||
0.925 |
k60 = 0.001349 |
514 | |||||||
47.1 oBx |
0.935 |
k96 = 0.003777 |
184 | ||||||
0.964 |
k90 = 0.003121 |
6.69 |
1 |
0.998 |
61–96 |
222 | |||
0.976 |
k80 = 0.00246 |
282 | |||||||
0.962 |
k61 = 0.00143 |
485 | |||||||
55.0 oBx |
0.988 |
k91 = 0.004712 |
147 |
Saguy et al. (1978b) |
|||||
0.972 |
k81 = 0.003348 |
8.60 |
1 |
0.999 |
61–91 |
207 | |||
0.970 |
k75 = 0.002715 |
255 | |||||||
0.951 |
k61 = 0.001618 |
428 | |||||||
62.5 oBx |
0.924 |
k96 = 0.01068 |
69 | ||||||
0.945 |
k81 = 0.005365 |
11.30 |
1 |
0.998 |
68–96 |
129 | |||
0.929 |
k76 = 0.004561 |
163 | |||||||
0.947 |
k68 = 0.003022 |
229 | |||||||
Green beans |
Canned |
0.89 |
k26.7 = 25.832 × 10−8 |
2.683 × 106 |
Cameron et al. (1955) |
||||
0.86 |
k18.3 = 17.819 × 10−8 |
7.5 |
1 |
0.99 |
10–26.7 |
3.890 × 106 | |||
0.81 |
k10 = 12.317 × 10−8 |
5.628 × 106 | |||||||
Raw, whole, sieved by mesh size | |||||||||
No. 5 |
0.96 |
k20 = 0.0002454 |
– |
1 |
– |
20 |
2,825 | ||
No. 4 |
0.95 |
k20 = 0.0002337 |
– |
1 |
– |
20 |
2,966 | ||
Nos. 2 and 3 |
0.85 |
k20 = 0.0003789 |
– |
1 |
– |
20 |
1,829 | ||
Stored at room temp. | |||||||||
(18.9–21.1°C) | |||||||||
Green beans |
Frozen |
– |
k−5 = 22.920 × 10−6 |
3.024 × 104 |
Giannakourou et al. (2003) |
||||
Blanch: 90°C/2 min |
– |
k−10 = 9.627 × 10−6 |
24.3 |
1 |
0.967 |
−5 to −20 |
7.200 × 104 |
||
IQF: −22°C/2 min |
– |
k−15 = 3.946 × 10−6 |
17.568 × 104 | ||||||
k−20 = 1.548 × 10−6 |
44.784 × 104 | ||||||||
Ascorbic acid |
|||||||||
Green Bell Peppers |
Rahman et al. (2015) |
||||||||
Fresh Capsicum |
7–10 time intervals per temp. |
0.73 |
k20 = 6.88 × 10−5 |
1.01 × 104 | |||||
(MC = 94 g/100 g) |
0.92 |
k5 = 4.93 × 10−5 |
1.37 |
1 |
0.819 |
−40–20 |
1.41 × 104 | ||
0.84 |
k−20 = 5.14 × 10−5 |
1.35 × 104 | |||||||
0.89 |
k−40 = 3.33 × 10−5 |
2.08 × 104 | |||||||
Freeze dried capsicum |
(freeze-dried and powdered) |
0.93 |
k60 = 10.3 × 10−5 |
0.674 × 104 | |||||
(MC = 15 g/100 g) |
0.99 |
k45 = 5.35 × 10−5 |
4.91 |
1 |
0.925 |
5–60 |
1.30 × 104 | ||
0.98 |
k20 = 2.64 × 10−5 |
2.63 × 104 | |||||||
Assay: |
0.90 |
k5 = 2.36 × 10−5 |
2.94 × 104 | ||||||
Freeze dried capsicum |
Indophenol |
0.96 |
k5 = 0.319 × 10−5 |
21.7 × 104 | |||||
(MC = 5 g/100 g) |
0.96 |
k−20 = 0.299 × 10−5 |
0.47 |
1 |
0.986 |
−40–5 |
23.2 × 104 | ||
0.93 |
k−40 = 0.271 × 10−5 |
25.6 × 104 | |||||||
Vitamin C | |||||||||
Infant food (fruit-based) |
Bosch et al. (2013) |
||||||||
22% pear puree |
Process: | ||||||||
22% tangerine juice |
Hot fill > 85°C |
0.973 |
k50 = 18.52 × 10−6 |
3.742 × 104 | |||||
16.5% banana puree |
130 g pkg. (PP/EVOH) |
0.883 |
k37 = 5.459 × 10−6 |
20.1 |
1 |
0.998 |
25–50 |
12.70 × 104 | |
10% carrot puree |
Pasteurized |
0.960 |
k25 = 1.345 × 10−6 |
51.53 × 104 | |||||
grape juice conc. |
Stored up to 32 wks |
– |
k4 no loss |
– |
– |
– |
4 |
– | |
starch, vitamin C |
Assay: Indophenol | ||||||||
Infant formula | |||||||||
[15% protein (milk-based); 24% lipids; 57% carbohydrates; 4% vitamins, minerals, water] |
With ferrous sulfate |
0.920 |
k45 = 4.24 × 10−6 |
1.63 × 105 |
Galdi et al. (1989) |
||||
0.916 |
k37 = 2.80 × 10−6 |
9.0 |
1 |
0.998 |
20–45 |
2.48 × 105 | |||
0.954 |
k20 = 1.25 × 10−6 |
5.55 × 105 | |||||||
With ferric glycinate |
0.959 |
k45 = 3.24 × 10−6 |
2.14 × 105 | ||||||
0.932 |
k37 = 2.04 × 10−6 |
8.7 |
1 |
0.992 |
20–45 |
3.40 × 105 | |||
0.926 |
k20 = 0.972 × 10−6 |
7.13 × 105 | |||||||
Ascorbic acid |
|||||||||
Mandarin slices |
Deff (m2/s)* |
Akdaş and Başlar (2014) |
|||||||
Ascorbic acid |
1.37 × 10−7 |
0.932 |
k75 = 12.2 × 10−4 |
569.6 |
|||||
Oven drying |
0.758 × 10−7 |
0.932 |
k65 = 6.61 × 10−4 |
10.12 |
1 |
0.951 |
55–75 |
1048.6 | |
0.353 × 10−7 |
0.948 |
k55 = 4.97 × 10−4 |
1394.7 | ||||||
Ascorbic acid |
2.76 × 10−7 |
0.888 |
k75 = 8.69 × 10−4 |
797.6 | |||||
Vacuum drying |
1.61 × 10−7 |
0.925 |
k65 = 4.44 × 10−4 |
12.34 |
1 |
0.978 |
55–75 |
1561.1 | |
0.952 × 10−7 |
0.971 |
k55 = 2.92 × 10−4 |
2373.8 | ||||||
DPPH** |
Assay: Indophenol |
0.940 |
k75 = 5.06 × 10−4 |
1369.9 | |||||
(antioxidant capacity) |
0.966 |
k65 = 2.91 × 10−4 |
8.42 |
1 |
0.919 |
55–75 |
2381.9 | ||
Oven drying |
0.957 |
k55 = 2.40 × 10−4 |
2888.1 | ||||||
DPPH** |
0.907 |
k75 = 7.37 × 10−4 |
940.5 |
Akdaş and Başlar (2014) |
|||||
(antioxidant capacity) |
0.912 |
k65 = 6.21 × 10−4 |
13.15 |
1 |
0.870 |
55–75 |
1116.2 |
||
Vacuum drying |
0.911 |
k55 = 2.33 × 10−4 |
2974.9 | ||||||
*effective moisture diffusivity |
|||||||||
**di(phenyl)-(2,4,6-trinitrophenyl) iminoazanium |
|||||||||
L-Ascorbic acid | |||||||||
Model system – pH 4.5 |
0.50 mmol/10 ml buffer |
0.951 |
k150 = 37.9 × 10−3 |
18.3 |
Li et al., (2016) |
||||
0.992 |
k140 = 21.4 × 10−3 |
32.4 | |||||||
0.999 |
k130 = 11.0 × 10−3 |
18.59 |
1 |
0.99 0 |
110–150 |
63.0 | |||
15 ml sealed vials |
0.999 |
k120 = 7.80 × 10−3 |
88.9 | ||||||
Heat: |
0.999 |
k110 = 3.50 × 10−3 |
198.0 | ||||||
Model system – pH 5.8 |
Oil bath (110–150°C) |
0.999 |
k150 = 30.7 × 10−3 |
22.6 | |||||
10–150 min |
0.996 |
k140 = 16.0 × 10−3 |
43.3 | ||||||
0.998 |
k130 = 9.20 × 10−3 |
18.01 |
1 |
0.995 |
110–150 |
75.3 | |||
0.991 |
k120 = 5.80 × 10−3 |
119.5 | |||||||
0.997 |
k110 = 3.10 × 10−3 |
223.6 | |||||||
Model system – pH 5.8 |
Buffers: |
0.998 |
k150 = 12.8 × 10−3 |
54.2 | |||||
0.020 M Na2HPO4 |
0.998 |
k140 = 9.70 × 10−3 |
71.5 | ||||||
0.020 M Na2H2PO4 |
0.995 |
k130 = 6.70 × 10−3 |
11.20 |
1 |
0.999 |
110–150 |
103.5 | ||
0.020 M Na2HPO4-Na2H2PO4 |
0.991 |
k120 = 4.80 × 10−3 |
144.4 | ||||||
0.998 |
k110 = 3.20 × 10−3 |
216.6 | |||||||
Model system – pH 8.0 |
0.997 |
k150 = 22.0 × 10−3 |
31.5 | ||||||
0.969 |
k140 = 10.5 × 10−3 |
66.0 | |||||||
Assay: |
0.995 |
k130 = 6.70 × 10−3 |
20.31 |
1 |
0.995419113 |
110–150 |
103.5 | ||
HPLC – A243 |
0.981 |
k120 = 3.20 × 10−3 |
216.6 | ||||||
0.992 |
k110 = 1.70 × 10−3 |
407.7 | |||||||
Model system – pH 9.5 |
0.999 |
k150 = 20.3 × 10−3 |
34.1 |
Li et al., (2016) |
|||||
0.996 |
k140 = 12.9 × 10−3 |
53.7 | |||||||
0.997 |
k130 = 5.50 × 10−3 |
22.31 |
1 |
0.984128498 |
110–150 |
126.0 | |||
1st-order best fit of 0, 1, 2-order calc. |
0.997 |
k120 = 2.30 × 10−3 |
301.4 | ||||||
0.992 |
k110 = 1.50 × 10−3 |
462.1 | |||||||
Okra |
Frozen |
– |
k−5 = 12.034 × 10−6 |
5.760 × 104 |
Giannakourou et al., (2003) |
||||
Blanch: 90°C/2 m |
– |
k−10 = 4.912 × 10−6 |
25.2 |
1 |
0.868 |
−5 to −20 |
14.112 × 104 |
||
IQF: −22°C/2 m |
– |
k−15 = 1.933 × 10−6 |
35.856 × 104 | ||||||
k−20 = 0.729 × 10−6 |
95.040 × 104 | ||||||||
Oranges (fresh squeezed/filtered) |
Van den Broeck, et al. (1998) |
||||||||
Thermal treatment: |
pH 3.5 |
0.99 |
k150 = 0.0967 |
7.2 |
|||||
In capillary tubes (1.15 × 150 mm) – vac – 0–150 min |
0.98 |
k140 = 0.048 |
28.1 |
1 |
0.998 |
120–150 |
14.4 | ||
0.98 |
k130 = 0.0205 |
33.8 | |||||||
0.99 |
k120 = 0.0076 |
91.2 | |||||||
Thermal/pressure treatment: |
0.98 |
k80 = 0.010289 |
67.4 | ||||||
8500 bar |
0.98 |
k70 = 0.004338 |
20.1 |
1 |
0.999 |
65–80 |
159.8 | ||
0.3 ml/N2 flush |
0.99 |
k65 = 0.0028967 |
239.3 | ||||||
Orange juice |
Canned |
0.98 |
k26.7 = 68.467 × 10−8 |
1.012 × 106 |
Cameron et al. (1955) |
||||
0.98 |
k18.3 = 22.738 × 10−8 |
24.3 |
1 |
0.99 |
10–26.7 |
3.048 × 106 | |||
0.81 |
k10 = 6.171 × 10−8 |
11.232 × 106 | |||||||
Ascorbic acid | |||||||||
Orange juice |
Micro Wet Milled |
0.97 |
k37 = 1.18 × 10−5 |
1.18 × 104 |
Islam et al. 2017 |
||||
OJ:MD 30:70 |
(with pulp) |
0.98 |
k30 = 0.903 × 10−5 |
4.2 |
1 |
0.996 |
4–37 |
7.68 × 104 | |
0.99 |
k4 = 0.639 × 10−5 |
10.8 × 104 | |||||||
Orange juice |
Blended/w/different maltodextrin (MD) ratios |
0.98 |
k37 = 1.60 × 10−5 |
4.34 × 104 | |||||
OJ:MD 40:60 |
0.98 |
k30 = 1.04 × 10−5 |
4.3 |
1 |
0.903 |
4–37 |
6.65 × 104 | ||
0.99 |
k4 = 0.833 × 10−5 |
8.32 × 104 | |||||||
Orange juice |
Vacuum spray-dried |
0.98 |
k37 = 2.01 × 10−5 |
3.44 × 104 | |||||
OJ:MD 50:50 |
0.98 |
k30 = 1.04 × 10−5 |
5.8 |
1 |
0.837 |
4–37 |
6.65 × 104 | ||
Analysis: HPLC |
0.99 |
k4 = 0.833 × 10−5 |
8.32 × 104 | ||||||
Orange juice |
UV (A254) |
0.95 |
k37 = 2.29 × 10−5 |
3.02 × 104 | |||||
OJ:MD 60:40 |
0.97 |
k30 = 1.11 × 10−5 |
6.6 |
1 |
0.861 |
4–37 |
6.24 × 104 | ||
0.98 |
k4 = 0.833 × 10−5 |
8.32 × 104 | |||||||
Ascorbic acid* |
|||||||||
Blood orange juice |
Pasteurize: |
0.982 |
k37 = 40.8 × 10−5 |
1.70 × 103 |
Remini et al. 2015 |
||||
(Not fortified control) |
Oil bath (80°C/2 min) |
0.974 |
k30 = 17.3 × 10−5 |
12.2 |
1 |
0.959 |
4–37 |
4.01 × 103 | |
30 ml glass bottles |
0.943 |
k20 = 8.47 × 10−5 |
8.18 × 103 | ||||||
15 ml headspace |
0.737 |
k4 = 3.47 × 10−5 |
20.0 × 103 | ||||||
AA-fortified juice |
rapid cool |
0.982 |
k37 = 32.2 × 10−5 |
2.15 × 103 | |||||
(100 mg AA/L) |
0.960 |
k30 = 14.3 × 10−5 |
14.7 |
1 |
0.993 |
4–37 |
4.84 × 103 | ||
Stored dark up to 25 days |
0.945 |
k20 = 7.38 × 10−5 |
9.39 × 103 | ||||||
0.815 |
k4 = 1.70 × 10−5 |
40.7 × 103 | |||||||
AA-fortified juice |
Assay: HPLC |
0.998 |
k37 = 30.6 × 10−5 |
2.27 × 103 | |||||
(200 mg AA/L) |
UV (A254) |
0.988 |
k30 = 14.7 × 10−5 |
13.3 |
1 |
0.986 |
4–37 |
4.72 × 103 | |
0.894 |
k20 = 6.60 × 10−5 |
10.5 × 103 | |||||||
0.917 |
k4 = 2.18 × 10−5 |
31.8 × 103 | |||||||
(Not fortified deaerated) |
0.842 |
k30 = 7.94 × 10−5 |
- |
1 |
– |
20–30 |
8.72 × 103 | ||
0.777 |
k20 = 1.27 × 10−5 |
54.5 × 103 | |||||||
*Similar trends found for color intensity measured at 515 nm |
|||||||||
Ascorbic acid |
|||||||||
Peaches |
Canned |
0.97 |
k26.7 = 56.939 × 10−8 |
– |
1 |
– |
26.7 |
1.217 × 106 |
Cameron et al. 1955 |
Peas (sweet) |
Canned |
0.92 |
k26.7 = 17.954 × 10−8 |
3.860 × 106 |
Cameron et al. 1955 |
||||
0.98 |
k18.3 = 10.794 × 10−8 |
9.0 |
1 |
0.99 |
10–26.7 |
6.422 × 106 | |||
0.82 |
k10 = 7.386 × 10−8 |
9.385 × 106 | |||||||
Peas (green) |
Frozen |
– |
k−5 = 20.060 × 10−6 |
3.456 × 104 |
Giannakourou et al. 2003 |
||||
Blanch: 90°C/2 m |
– |
k−10 = 8.596 × 10−6 |
23.4 |
1 |
0.958 |
−5 to −20 |
8.064 × 104 | ||
IQF: −22°C/2 m |
– |
k−15 = 3.647 × 10−6 |
19.008 × 104 | ||||||
k−20 = 1.481 × 10−6 |
46.800 × 104 | ||||||||
Predicted |
Teff = -3.8°C |
– |
keff = 24.24 × 10−6 |
– |
1 |
– |
−5 to −20 |
2.86 × 104 | |
Temp. Cycle: | |||||||||
−3°C/72 h | |||||||||
−5°C/24 h |
– |
kexp = 21.88 × 10−6 |
– |
1 |
0.981 |
−3 to −8°C |
3.17 × 104 | ||
−8°C/12 h | |||||||||
Ascorbic acid | |||||||||
Peas (sweet) |
Dehydro-frozen (50% H2O) |
Neumann et al. 1965 (from Labuza 1972) |
|||||||
Storage losses (in air) | |||||||||
aw = 0.90 |
– |
k−7 = 3.19 × 10−5 |
2.17 × 104 | ||||||
aw = 0.90 |
– |
k−15 = 0.214 × 10−5 |
46.0 |
1 |
– |
−15 to −7 |
32.39 × 104 | ||
Peas (sweet) |
Canned |
– |
k132.2 = 0.009 |
77 |
Lathrop and Leung 1980 |
||||
– |
k126.7 = 0.0043 |
161 | |||||||
– |
k121.1 = 0.0025 |
39.3 |
1 |
0.984 |
110–132 |
277 | |||
– |
k115.6 = 0.0014 |
495 | |||||||
– |
k110.0 = 0.00046 |
1,507 | |||||||
Pineapple slices |
Canned |
0.98 |
k26.7 = 67.577 × 10−8 |
1.026 × 106 |
Cameron et al. 1955 |
||||
0.87 |
k18.3 = 26.975 × 10−8 |
11.5 |
1 |
0.88 |
10–26.7 |
2.570 × 106 | |||
0.70 |
k10 = 21.456 × 10−8 |
3.231 × 106 | |||||||
Spinach |
Canned |
0.81 |
k26.7 = 17.475 × 10−8 |
3.967 × 106 |
Cameron et al. 1955 |
||||
0.80 |
k18.3 = 11.574 × 10−8 |
6.3 |
1 |
0.96 |
10–26.7 |
5.989 × 106 | |||
0.95 |
k10 = 9.347 × 10−8 |
7.4165 × 106 | |||||||
Spinach |
Frozen |
– |
k−5 = 60.169 × 10−6 |
1.152 × 104 |
Giannakourou et al. 2003 |
||||
Blanch: 90°C/2 m |
– |
k−10 = 24.068 × 10−6 |
26.8 |
1 |
0.992 |
−5 to −20 |
2.880 × 104 |
||
IQF: −22°C/2 m |
– |
k−15 = 8.752 × 10−6 |
7.920 × 104 | ||||||
k−20 = 3.146 × 10−6 |
22.032 × 104 | ||||||||
Predicted |
Teff = –1.7°C |
– |
keff = 119.9 × 10−6 |
– |
1 |
– |
−5 to −20 |
0.578 × 104 | |
Temp. Cycle: | |||||||||
−1°C/72 h | |||||||||
−4°C/24 h |
– |
kexp = 113.9 × 1 0−6 |
– |
1 |
0.917 |
−1 to −7°C |
0.609 × 104 | ||
−7°C/12 h | |||||||||
Sweet potato (flour) |
Freeze-dried/ground/rehumidified |
Haralampu and Karel 1983 |
|||||||
aw = 0.020 |
0.629 |
k40 = 1.58 × 10−5 |
– |
1 |
– |
40 |
43.87 × 103 |
||
aw = 0.058 |
0.843 |
k40 = 2.53 × 10−5 |
– |
1 |
– |
40 |
27.40 × 103 | ||
aw = 0.112 |
0.973 |
k40 = 2.67 × 10−5 |
– |
1 |
– |
40 |
25.96 × 103 | ||
aw = 0.316 |
0.999 |
k40 = 6.57 × 10−5 |
– |
1 |
– |
40 |
10.55 × 103 | ||
aw = 0.484 |
0.986 |
k40 = 10.77 × 10−5 |
– |
1 |
– |
40 |
6.44 × 103 | ||
aw = 0.555 |
0.960 |
k40 = 16.48 × 10−5 |
– |
1 |
– |
40 |
4.21 × 103 | ||
aw = 0.661 |
0.985 |
k40 = 27.67 × 10−5 |
– |
1 |
– |
40 |
2.51 × 103 | ||
aw = 0.747 |
1.000 |
k40 = 31.83 × 10−5 |
– |
1 |
– |
40 |
2.18 × 103 | ||
Tomatoes |
Canned |
0.94 |
k26.7 = 32.380 × 10−8 |
2.141 × 106 |
Cameron et al. 1955 |
||||
0.70 |
k18.3 = 9.865 × 10−8 |
13.3 |
1 |
0.82 |
10–26.7 |
7.026 × 106 | |||
0.70 |
k10 = 8.578 × 10−8 |
8.081 × 106 | |||||||
Tomatoes (fresh squeezed/filtered) |
Van den Broeck, et al. 1998 |
||||||||
Thermal treatment: |
pH 4.5 |
0.99 |
k150 = 0.0487 |
14.2 |
|||||
Variety A |
In capillary tubes (1.15 × 150 mm) – vac – 0–150 min |
0.98 |
k140 = 0.0245 |
25.2 |
1 |
0.999 |
120–150 |
60.3 | |
0.98 |
k130 = 0.0115 |
28.3 | |||||||
0.99 |
k120 = 0.0049 |
141.5 | |||||||
Thermal/pressure treatment: |
0.99 |
k80 = 0.005744 |
120.7 | ||||||
8500 bar |
0.98 |
k70 = 0.0032353 |
17.8 |
1 |
0.965 |
65–80 |
214.3 | ||
0.3 ml/N2 flush |
0.98 |
k65 = 0.001789 |
387.4 | ||||||
Thermal treatment: | |||||||||
Variety B |
0.99 |
k150 = 0.0864 |
8 | ||||||
0.99 |
k140 = 0.0411 |
27.5 |
1 |
0.998 |
120–150 |
16.9 | |||
0.99 |
k130 = 0.0183 |
37.9 | |||||||
0.98 |
k120 = 0.0071 |
97.6 | |||||||
Thermal treatment: |
Van den Broeck, et al. 1998 |
||||||||
Phosphate buffer |
pH 4.0 |
– |
k140 = 0.01302 |
– |
1 |
– |
140 |
53.2 |
|
pH 7.0 |
– |
k140 = 0.0060626 |
– |
1 |
– |
140 |
114.4 | ||
pH 8.0 |
– |
k140 = 0.0022658 |
– |
1 |
– |
140 |
305.4 | ||
(0–360 min) | |||||||||
Ascorbic acid | |||||||||
Tomato juice |
Heat processed, stored in 8 oz cans + citrate buffer |
Lee et al. 1977 |
|||||||
pH 3.53 |
– |
k37.8 = 0.128 × 10−5 |
4.5 |
1 |
– |
10–37.8 |
54.15 × 104 | ||
pH 3.78 |
– |
k37.8 = 0.158 × 10−5 |
4.0 |
1 |
– |
10–37.8 |
43.87 × 104 | ||
pH 4.06 |
– |
k37.8 = 0.172 × 10−5 |
40.30 × 104 | ||||||
– |
k29.4 = 0.147 × 10−5 |
3.3 |
1 |
0.999 |
10–37.8 |
47.15 × 104 | |||
– |
k18.3 = 0.121 × 10−5 |
57.28 × 104 | |||||||
– |
k10 = 0.101 × 10−5 |
68.63 × 104 | |||||||
pH 4.36 |
– |
k37.8 = 0.158 × 10−5 |
3.8 |
1 |
– |
37.8 |
43.87 × 104 | ||
Tomato juice |
Freeze-dried/rehydrated |
Riemer and Karel 1977 |
|||||||
aw = 0 |
0.99 |
k51 = 2.083 × 10−5 |
18.8 |
3.32 × 104 |
|||||
0.99 |
k37 = 0.340 × 10−5 |
(24.6)a |
1 |
0.971 |
20–51 |
20.37 × 104 | |||
0.74 |
k20 = 0.090 × 10−5 |
77.02 × 104 | |||||||
aw = 0.11 |
0.99 |
k51 = 6.944 × 10−5 |
17.0 |
0.981 × 104 | |||||
0.98 |
k37 = 1.389 × 10−5 |
(22.3)a |
1 |
0.974 |
20–51 |
4.99 × 104 | |||
0.95 |
k20 = 0.410 × 10−5 |
16.91 × 104 | |||||||
aw = 0.32 |
0.99 |
k51 = 19.444 × 10−5 |
20.3 |
0.357 × 104 | |||||
0.99 |
k37 = 4.861 × 10−5 |
(20.2)a |
1 |
0.999 |
20–51 |
1.43 × 104 | |||
0.99 |
k20 = 0.694 × 10−5 |
9.99 × 104 | |||||||
aw = 0.57 |
0.99 |
k51 = 48.611 × 10−5 |
16.0 |
0.143 × 104 | |||||
0.99 |
k37 = 13.889 × 10−5 |
(18.1)a |
1 |
0.997 |
20–51 |
0.499 × 104 | |||
0.99 |
k20 = 3.472 × 10−5 |
2.00 × 104 | |||||||
aw = 0.75 |
0.98 |
k51 = 81.944 × 10−5 |
14.6 |
0.0846 × 104 | |||||
0.98 |
k37 = 38.194 × 10−5 |
(16.2)a |
1 |
0.986 |
20–51 |
0.181 × 104 | |||
0.99 |
k20 = 7.639 × 10−5 |
0.907 × 104 | |||||||
Tomato paste |
Lavelli and Giovanelli 2003 |
||||||||
Total ascorbic acid |
Storage: 90 d |
0.94 |
k50 = 9.51 × 10−6 |
7.29 × 104 |
|||||
130 g Al-tubes |
0.94 |
k40 = 6.67 × 10−6 |
5.84 |
1 |
0.985 |
30–50 |
10.40 × 104 | ||
0.69 |
k30 = 5.21 × 10−6 |
(5.64)a |
13.31 × 104 | ||||||
Tomato pulp |
Storage: 90 d |
0.92 |
k50 = 14.93 × 10−6 |
4.64 × 104 | |||||
450 g cans |
0.84 |
k40 = 3.47 × 10−6 |
25.90 |
1 |
0.995 |
30–50 |
19.96 × 104 | ||
0.77 |
k30 = 1.04 × 10−6 |
(25.1)a |
66.54 × 104 | ||||||
Tomato pulp/w/XS heat |
0.94 |
k40 = 11.11 × 10−6 |
– |
1 |
– |
40 |
6.24 × 104 | ||
Tomato puree |
0.94 |
k40 = 7.43 × 10−6 |
– |
1 |
– |
40 |
9.33 × 104 | ||
B-Vitamins | |||||||||
Vitamin B1 (thiamine) | |||||||||
Breakfast cereal model system (Vit. B1) |
Packaged in: | ||||||||
TDT cans | |||||||||
aw = 0.10 |
– |
k45 = 0.00066 |
– |
1 |
– |
45 |
1,050 |
Dennison, et al. 1977 |
|
aw = 0.25 |
– |
k45 = 0.00091 |
– |
1 |
– |
45 |
762 | ||
aw = 0.40 |
– |
k45 = 0.000675 |
– |
1 |
– |
45 |
103 | ||
aw = 0.50 |
– |
k45 = 0.01101 |
– |
1 |
– |
45 |
63 | ||
aw = 0.65 |
– |
k45 = 0.00867 |
– |
1 |
– |
45 |
80 | ||
Breakfast cereal model system |
Dennison, et al. 1977 |
||||||||
(Vit. B1 + Vit. C + Vit. A) |
aw = 0.10 |
– |
k45 = 0.00014 |
– |
1 |
– |
45 |
4951 | |
aw = 0.25 |
– |
k45 = 0.00065 |
– |
1 |
– |
45 |
1066 | ||
aw = 0.40 |
– |
k45 = 0.00648 |
– |
1 |
– |
45 |
107 | ||
aw = 0.50 |
– |
k45 = 0.00927 |
– |
1 |
– |
45 |
75 | ||
aw = 0.65 |
– |
k45 = 0.00948 |
– |
1 |
– |
45 |
73 | ||
Carrots (puree) |
– |
ak149 = 0.1669 |
4.2 |
Feliciotti and Esselen, 1957 |
|||||
– |
k139 = 0.0711 |
9.7 |
|||||||
– |
k129 = 0.0285 |
28.3 |
1 |
0.999 |
109–149 |
24 | |||
– |
k119 = 0.012 |
58 | |||||||
– |
k109 = 0.0049 |
141 | |||||||
Vitamin B1 | |||||||||
Green beans (puree) |
– |
k149 = 0.1744 |
4.0 |
Feliciotti and Esselen, 1957 |
|||||
– |
k139 = 0.0717 |
9.7 |
|||||||
– |
k129 = 0.0311 |
28.6 |
1 |
0.999 |
109–149 |
22 | |||
– |
k119 = 0.0122 |
57 | |||||||
– |
k109 = 0.0049 |
141 | |||||||
Meats |
Feliciotti and Esselen, 1957 |
||||||||
Beef heart (puree) |
– |
k149 = 0.2171 |
3.2 |
||||||
– |
k139 = 0.0161 |
22.1 |
1 |
0.687 |
109–149 |
43 | |||
– |
k129 = 0.0392 |
27.9 |
1 |
0.999 |
109–149 |
18 | |||
– |
k119 = 0.0157 |
(−k139) |
44 | ||||||
– |
k109 = 0.0068 |
102 | |||||||
Beef liver (puree) |
– |
k149 = 0.2326 |
3.0 |
Feliciotti and Esselen, 1957 |
|||||
– |
k139 = 0.0892 |
7.8 |
|||||||
– |
k129 = 0.0364 |
28.5 |
1 |
0.996 |
109–149 |
19 | |||
– |
k119 = 0.0147 |
47 | |||||||
– |
k109 = 0.0067 |
103 | |||||||
Beef (puree) |
– |
k137.8 = 0.03673 |
19 |
Mulley, et al. 1975a |
|||||
– |
k132.2 = 0.02509 |
28 | |||||||
– |
k126.7 = 0.01436 |
27.5 |
1 |
0.996 |
121–138 |
48 | |||
– |
k121.1 = 0.00906 |
77 | |||||||
Lamb (puree) |
– |
k149 = 0.1935 |
3.6 |
Feliciotti and Esselen, 1957 |
|||||
– |
k139 = 0.0814 |
8.5 |
|||||||
– |
k129 = 0.0377 |
27.7 |
1 |
0.998 |
109–149 |
18 | |||
– |
k119 = 0.0138 |
50 | |||||||
– |
k109 = 0.0062 |
112 | |||||||
Vitamin B1 | |||||||||
Pork (puree) |
– |
k149 = 0.1693 |
4.1 |
Feliciotti and Esselen, 1957 |
|||||
– |
k139 = 0.0717 |
9.7 |
|||||||
– |
k129 = 0.0288 |
27.4 |
1 |
0.998 |
109–149 |
24 | |||
– |
k119 = 0.0129 |
54 | |||||||
– |
k109 = 0.0055 |
126 | |||||||
Vitamin B1 | |||||||||
Pork (puree) |
– |
ak137.8 = 0.084 |
8.3 |
Lenz and Lund, 1977b |
|||||
– |
k126.7 = 0.0385 |
25.6 |
1 |
0.997 |
115–138 |
18 | |||
– |
k115.6 = 0.014 |
50 | |||||||
Pork (puree) |
– |
– |
18.4a |
1 |
– |
99–126.5 |
– |
Greenwood et al. 1944) |
|
Meat loaf |
– |
ak98 = 0.002511 |
276 |
Skjöldebrand, et al. (1983 |
|||||
(ground meat, potato starch and bread crumbs) |
baked in convection oven |
– |
k85.5 = 0.001244 |
27.1 |
1 |
0.955 |
70.5–98 |
557 |
|
– |
k70.5 = 0.000139 |
4,987 | |||||||
Milk | |||||||||
infant formula [15% protein, (milk-based); 24% lipids; 57% carbohydrates; 4% vitamins, minerals, water] |
Flexible plastic containers, no headspace |
Galdi et al. (1989) |
|||||||
With ferrous sulfate |
0.992 |
k45 = 2.18 × 10−6 |
3.18 × 105 | ||||||
0.915 |
k37 = 1.27 × 10−6 |
7.6 |
1 |
0.950 |
20–45 |
5.46 × 105 | |||
0.984 |
k20 = 0.741 × 10−6 |
9.35 × 105 | |||||||
With ferric glycinate |
0.920 |
k45 = 1.74 × 10−6 |
3.98 × 105 |
Galdi et al. (1989) |
|||||
0.967 |
k37 = 0.794 × 10−6 |
10.6 |
1 |
0.933 |
20–45 |
9.07 × 105 | |||
0.920 |
k20 = 0.370 × 10−6 |
18.73 × 105 | |||||||
Milk |
Pasteurized/UHT stored in 0.5-L glass bottles/dark |
– |
k85 = 13.68 × 10−4 |
507 |
Fink and Kessler (1985) |
||||
(3.5% fat) |
– |
k72 = 2.69 × 10−4 |
30.5 |
2 |
0.970 |
35–85 |
2,580 | ||
– |
k50 = 0.248 × 10−4 |
27,950 | |||||||
– |
k35 = 0.0396 × 10−4 |
175,000 | |||||||
Vitamin B1 |
Steady-state |
Kamman et al. (1981) |
|||||||
Pasta (enriched) |
conditions | ||||||||
aw = 0.44 |
0.992 |
k55 = 1.087 × 10−5 |
0.638 × 105 | ||||||
0.982 |
k45 = 0.154 × 10−5 |
27.7 |
1 |
0.976 |
25–55 |
4.50 × 105 | |||
0.931 |
k35 = 0.0451 × 10−5 |
15.37 × 105 | |||||||
0.875 |
k25 = 0.0138 × 10−5 |
50.23 × 105 | |||||||
aw = 0.54 |
0.995 |
k55 = 1.406 × 10−5 |
0.493 × 105 | ||||||
0.994 |
k45 = 0.267 × 10−5 |
29.0 |
1 |
0.996 |
25–55 |
2.60 × 105 | |||
0.979 |
k35 = 0.066 × 10−5 |
10.50 × 105 | |||||||
0.828 |
k25 = 0.0153 × 10−5 |
45.30 × 105 | |||||||
aw = 0.65 |
0.995 |
k55 = 1.809 × 10−5 |
0.383 × 105 |
Kamman et al. (1981) |
|||||
0.997 |
k45 = 0.435 × 10−5 |
24.2 |
1 |
0.992 |
25–55 |
1.59 × 105 | |||
0.983 |
k35 = 0.127 × 10−5 |
5.46 × 105 | |||||||
0.941 |
k25 = 0.0424 × 10−5 |
16.35 × 105 | |||||||
Square-wave fluctuations | |||||||||
aw = 0.44 | |||||||||
25–55°C |
0.930 |
k = 0.463 × 10−5 |
– |
1 |
– |
25–55 |
1.50 × 105 | ||
25–45°C |
0.973 |
k = 0.0807 × 10−5 |
– |
1 |
– |
25–45 |
8.59 × 105 | ||
aw = 0.54 | |||||||||
25–55°C |
0.954 |
k = 0.589 × 10−5 |
– |
1 |
– |
25–55 |
1.18 × 105 | ||
25–45°C |
0.960 |
k = 0.132 × 10−5 |
– |
1 |
– |
25–45 |
5.25 × 105 | ||
aw = 0.65 | |||||||||
25–55°C |
0.989 |
k = 0.194 × 10−5 |
– |
1 |
– |
25–55 |
3.57 × 105 | ||
25–45°C |
0.989 |
k = 0.882 × 10−5 |
– |
1 |
– |
25–45 |
0.786 × 105 | ||
Peas |
Bendix et al. (1951) |
||||||||
Brine packed |
– |
ak132.2 = 0.0351 |
20 | ||||||
(whole) |
– |
k126.7 = 0.0286 |
20.5 |
1 |
0.976 |
104–132 |
24 | ||
– |
k118.3 = 0.0122 |
57 | |||||||
– |
k104.4 = 0.0058 |
120 | |||||||
Vacuum packed |
– |
k132.2 = 0.0351 |
20 |
Bendix et al. (1951) |
|||||
(whole) |
– |
k126.7 = 0.0226 |
21.9 |
1 |
0.996 |
104–132 |
31 | ||
– |
k118.3 = 0.0142 |
49 | |||||||
– |
k104.4 = 0.0046 |
151 | |||||||
Vitamin B1 | |||||||||
Peas (puree) |
– |
k149 = 0.1659 |
4.2 |
Feliciotti and Esselen, (1957) |
|||||
– |
k139 = 0.0708 |
9.8 |
|||||||
– |
k129 = 0.0276 |
28.1 |
1 |
0.998 |
109–149 |
25 | |||
– |
k119 = 0.0114 |
61 | |||||||
– |
k109 = 0.0051 |
136 | |||||||
Peas (puree) |
– |
ak137.8 = 0.0435 |
16 |
Lenz and Lund (1977b) |
|||||
– |
k126.7 = 0.021 |
23.2 |
1 |
0.998 |
115–138 |
33 |
|||
– |
k115.6 = 0.0086 |
81 | |||||||
Peas (puree) |
– |
k137.8 = 0.03757 |
18 |
Mulley et al. (1975a) |
|||||
– |
k132.2 = 0.02206 |
27.8 |
1 |
0.964 |
121–138 |
31 | |||
– |
k126.7 = 0.01164 |
60 | |||||||
– |
k121.1 = 0.009328 |
74 | |||||||
Peas (puree, in brine) |
– |
k137.8 = 0.03897 |
18 | ||||||
– |
k132.2 = 0.03026 |
27.1 |
1 |
0.977 |
121–138 |
23 | |||
– |
k126.7 = 0.01584 |
44 | |||||||
– |
k121.1 = 0.01016 |
68 | |||||||
Spinach (puree) |
– |
k149 = 0.228 |
3.0 |
Feliciotti and Esselen, (1957) |
|||||
– |
k139 = 0.0825 |
8.4 |
|||||||
– |
k129 = 0.0336 |
28.2 |
1 |
0.993 |
109–149 |
21 | |||
– |
k119 = 0.0143 |
48 | |||||||
– |
k109 = 0.0067 |
103 | |||||||
Vitamin B2 (Riboflavin) |
Packaged in TDT cans |
Dennison, et al. (1977) |
|||||||
aw = 0.10 |
– |
a,bk37 = 0.00023 |
– |
1 |
– |
37 |
3,010 |
||
aw = 0.25 |
– |
k37 = 0.00188 |
– |
1 |
– |
37 |
369 | ||
aw = 0.40 |
– |
k37 = 0.00263 |
– |
1 |
– |
37 |
264 | ||
aw = 0.50 |
– |
k37 = 0.00411 |
– |
1 |
– |
37 |
169 | ||
aw = 0.65 |
– |
k37 = 0.00503 |
– |
1 |
– |
37 |
138 | ||
Breakfast cereal |
Packaged in paperboard boxes |
Dennison, et al. (1977) |
|||||||
aw = 0.10 |
– |
k30 = 0.0044 |
– |
1 |
– |
30 |
158 |
||
aw = 0.40 |
– |
k30 = 0.0043 |
– |
1 |
– |
30 |
161 | ||
aw = 0.85 |
– |
k30 = 0.0043 |
– |
1 |
– |
30 |
161 | ||
Vitamin B2 | |||||||||
Macaroni |
Woodcock et al. (1982) |
||||||||
Light exposure (lumens/m2) |
First phase | ||||||||
27.87 |
aw = 0.32 |
– |
a,bk55 = 1.38 |
0.502 | |||||
– |
k25 = 1.26 |
0.550 | |||||||
27.87 |
aw = 0.44 |
– |
k55 = 1.32 |
0.525 | |||||
– |
k35 = 1.52 |
0.546 | |||||||
– |
k25 = 1.56 |
0.444 | |||||||
18.58 |
aw = 0.44 |
– |
k55 = 1.72 |
0.403 | |||||
– |
k35 = 1.27 |
0.6–2.0a |
1 |
– |
25–55 |
0.546 | |||
– |
k25 = 1.0 |
0.533 | |||||||
9.29 |
aw = 0.44 |
– |
k55 = 1.32 |
0.525 | |||||
– |
k35 = 1.53 |
0.453 | |||||||
– |
k25 = 1.37 |
0.506 | |||||||
Second phase | |||||||||
27.87 |
aw = 0.32 |
– |
k55 = 0.55 |
1.260 | |||||
– |
k25 = 0.78 |
0.889 | |||||||
27.87 |
aw = 0.44 |
– |
k55 = 0.87 |
0.797 | |||||
– |
k35 = 0.55 |
1.260 | |||||||
– |
k25 = 0.57 |
1.2 20 | |||||||
18.58 |
aw = 0.44 |
– |
k55 = 1.0 |
0.630 | |||||
– |
k35 = 0.85 |
1.9–4.3a |
1 |
– |
25–55 |
0.815 | |||
– |
k25 = 0.84 |
0.825 | |||||||
9.29 |
aw = 0.44 |
– |
k55 = 1.33 |
0.521 | |||||
– |
k35 = 0.0 |
0.866 | |||||||
– |
k25 = 0.0 |
0.990 | |||||||
Vitamin B2 | |||||||||
Macaroni |
Light exposure = 150 ft-c at 4°C |
Furuya et al. (1984) |
|||||||
Whole |
First phase |
0.83 |
k4 = 0.326 × 10−3 |
– |
1 |
– |
4 |
2.13 × 103 | |
Second phase |
0.80 |
k4 = 0.764 × 10−5 |
– |
1 |
– |
4 |
90.73 × 103 | ||
Particulate |
First phase |
0.88 |
k4 = 0.386 × 10−3 |
– |
1 |
– |
4 |
1.80 × 103 | |
Second phase |
0.75 |
k4 = 1.181 × 10−5 |
– |
1 |
– |
4 |
58.69 × 103 | ||
Milk |
Galdi et al. (1989) |
||||||||
Infant formula |
Flexible plastic containers | ||||||||
[15% protein (milk-based); 24% lipids; 57% carbohydrates; 4% vitamins, minerals, water] |
(no head space) | ||||||||
With ferrous sulfate |
0.952 |
k45 = 3.06 × 10−6 |
2.27 × 105 | ||||||
0.939 |
k37 = 2.50 × 10−6 |
8.0 |
1 |
0.986 |
20–45 |
2.77 × 105 | |||
0.930 |
k20 = 1.07 × 10−6 |
6.48 × 105 | |||||||
With ferric glycinate |
0.968 |
k45 = 2.186 × 10−6 |
3.18 × 105 | ||||||
0.796 |
k37 = 0.949 × 10−6 |
27.0 |
1 |
0.994 |
20–45 |
7.30 × 105 | |||
0.907 |
k20 = 0.058 × 10−6 |
120 × 105 | |||||||
Milk (whole) |
Container type: |
Singh et al. (1975) |
|||||||
(1-gal samples) |
Glass | ||||||||
Light intensity: |
150 ft-c |
– |
k10 = 1.83 × 10−5 |
37.88 × 103 | |||||
– |
k4.4 = 1.46 × 10−5 |
6.6 |
1 |
0.098 |
1.7–10 |
47.48 × 103 | |||
– |
k1.7 = 1.28 × 10−5 |
54.15 × 103 | |||||||
300 ft-c |
– |
k10 = 5.37 × 10−5 |
12.91 × 103 | ||||||
– |
k4.4 = 4.04 × 10−5 |
8.1 |
1 |
0.999 |
1.7–10 |
17.16 × 103 | |||
– |
k1.7 = 3.48 × 10−5 |
19.92 × 103 | |||||||
450 ft-c |
– |
k10 = 5.98 × 10−5 |
20.8 |
1 |
– |
4.4–10 |
11.52 × 103 | ||
– |
k4.4 = 5.55 × 10−5 |
18.02 × 103 | |||||||
Vitamin B2 |
Blow-molded poly-ethylene (BMP) |
Singh et al. (1975) |
|||||||
Light intensity: |
150 ft-c |
– |
k10 = 1.76 × 10−5 |
3.94 × 104 | |||||
– |
k4.4 = 0.998 × 10−5 |
16.2 |
1 |
0.999 |
1.7–10 |
6.95 × 104 | |||
– |
k1.7 = 0.735 × 10−5 |
9.43 × 104 | |||||||
300 ft-c |
– |
k10 = 5.19 × 10−5 |
1.34 × 104 | ||||||
– |
k4.4 = 3.79 × 10−5 |
11.4 |
1 |
0.962 |
1.7–10 |
1.83 × 104 | |||
– |
k1.7 = 2.75 × 10−5 |
2.52 × 104 | |||||||
450 ft-c |
– |
k10 = 8.75 × 10−5 |
11.9 |
1 |
– |
4.4–10 |
0.792 × 104 | ||
– |
k4.4 = 5.70 × 10−5 |
1.22 × 104 | |||||||
Gold-pigmented | |||||||||
BMP | |||||||||
Light intensity: |
150 ft-c |
– |
k10 = 0.655 × 10−5 |
10.58 × 104 | |||||
– |
k4.4 = 0.570 × 10−5 |
11.6 |
1 |
0.749 |
1.7–10 |
12.16 × 104 | |||
– |
k1.7 = 0.327 × 10−5 |
21.20 × 104 | |||||||
300 ft-c |
– |
k10 = 1.53 × 10−5 |
4.53 × 104 | ||||||
– |
k4.4 = 1.16 × 10−5 |
20.5 |
1 |
0.773 |
1.7–10 |
5.98 × 104 | |||
– |
k1.7 = 0.453 × 10−5 |
15.30 × 104 | |||||||
450 ft-c |
– |
k10 = 0.920 × 10−5 |
15.5 |
1 |
– |
4.4–10 |
7.53 × 104 | ||
– |
k4.4 = 0.527 × 10−5 |
13.15 × 104 | |||||||
Paperboard | |||||||||
Light intensity: |
150 ft-c |
– |
k10 = 0.453 × 10−5 |
15.30 × 104 | |||||
– |
k4.4 = 0.648 × 10−5 |
14.2 |
1 |
0.313 |
1.7–10 |
10.70 × 104 | |||
– |
k1.7 = 0.170 × 10−5 |
40.77 × 104 | |||||||
300 ft-c |
– |
k10 = 1.75 × 10−5 |
3.96 × 104 | ||||||
– |
k4.4 = 1.547 × 10−5 |
49.8 |
1 |
0.916 |
1.7–10 |
12.67 × 104 | |||
– |
k1.7 = 0.103 × 10−5 |
67.30 × 104 | |||||||
450 ft-c |
– |
k10 = 0.302 × 10−5 |
23.0 |
1 |
– |
4.4–10 |
22.95 × 104 | ||
– |
k4.4 = 0.690 × 10−5 |
10.05 × 104 | |||||||
Vitamin B2 | |||||||||
Milk (skim) |
Light exposure = 150 ft-c at 4°C |
Furuya et al. (1984) |
|||||||
Liquid | |||||||||
First phase |
0.97 |
k4 = 0.834 × 10−3 |
– |
1 |
– |
4 |
831 | ||
Milk (nonfat dry milk powder) | |||||||||
First phase |
0.90 |
k4 = 0.190 × 10−3 |
– |
1 |
– |
4 |
3,648 | ||
Second phase |
0.68 |
k4 = 2.50 × 10−3 |
– |
1 |
– |
4 |
27,730 | ||
Vitamin B3/Niacin |
Nisha et al. (2009) |
||||||||
Potatoes |
10 g potato cubes (1 cm3)/30 g water in 100 ml beaker | ||||||||
0.995 |
k120 = 3.10 × 10−3 |
224 | |||||||
0.987 |
k110 = 2.70 × 10−3 |
257 | |||||||
Heat: |
0.992 |
k100 = 2.50 × 10−3 |
277 | ||||||
waterbath 50–100°C |
0.988 |
k90 = 2.00 × 10−3 |
4.2 |
1 |
0.992 |
50–120 |
347 | ||
autoclave 110–120°C |
0.989 |
k80 = 1.60 × 10−3 |
433 | ||||||
Time: 0–60 min |
0.989 |
k70 = 1.40 × 10−3 |
495 | ||||||
0.994 |
k60 = 1.20 × 10−3 |
578 | |||||||
0.991 |
k50 = 1.00 × 10−3 |
693 | |||||||
Niacin solutions |
1 ml niacin soln. (900 mg/100 ml water) | ||||||||
0.988 |
k120 = 3.40 × 10−3 |
204 | |||||||
adjust pH 4.5/w/10N NaOH |
0.985 |
k110 = 3.10 × 10−3 |
224 | ||||||
0.991 |
k100 = 2.70 × 10−3 |
257 | |||||||
0.994 |
k90 = 2.20 × 10−3 |
4.3 |
1 |
0.994 |
50–120 |
315 | |||
0.986 |
k80 = 1.80 × 10−3 |
385 | |||||||
0.990 |
k70 = 1.50 × 10−3 |
462 | |||||||
0.990 |
k60 = 1.30 × 10−3 |
533 | |||||||
0.987 |
k50 = 1.10 × 10−3 |
630 | |||||||
Nicotinic acid | |||||||||
Averrhoa bilimbi fruit |
Muhamed et al. (2015) |
||||||||
Process: | |||||||||
extract |
– |
k120 = 7.22 × 10−2 |
9.6 | ||||||
extract |
– |
k100 = 2.57 × 10−2 |
8.8 |
1 |
0.995 |
90–120 |
27.0 | ||
extract |
– |
k90 = 3.11 × 10−2 |
22.3 | ||||||
Assay: UHPLC-QTOF |
pure solution |
– |
k90 = 2.50 × 10−2 |
90 |
27.7 | ||||
Vitamin B6 | |||||||||
Breakfast cereal model system |
Toasted |
– |
ak200 = 0.4895 |
1.4 |
Evans et al. (1981) |
||||
– |
k185 = 0.1688 |
30.0 |
1 |
0.999 |
155–200 |
4.1 | |||
Pyridoxine |
– |
k170 = 0.0522 |
13 | ||||||
– |
k155 = 0.0174 |
40 | |||||||
Vitamin B6 | |||||||||
Casein-based liquid model system |
Gregory and Hiner (1983) |
||||||||
Pyridoxine |
0.98 |
k133 = 0.0083 |
84 |
||||||
0.98 |
k118 = 0.0025 |
28.6 |
1 |
0.995 |
105–133 |
277 | |||
0.98 |
k105 = 0.0006 |
1155 | |||||||
Pyridoxamine |
0.99 |
k133 = 0.0187 |
37 |
Gregory and Hiner (1983) |
|||||
0.98 |
k118 = 0.0064 |
23.8 |
1 |
0.999 |
105–133 |
108 |
|||
0.98 |
k105 = 0.0021 |
330 | |||||||
Pyridoxal |
0.94 |
k133 = 0.0266 |
26 | ||||||
0.98 |
k118 = 0.0092 |
20.7 |
1 |
0.998 |
105–133 |
75 | |||
0.96 |
k105 = 0.004 |
173 | |||||||
Cauliflower (puree) |
Heated in 125-ml flasks |
– |
ak137.7 = 0.01145 |
61 |
Navankasattusas and Lund (1982) |
||||
Overall B6 |
– |
k125.6 = 0.00652 |
13.8 |
1 |
0.990 |
105.9–137.7 |
106 |
||
– |
k114.6 = 0.00453 |
(27 + 2)a |
pseudo-1a |
153 | |||||
– |
k105.9 = 0.00265 |
262 | |||||||
Vitamin B12 | |||||||||
Milk (cow) |
Watanabe et al. (1998) |
||||||||
Conventional boil 30 min/CUT = ~7.5 min |
0.990 |
k100 = 0.018279 |
– |
1 |
– |
100 |
38 |
||
Microwave 6 min/CUT = ~ 2 min |
0.999 |
k100 = 0.091545 |
– |
1 |
– |
100 |
7.6 | ||
Folates | |||||||||
Folic acid | |||||||||
Apple juice |
pH 3.4 |
– |
ak140 = 0.0137 |
51 |
Mnkeni and Beveridge (1982) |
||||
Method: L. casei |
– |
k130 = 0.00792 |
88 |
||||||
– |
k121 = 0.00468 |
19.9 |
1 |
0.998 |
100–140 |
148 | |||
– |
k110 = 0.00202 |
343 | |||||||
– |
k100 = 0.00105 |
660 | |||||||
Folic acid | |||||||||
Tomato juice |
pH 4.3 |
– |
k140 = 0.01205 |
58 |
Mnkeni and Beveridge (1982) |
||||
– |
k130 = 0.006567 |
106 |
|||||||
– |
k121 = 0.003417 |
19.9 |
1 |
0.996 |
100–140 |
203 | |||
– |
k110 = 0.001733 |
400 | |||||||
– |
k100 = 0.0009333 |
743 | |||||||
Citrate buffer |
pH 3.0 |
– |
k140 = 0.03933 |
18 | |||||
– |
k130 = 0.02767 |
25 | |||||||
– |
k121 = 0.0124 |
22.4 |
1 |
0.989 |
100–140 |
56 | |||
– |
k110 = 0.004883 |
142 | |||||||
– |
k100 = 0.002417 |
287 | |||||||
pH 4.0 |
– |
k140 = 0.014 |
50 | ||||||
– |
k130 = 0.009667 |
72 | |||||||
– |
k121 = 0.0039 |
19.4 |
1 |
0.982 |
100–140 |
178 | |||
– |
k110 = 0.002133 |
325 | |||||||
– |
k100 = 0.001233 |
562 | |||||||
Folic acid |
pH 5.0 |
– |
k140 = 0.00345 |
201 |
Mnkeni and Beveridge (1982) |
||||
– |
k130 = 0.001867 |
371 |
|||||||
– |
k121 = 0.0008833 |
17.8 |
1 |
0.975 |
100–140 |
785 | |||
– |
k110 = 0.0005167 |
1,341 | |||||||
– |
k100 = 0.00035 |
1,980 | |||||||
Folic acid | |||||||||
Phosphate buffer |
Nguyen et al. (2003) |
||||||||
pH 7.0 |
Capillary tubes: |
– |
k160 = 0.00473 |
147 | |||||
HPLC |
1.5 × 150 mm |
– |
k140 = 0.00126 |
a12.35 |
1 |
0.8 |
120–160 |
550 | |
– |
k120 = 0.00104 |
666 | |||||||
Folic acid | |||||||||
Model system (solid) |
Hawkes and Villota (1989a) |
||||||||
Avicel/glycerol |
Heat in 6 × 50 mm glass tubes | ||||||||
(60:40) | |||||||||
Initial folate conc. = 0.2 mg/g solids |
MC = g H2O/100 g solids | ||||||||
6.8 |
0.997 |
k80 = 0.0005109 |
1,357 | ||||||
0.994 |
k70 = 0.0003386 |
9.47 |
1 |
0.998 |
50–80 |
2,047 | |||
0.961 |
k60 = 0.0002298 |
3,016 | |||||||
0.984 |
k50 = 0.0001436 |
4,827 | |||||||
11.0 |
0.986 |
k80 = 0.000521 |
1,330 | ||||||
0.977 |
k70 = 0.0003386 |
9.39 |
1 |
0.998 |
50–80 |
2,047 | |||
Cold extraction – pH 8.0 phos. Buffer |
0.998 |
k60 = 0.0002365 |
2,931 | ||||||
0.952 |
k50 = 0.0001475 |
4,699 | |||||||
Assay: HPLC |
18.0 |
0.995 |
k80 = 0.0006502 |
1,066 | |||||
Detector: UV/VIS |
0.990 |
k70 = 0.0004199 |
8.65 |
1 |
0.995 |
50–80 |
1,651 | ||
A280 |
0.990 |
k60 = 0.0003033 |
2,285 | ||||||
0.997 |
k50 = 0.0002025 |
3,423 | |||||||
27.0 |
0.993 |
k80 = 0.0007266 |
954 | ||||||
0.993 |
k70 = 0.0005189 |
8.82 |
1 |
0.998 |
50–80 |
1,336 | |||
0.984 |
k60 = 0.0003357 |
2,065 | |||||||
0.999 |
k50 = 0.0002294 |
3,022 | |||||||
40.0 |
0.998 |
k80 = 0.0008392 |
826 | ||||||
0.998 |
k70 = 0.0005628 |
9.66 |
1 |
0.996 |
50–80 |
1,232 | |||
0.992 |
k60 = 0.0003463 |
2,002 | |||||||
0.998 |
k50 = 0.0002379 |
2,914 | |||||||
Folic acid | |||||||||
Strawberries (fresh/whole – Zephyr) |
Strålsjö et al. (2003) |
||||||||
Total folate |
Stored: 0–9 days |
0.998 |
k4 = 0.000025744 |
– |
1 |
– |
4 |
26,925 | |
Open air |
0.996 |
k20 = 0.00010381 |
– |
1 |
– |
20 |
6,677 | ||
Swiss chard |
Storage conditions: |
Gami and Chen (1985) |
|||||||
Plastic bag |
0.998 |
k21 = 0.000135 |
– |
1 |
– |
21 |
5,134 |
||
Moist conditions |
0.996 |
k21 = 0.000149 |
– |
1 |
– |
21 |
4,652 | ||
Open air |
– |
k40 = 0.001645 |
421 | ||||||
– |
k35 = 0.001042 |
22.9 |
1 |
0.996 |
4–40 |
665 | |||
– |
k21 = 0.000205 |
3,381 | |||||||
– |
k4 = 0.00001433 |
48,370 | |||||||
5-Methyltetrahydrofolate | |||||||||
Apple juice |
pH 3.4 |
0.97 |
k70 = 0.249 |
2.8 |
Mnkeni and Beveridge (1983) |
||||
Method: L. casei |
(unlimited O2) |
0.95 |
k60 = 0.193 |
7.9 |
1 |
0.99 |
50–70 |
3.6 |
|
0.96 |
k50 = 0.123 |
5.6 | |||||||
pH 3.4 |
0.89 |
k70 = 0.00 |
3.5 | ||||||
(limited O2, at 5.3 ppm) |
0.92 |
k60 = 0.126 |
9.5 |
1 |
0.98 |
50–70 |
5.5 | ||
0.99 |
k50 = 0.089 |
7.8 | |||||||
Tomato juice |
pH 4.3 |
0.93 |
k130 = 1.065 |
0.65 | |||||
(unlimited O2) |
0.92 |
k121 = 0.792 |
10.6 |
1 |
0.99 |
100–130 |
0.88 | ||
0.95 |
k110 = 0.508 |
1.4 | |||||||
0.99 |
k100 = 0.374 |
1.9 | |||||||
pH 4.3 |
0.98 |
k130 = 0.488 |
1.4 | ||||||
(limited O2, at 5.3 ppm) |
0.95 |
k121 = 0.353 |
10.8 |
1 |
0.99 |
100–130 |
2.0 | ||
0.97 |
k110 = 0.259 |
2.7 | |||||||
0.98 |
k100 = 0.16 |
4.3 | |||||||
5-Methyltetrahydrofolate | |||||||||
Model system (aqueous solutions) |
Hawkes and Villota (1989a) |
||||||||
Glycerol/water |
Heat in 6 × 50 mm glass tubes | ||||||||
Initial folate conc. = 0.1 mg/g solids |
g glycerol/g water | ||||||||
HPLC |
0.996 |
k85 = 0.00645 |
107.5 | ||||||
0 |
0.998 |
k80 = 0.005 |
10.8 |
1 |
0.989 |
75–85 |
138.6 | ||
0.993 |
k75 = 0.00417 |
166.2 | |||||||
0.991 |
k85 = 0.00552 |
125.6 | |||||||
0.0526 |
0.998 |
k80 = 0.00378 |
17.2 |
1 |
0.996 |
183.4 | |||
0.995 |
k75 = 0.00276 |
251.1 | |||||||
g glycerol/g water | |||||||||
0.991 |
k85 = 0.00483 |
143.5 | |||||||
0.1100 |
0.999 |
k80 = 0.00338 |
17.0 |
1 |
0.999 |
205.1 | |||
0.989 |
k75 = 0.00243 |
285.2 | |||||||
0.989 |
k85 = 0.0041 |
169.1 | |||||||
0.2500 |
0.998 |
k80 = 0.0028 |
17.1 |
1 |
0.996 |
247.6 | |||
0.989 |
k75 = 0.00205 |
338.1 | |||||||
5-Methyltetrahydrofolate | |||||||||
Phosphate buffer |
Micro-scale |
Viberg et al. (1997) |
|||||||
UHT simulation | |||||||||
pH 7.0 | |||||||||
anaerobic |
O2 at 0.3 ppm |
– |
k150 = 1.63 |
0.425 | |||||
– |
k140 = 1.12 |
14.9 |
1 |
0.989 |
110–150 |
0.619 | |||
– |
k120 = 0.488 |
1.420 | |||||||
– |
k110 = 0.242 |
2.864 | |||||||
aerobic |
O2 at 6.8 ppm |
– |
k150 = 3.18 |
0.218 | |||||
– |
k140 = 1.65 |
18.3 |
1 |
0.994 |
110–150 |
0.132 | |||
– |
k120 = 0.638 |
(25.5) |
(2) |
0.998 |
0.207 | ||||
– |
k110 = 0.3 |
0.690 | |||||||
Folates – L-5-Methyltetrahydrofolic acid |
|||||||||
Phosphate buffer |
Capillary tubes: |
Nguyen et al. (2003) |
|||||||
1.5 × 150 mm |
– |
k90 = 0.06831 |
10.2 | ||||||
pH 7.0 |
– |
k80 = 0.02814 |
19.1 |
1 |
0.993 |
65–90 |
24.6 | ||
– |
k70 = 0.01306 |
53.1 | |||||||
– |
k65 = 0.00973 |
71.2 | |||||||
L-5-Methyltetrahydrofolic acid |
|||||||||
Model system – pH 4.0 |
Liu et al. (2012) |
||||||||
50 μg/ml in 0.1M acetate buffer |
Heat: Waterbath (21–75°C) |
k75 = 22.5 × 10−3 |
30.8 | ||||||
k50 = 8.20 × 10−3 |
22.94 |
1 |
0.911 |
21–75 |
84.5 | ||||
k37 = 1.20 × 10−3 |
577.6 | ||||||||
k21 = 0.050 × 10−3 |
13862.9 | ||||||||
Model system – pH 6.9 |
Analysis: HPLC |
k75 = 210.5 × 10−3 |
3.3 | ||||||
50 μg/ml in 0.1M phosphate buffer |
Detectors: DAD (A290) |
k50 = 30.9 × 10−3 |
17.37 |
1 |
0.972 |
21–75 |
22.4 | ||
k37 = 5.46 × 10−3 |
127.0 | ||||||||
Fluorescence (Ex: A290/Em: A365) |
k21 = 2.50 × 10−3 |
277.3 | |||||||
NaAsc*:L-5-CH3THF | |||||||||
0:1 |
Heat: Waterbath (50°C) |
k50 = 33.7 × 10−3 |
20.5 |
Liu et al. (2012) |
|||||
100:1 |
k50 = 9.80 × 10−3 |
70.7 | |||||||
500:1 |
k50 = 4.80 × 10−3 |
– |
1 |
– |
50 |
144.4 | |||
2000:1 |
k50 = 2.10 × 10−3 |
330.1 | |||||||
5000:1 |
k50 = 0.20 × 10−3 |
3465.7 | |||||||
* Sodium ascorbate |
|||||||||
Pantothenic acid | |||||||||
Averrhoa bilimbi fruit |
Muhamed et al. (2015) |
||||||||
Process: | |||||||||
extract |
– |
k120 = 8.37 × 10−2 |
8.3 | ||||||
extract |
– |
k100 = 2.31 × 10−2 |
11.2 |
1 |
0.994 |
90–120 |
30.0 | ||
extract |
– |
k90 = 2.88 × 10−2 |
24.1 | ||||||
Assay: UHPLC-QTOF |
pure solution |
– |
k90 = 2.03 × 10−2 |
90 |
34.1 | ||||
Catechin | |||||||||
Averrhoa bilimbi fruit |
Muhamed et al. (2015) |
||||||||
Process: | |||||||||
extract |
– |
k120 = 8.69 × 10−2 |
8.0 |
||||||
extract |
– |
k100 = 7.07 × 10−2 |
1.3 |
1 |
0.999 |
90–120 |
9.8 | ||
Assay: UHPLC-QTOF |
extract |
– |
k90 = 7.79 × 10−2 |
8.9 | |||||
pure solution |
– |
k90 = 4.92 × 10−2 |
90 |
14.1 | |||||
Pantothenic acid (PA) | |||||||||
Meat puree (beef) |
Hamm and Lund (1978) |
||||||||
Free PA |
pH 5.4 |
– |
– |
a20 |
1 |
– |
118–143 |
– |
|
Total PA |
pH 5.4 |
– |
– |
25 |
1 |
– |
118–143 |
– | |
Pea puree | |||||||||
Free PA |
pH 7.0 |
– |
– |
38 |
1 |
– |
118–143 |
– | |
Total PA |
pH 7.0 |
– |
– |
36 |
1 |
– |
118–143 |
– | |
Buffered PA |
pH 4.0 |
– |
– |
20 |
1 |
– |
118–143 |
– | |
pH 5.0 |
– |
– |
22 |
1 |
– |
118–143 |
– | ||
pH 6.0 |
– |
– |
27 |
1 |
– |
118–143 |
– | ||
Fat Soluble Vitamins: |
|||||||||
Vitamin A | |||||||||
Beef liver puree |
Trans-retinol |
– |
k126.7 = 0.09738 |
26.9 |
7.1 |
Wilkinson et al. (1981) |
|||
– |
k122.1 = 0.05766 |
12 |
|||||||
– |
k118.3 = 0.0408 |
1 |
0.995 |
102.9–126.7 |
17 | ||||
– |
k111.0 = 0.02316 |
30 | |||||||
– |
k102.9 = 0.01074 |
65 | |||||||
(% fat/protein/moisture/ash + carbohydrate) | |||||||||
Sample 1: |
10.9/21.6/63.2/4.3 |
a0.992 |
k122 = 0.006162 |
26.4 |
112 | ||||
0.993 |
k112 = 0.002694 |
1 |
0.999 |
102–122 |
257 | ||||
0.986 |
k102 = 0.001026 |
676 | |||||||
Sample 2: |
27.9/11.7/56.0/4.4 |
0.993 |
k122 = 0.00348 |
199 | |||||
0.984 |
k112 = 0.001392 |
24.2 |
1 |
0.993 |
102–122 |
498 | |||
0.990 |
k102 = 0.000672 |
1,031 | |||||||
Sample 3: |
10.0/13.0/72.2/4.8 |
0.996 |
k122 = 0.007704 |
23.9 |
90 |
Wilkinson et al. (1982) |
|||
0.997 |
k112 = 0.003696 |
1 |
0.998 |
102–122 |
188 |
||||
0.999 |
k102 = 0.001524 |
455 | |||||||
Sample 4: |
26.1/20.2/51.7/2.0 |
0.979 |
k122 = 0.002718 |
27.0 |
255 | ||||
0.925 |
k112 = 0.00078 |
1 |
0.953 |
102–122 |
889 | ||||
0.998 |
k102 = 0.000432 |
1,605 | |||||||
(15% protein/17–30% fat) |
ppm Cu + 2/pH/% moisture | ||||||||
Sample 1: |
6/5.6/55 |
a0.999 |
k122 = 0.00273 |
a21.8 |
1 |
– |
102–122 |
254 | |
0.974 |
k102 = 0.000666 |
1,041 | |||||||
Sample 2: |
30/5.6/55 |
0.994 |
k122 = 0.001213 |
8.6 |
1 |
– |
102–122 |
571 | |
0.994 |
k102 = 0.000774 |
896 | |||||||
Sample 3: |
6/7.0/55 |
0.975 |
k122 = 0.002781 |
28.0 |
1 |
– |
102–122 |
255 | |
0.980 |
k102 = 0.000498 |
1,392 | |||||||
Sample 4: |
30/7.0/55 |
0.971 |
k122 = 0.001368 |
8.6 |
1 |
– |
102–122 |
507 | |
0.998 |
k102 = 0.000666 |
1,041 | |||||||
Sample 5: |
6/5.6/68 |
0.998 |
k122 = 0.01102 |
28.2 |
1 |
– |
102–122 |
63 | |
0.996 |
k102 = 0.00165 |
420 | |||||||
Sample 6: |
30/5.6/68 |
0.999 |
k122 = 0.00921 |
23.2 |
1 |
– |
102–122 |
75 | |
0.988 |
k102 = 0.00227 |
305 | |||||||
Sample 7: |
6/7.0/68 |
0.998 |
k122 = 0.01069 |
28.9 |
1 |
– |
102–122 |
65 | |
0.996 |
k102 = 0.001542 |
450 | |||||||
Sample 8: |
30/7.0/68 |
0.993 |
k122 = 0.005028 |
17.2 |
1 |
– |
102–122 |
138 | |
0.999 |
k102 = 0.001458 |
475 | |||||||
Vitamin A | |||||||||
Carotene (crystalline) |
Heated dry in 2-ml glass vials (50–150°C/10–30 min) |
Chen et al. (1994) |
|||||||
All-trans-α-Carotene | |||||||||
⇆ 13-cis-α-carotene | |||||||||
Forward reaction (k1) |
HPLC analysis dissolved in hexane for analysis |
0.994 |
ak150 = 0.0323→ |
– |
1 |
– |
150 |
– | |
Reverse reaction (k−1) |
k150 = 0.0998← |
– |
1 |
– |
150 |
– | |||
⇆ 9-cis-α-carotene | |||||||||
Forward reaction (k1) |
0.980 |
k150 = 0.0038→ |
– |
1 |
– |
150 |
– | ||
Reverse reaction (k−1) |
k150 = 0.0449← |
– |
1 |
– |
150 |
– | |||
⇆ 15-cis-α-carotene | |||||||||
Forward reaction (k1) |
0.990 |
k150 = 0.0067→ |
– |
1 |
– |
150 |
– | ||
Reverse reaction (k−1) |
k150 = 0.0407← |
– |
1 |
– |
150 |
– | |||
All-trans-β-Carotene |
Chen et al. (1994) |
||||||||
⇆ 13-cis-β-carotene | |||||||||
Forward reaction (k1) |
0.996 |
k150 = 0.0125→ |
– |
1 |
– |
150 |
– | ||
Reverse reaction (k−1) |
dissolved in MeOH: CHCl3 (45:55) for analysis |
k150 = 0.0339← |
– |
1 |
– |
150 |
– | ||
⇆ 9-cis-β-carotene | |||||||||
Forward reaction (k1) |
0.990 |
k150 = 0.0043→ |
– |
1 |
– |
150 |
– | ||
Reverse reaction (k−1) |
k150 = 0.0184← |
– |
1 |
– |
150 |
– | |||
Vitamin A | |||||||||
Corn flakes (fortified) |
Storage: |
Kim et al. (2000) |
|||||||
Vitamin A palmitate |
23–45°C, up to 16 wks |
0.960 |
ak45 = 1.2639 × 105 |
– |
apparent-2 |
– |
23–45 |
5.484 × 104 | |
(15% RDI) |
0.954 |
k23 = 1.0208 × 105 |
– |
apparent-2 |
– |
23–45 |
6.790 × 104 | ||
Vitamin A palmitate |
Packaging: cardboard box with plastic liner |
0.960 |
k45 = 17.5694 × 105 |
– |
apparent-1 |
– |
23–45 |
0.395 × 104 | |
(plus B1, B6, B12, C, D2 & D3 – 15% RDI each) |
0.793 |
k23 = 4.5139 × 105 |
– |
apparent-1 |
– |
23–45 |
1.536 × 104 | ||
Carotenoids | |||||||||
β-Cryptoxanthin |
Solutions: |
0.9997 |
k80 = 14.4 × 10−3 |
48.0 |
Mitra et al. (2016) |
||||
(extracted from |
50:50 EtOH:Water |
0.9970 |
k70 = 11.1 × 10−3 |
62.4 | |||||
Kocuria marina) |
Time: 9 hrs |
0.9961 |
k60 = 9.49 × 10−3 |
73.1 | |||||
Transparent flasks |
0.9933 |
k50 = 8.60 × 10−3 |
3.2 |
1 |
0.952 |
25–80 |
80.6 | ||
Fluorescent light |
0.9958 |
k40 = 7.43 × 10−3 |
93.3 | ||||||
Analysis: UV-VIS |
0.9996 |
k37 = 6.50 × 10−3 |
106.6 | ||||||
(A445) |
0.9991 |
k25 = 6.22 × 10−3 |
111.5 | ||||||
β-Cryptoxanthin |
Effect of pH: | ||||||||
1 ml sample/3 ml buffer |
0.9988 |
k25 = 4.15 × 10−4 |
1670.2 | ||||||
0.9985 |
k25 = 2.75 × 10−4 |
2520.5 | |||||||
0.9999 |
k25 = 2.45 × 10−4 |
– |
1 |
– |
25 |
2829.2 | |||
0.9997 |
k25 = 2.52 × 10−4 |
2754.2 | |||||||
0.9996 |
k25 = 1.37 × 10−4 |
5071.8 | |||||||
0.9992 |
k25 = 1.03 × 10−4 |
6707.9 | |||||||
Vitamin A |
Liu et al. (2015) |
||||||||
Emulsions (O/W/w/β-Carotene) | |||||||||
Control |
Composition: |
– |
k65 = 34.2 × 10−5 |
0.203 × 10−4 | |||||
(no antioxidants) |
Gum arabic |
– |
k45 = 6.68 × 10−5 |
5.1 |
1 |
0.679 |
4–65 |
1.04 × 10−4 | |
Carotene |
– |
k25 = 6.63 × 10−5 |
1.05 × 10−4 | ||||||
Antioxidant: |
Antioxidant |
– |
k4 = 4.92 × 10−5 |
1.41 × 10−4 | |||||
0.01% Ascorbyl Palmitate |
– |
k65 = 15.5 × 10−5 |
0.446 × 10−4 | ||||||
– |
k45 = 3.67 × 10−5 |
7.8 |
1 |
0.874 |
4–65 |
1.89 × 10−4 | |||
– |
k25 = 1.51 × 10−5 |
4.60 × 10−4 | |||||||
– |
k4 = 1.15 × 10−5 |
6.04 × 10−4 | |||||||
0.05% Ascorbyl Palmitate |
– |
k65 = 15.2 × 10−5 |
0.455 × 10−4 | ||||||
– |
k45 = 2.47 × 10−5 |
10.9 |
1 |
0.954 |
4–65 |
2.81 × 10−4 | |||
– |
k25 = 1.26 × 10−5 |
5.52 × 10−4 | |||||||
– |
k4 = 0.347 × 10−5 |
20.0 × 10−4 | |||||||
0.10% Ascorbyl Palmitate |
– |
k65 = 15.9 × 10−5 |
0.436 × 10−4 |
Liu et al. (2015) |
|||||
– |
k45 = 3.60 × 10−5 |
12.2 |
1 |
0.988 |
4–65 |
1.93 × 10−4 | |||
– |
k25 = 0.965 × 10−5 |
7.18 × 10−4 | |||||||
– |
k4 = 0.278 × 10−5 |
24.9 × 10−4 | |||||||
0.01% α-Tocopherol |
– |
k65 = 13.2 × 10−5 |
0.524 × 10−4 | ||||||
– |
k45 = 2.35 × 10−5 |
9.6 |
1 |
0.937 |
4–65 |
2.95 × 10−4 | |||
– |
k25 = 1.38 × 10−5 |
5.02 × 10−4 | |||||||
– |
k4 = 0.458 × 10−5 |
15.1 × 10−4 | |||||||
0.05% α-Tocopherol |
– |
k65 = 9.07 × 10−5 |
0.765 × 10−4 | ||||||
– |
k45 = 1.70 × 10−5 |
10.1 |
1 |
0.955 |
4–65 |
4.08 × 10−4 | |||
– |
k25 = 0.993 × 10−5 |
6.98 × 10−4 | |||||||
– |
k4 = 0.263 × 10−5 |
26.3 × 10−4 | |||||||
0.10% α-Tocopherol |
– |
k65=9.53 × 10−5 |
0.727 × 10−4 | ||||||
– |
k45 = 2.45 × 10−5 |
12.3 |
1 |
0.996 |
4–65 |
2.83 × 10−4 | |||
– |
k25 = 0.847 × 10−5 |
8.19 × 10−4 | |||||||
– |
k4 = 0.153 × 10−5 |
45.4 × 10−4 | |||||||
0.01% TBHQ |
– |
k65 = 23.3 × 10−5 |
0.297 × 10−4 | ||||||
– |
k45 = 3.82 × 10−5 |
1 |
4–65 |
1.82 × 10−4 | |||||
– |
k25 = 3.45 × 10−5 |
2.01 × 10−4 | |||||||
– |
k4 = 2.00 × 10−5 |
3.47 × 10−4 | |||||||
Antioxidant: | |||||||||
0.05% TBHQ |
– |
k65 = 18.7 × 10−5 |
0.371 × 10−4 | ||||||
– |
k45 = 2.45 × 10−5 |
1 |
4–65 |
2.83 × 10−4 | |||||
– |
k25 = 1.61 × 10−5 |
4.32 × 10−4 | |||||||
– |
k4 = 0.355 × 10−5 |
19.5 × 10−4 | |||||||
0.10% TBHQ |
– |
k65 = 13.4 × 10−5 |
0.519 × 10−4 | ||||||
– |
k45 = 2.33 × 10−5 |
1 |
4–65 |
2.97 × 10−4 | |||||
– |
k25 = 1.21 × 10−5 |
5.74 × 10−4 | |||||||
– |
k4 = 0.257 × 10−5 |
27.0 × 10−4 | |||||||
Vitamin A | |||||||||
Enteral feeding formula (5.5% protein, 3.6% lipid, 11.4% CHO) |
Frias and Vidal-Valverde (2001) |
||||||||
Reconstitution; presterilization (UHT: 136°C/3–4 s); homogenize; add vitamins; pack in glass; sterilize (118°C/9 min); store 4–30°C/0–9 mo. |
|||||||||
All-trans-retinol |
0.780 |
k30 = 5.628 × 10−6 |
1.23 × 105 | ||||||
0.840 |
k20 = 5.859 × 10−6 |
1.06 |
1 |
0.708 |
4–30 |
1.18 × 105 | |||
0.829 |
k4 = 4.849 × 10−6 |
1.43 × 105 | |||||||
13-cis-retinol |
0.945 |
k30 = 3.853 × 10−6 |
1.80 × 105 | ||||||
0.881 |
k20 = 2.766 × 10−6 |
2.47 |
1 |
0.784 |
4–30 |
2.51 × 105 | |||
0.809 |
k4 = 2.538 × 10−6 |
2.73 × 105 | |||||||
Vitamin A activity |
0.831 |
k30 = 11.21 × 10−6 |
0.619 × 105 |
Frias and Vidal-Valverde (2001) |
|||||
0.844 |
k20 = 5.581 × 10−6 |
5.19 |
1 |
0.783 |
4–30 |
1.24 × 105 |
|||
0.830 |
k4 = 4.664 × 10−6 |
1.49 × 105 | |||||||
Milk/infant (stored 12 months) |
Albalá-Hurtado et al. (2000) |
||||||||
Liquid: 115°C/15 min sealed in brown glass jars |
k37 = 7.87 × 10−7 |
– |
1 |
– |
37 |
8.81 × 105 |
|||
Powdered: 40% conc./60°C; 70–72°C/15 sec; spray dry 80°C; agglom. |
k37 = 9.44 × 10−7 |
– |
1 |
– |
37 |
7.34 × 105 |
|||
Vitamin A |
Galdi et al. (1989) |
||||||||
Milk |
Flexible plastic containers, no headspace | ||||||||
infant formula [15% protein, (milk-based); 24% lipids; 57% carbohydrates; 4% vitamins, minerals, water] | |||||||||
With ferrous sulfate |
0.978 |
k45 = 2.92 × 10−6 |
2.37 × 105 | ||||||
0.993 |
k37 = 2.36 × 10−6 |
7.6 |
1 |
0.991 |
20–45 |
2.94 × 105 | |||
0.935 |
k20 = 1.07 × 10−6 |
6.48 × 105 | |||||||
With ferric glycinate |
0.991 |
k45 = 2.39 × 10−6 |
2.90 × 105 | ||||||
0.970 |
k37 = 1.18 × 10−6 |
8.5 |
1 |
0.909 |
20–45 |
5.87 × 105 | |||
0.929 |
k20 = 0.694 × 10−6 |
9.99 × 105 | |||||||
Butternut squash |
Carotene |
– |
ak80 = 0.0011 |
11.8 |
630 |
Stefanovich and Karel (1982) |
|||
– |
k70 = 0.0007 |
(13.5)a |
1 |
0.998 |
60–80 |
990 |
|||
– |
k60 = 0.0004 |
1,733 | |||||||
Yellow corn |
Carotene |
– |
k80 = 0.00135 |
20.5 |
513 | ||||
– |
k70 = 0.00023 |
(4.8)a |
1 |
0.735 |
60–80 |
3,014 | |||
– |
k60 = 0.00023 |
3,014 | |||||||
Model system |
Avicel-PH102/ |
– |
k80 = 0.0239 |
21.8 |
29 | ||||
β-carotene |
– |
k70 = 0.0119 |
(21.7)a |
pseudo-1 |
0.984 |
60–80 |
58 | ||
– |
k60 = 0.0037 |
187 | |||||||
Sweet potato |
– |
k80 = 0.00116 |
10.5 |
598 | |||||
– |
k70 = 0.00061 |
(10.6)a |
1 |
0.936 |
60–80 |
1,136 | |||
– |
k60 = 0.00047 |
1,475 | |||||||
Sweet potato |
Freeze-dried/ground/rehumidified |
Haralampu and Karel (1983) |
|||||||
β-carotene: test 1 |
g H2O/g solids | ||||||||
aw = 0.020 |
0.008 |
0.978 |
k40 = 1.01 × 10−4 |
– |
pseudo-1 |
– |
40 |
6.88 × 103 | |
aw = 0.058 |
0.026 |
0.999 |
k40 = 0.638 × 10−4 |
– |
pseudo-1 |
– |
40 |
10.86 × 103 | |
aw = 0.112 |
0.034 |
0.993 |
k40 = 0.570 × 10−4 |
– |
pseudo-1 |
– |
40 |
12.16 × 103 | |
aw = 0.316 |
0.068 |
0.993 |
k40 = 0.423 × 10−4 |
– |
pseudo-1 |
– |
40 |
16.39 × 103 | |
aw = 0.484 |
0.085 |
0.992 |
k40 = 0.382 × 10−4 |
– |
pseudo-1 |
– |
40 |
18.15 × 103 | |
aw = 0.555 |
0.101 |
0.996 |
k40 = 0.313 × 10−4 |
– |
pseudo-1 |
– |
40 |
22.15 × 103 | |
aw = 0.661 |
0.116 |
0.981 |
k40 = 0.347 × 10−4 |
– |
pseudo-1 |
– |
40 |
19.98 × 103 | |
aw = 0.747 |
0.204 |
0.995 |
k40 = 0.320 × 10−4 |
– |
pseudo-1 |
– |
40 |
21.66 × 103 | |
β-carotene: test 2 |
g H2O/g solids | ||||||||
aw = 0.020 |
0.030 |
0.994 |
k40 = 2.15 × 10−4 |
– |
pseudo-1 |
– |
40 |
3.22 × 103 | |
aw = 0.058 |
0.058 |
0.996 |
k40 = 1.16 × 10−4 |
– |
pseudo-1 |
– |
40 |
5.98 × 103 | |
aw = 0.112 |
0.064 |
0.998 |
k40 = 0.789 × 10−4 |
– |
pseudo-1 |
– |
40 |
8.79 × 103 | |
aw = 0.316 |
0.094 |
0.997 |
k40 = 0.653 × 10−4 |
– |
pseudo-1 |
– |
40 |
10.61 × 103 | |
aw = 0.484 |
0.110 |
0.994 |
k40 = 0.577 × 10−4 |
– |
pseudo-1 |
– |
40 |
12.01 × 103 | |
aw = 0.555 |
0.133 |
0.972 |
k40 = 0.417 × 10−4 |
– |
pseudo-1 |
– |
40 |
16.62 × 103 | |
aw = 0.661 |
0.147 |
0.999 |
k40 = 0.368 × 10−4 |
– |
pseudo-1 |
– |
40 |
18.84 × 103 | |
aw = 0.747 |
0.190 |
0.995 |
k40 = 0.423 × 10−4 |
– |
pseudo-1 |
– |
40 |
16.39 × 103 | |
Vitamin A | |||||||||
Tomato paste |
Lavelli and Giovanelli (2003) |
||||||||
(reported as reduction in total antioxidant activity – β-carotene and lycopene) |
Storage 0–90 days |
0.98 |
k50 = 7.43 × 10−6 |
1.35 × 105 |
|||||
0.91 |
k40 = 5.07 × 10−6 |
4.97 |
1 |
0.917 |
30–50 |
1.37 × 105 | |||
0.89 |
k30 = 4.44 × 10−6 |
(4.83)a |
1.56 × 105 | ||||||
Tomato pulp |
0.96 |
k50 = 5.28 × 10−6 |
1.31 × 105 | ||||||
0.89 |
k40 = 3.13 × 10−6 |
5.49 |
1 |
0.795 |
30–50 |
2.22 × 105 | |||
0.94 |
k30 = 2.99 × 10−6 |
(5.31)a |
2.32 × 105 | ||||||
Tomato pulp/w/XS heat |
(additional 98°C/50 min) |
0.97 |
k40 = 3.33 × 10−6 |
– |
1 |
– |
40 |
2.08 × 105 | |
Tomato puree |
0.980 |
k40 = 2.71 × 10−6 |
– |
1 |
– |
40 |
2.56 × 105 | ||
Carotenoids | |||||||||
Tomato (Lycopersicum esculentum) |
Demiray et al. (2013) |
||||||||
β-Carotene |
Process: | ||||||||
Tomatoes quartered |
– |
k100 = 6.35 × 10−3 |
109.2 | ||||||
50 kg/batch |
– |
k90 = 5.15 × 10−3 |
134.7 | ||||||
Tray drier |
– |
k80 = 4.78 × 10−3 |
9.6 |
1 |
0.922 |
60–100 |
144.9 | ||
A445 |
Final MC ~15 g/100 g |
– |
k70 = 2.26 × 10−3 |
307.4 | |||||
Airflow: 0.2 m/s |
– |
k60 = 1.40 × 10−3 |
495.7 | ||||||
~2% humidity | |||||||||
Lycopene |
Organic solvent extraction |
– |
k100 = 7.47 × 10−3 |
92.9 |
Demiray et al. (2013) |
||||
A470 |
– |
k90 = 6.29 × 10−3 |
110.1 | ||||||
Analysis: UV-VIS |
– |
k80 = 5.44 × 10−3 |
11.2 |
1 |
0.921 |
60–100 |
127.5 | ||
– |
k70 = 2.30 × 10−3 |
301.4 | |||||||
– |
k60 = 1.30 × 10−3 |
533.2 | |||||||
Ascorbic acid | |||||||||
– |
k100 = 7.87 × 10−3 |
88.1 | |||||||
A254 |
– |
k90 = 6.87 × 10−3 |
100.9 | ||||||
– |
k80 = 5.01 × 10−3 |
11.2 |
1 |
0.933 |
60–100 |
138.4 | |||
– |
k70 = 2.92 × 10−3 |
237.7 | |||||||
– |
k60 = 1.27 × 10−3 |
547.9 | |||||||
Vitamin D | |||||||||
Vitamin D2 (ergocalciferol) |
Li and Min (1998) |
||||||||
Model system (12% water/88% acetone) |
Air-tight serum bottles/w/light | ||||||||
Phase 1: | |||||||||
Initial concentration: |
0 ppm B2 |
0.99 |
k25 = 1.12 × 10−4 |
– |
1 |
– |
25–60 |
6.21 × 103 | |
1000 ppm D2 |
0.91 |
k60 = 3.24 × 10−4 |
– |
1 |
– |
25–60 |
2.14 × 103 | ||
15 ppm B2 |
0.90 |
k25 = 5.48 × 10−4 |
– |
1 |
– |
25–60 |
1.27 × 103 | ||
0.94 |
k60 = 6.96 × 10−4 |
– |
1 |
– |
25–60 |
0.996 × 103 | |||
Phase 2: | |||||||||
0 ppm B2 |
0.86 |
k25 = 0.217 × 10−4 |
– |
1 |
– |
25–60 |
31.9 × 103 | ||
0.96 |
k60 = 0.200 × 10−4 |
– |
1 |
– |
25–60 |
34.7 × 103 | |||
15 ppm B2 |
0.87 |
k25 = 0.583 × 10−4 |
– |
1 |
– |
25–60 |
11.9 × 103 | ||
0.83 |
k60 = 0.250 × 10−4 |
– |
1 |
– |
25–60 |
27.7 × 103 | |||
Vitamins D, A, B2 | |||||||||
Skim milk |
Vitamin D3 | ||||||||
20 g powdered skim/100 ml water |
Control |
– |
k21 = 11.8 × 10−4 |
16.0 |
1 |
– |
8–21 |
586 |
Montenegro et al. (2007) |
– |
k8 = 3.33 × 10−4 |
2079 |
|||||||
MIC: (Spray dried Lycopene/Gum Arabic) |
w/MIC (6 g/L) |
– |
k8 = 1.83 × 10−4 |
3781 | |||||
Vitamin A | |||||||||
Control |
– |
k21 = 5.33 × 10−3 |
4.0 |
1 |
– |
8–21 |
130 | ||
(230 μg lycopene/100 g) |
– |
k8 = 4.00 × 10−3 |
173 | ||||||
w/MIC (6 g/L) |
– |
k8 = 2.17 × 10−3 |
320 | ||||||
Vitamins D, A, B2 |
Montenegro et al. (2007) |
||||||||
Skim milk cont. - | |||||||||
Assays: HPLC |
Riboflavin (Rf)* | ||||||||
*Rf: triplet excited state B2 |
Control |
– |
k21 = 9.00 × 10−1 |
0.77 | |||||
w/MIC (6 g/L) |
– |
k21 = 4.17 × 10−1 |
1.66 | ||||||
Vitamins D, A, B2 | |||||||||
UHT Milk (fortified) |
Vitamin D3 |
Saffert et al. (2009) |
|||||||
1.5% fat | |||||||||
15% RDA Vit. A, D3 |
PET Clear |
0.997 |
k23 = 8.63 × 10−6 |
– |
1 |
– |
23 |
0.803 × 10−5 | |
Preheat 65°C/10–15 m |
PET low white |
0.983 |
k23 = 8.93 × 10−6 |
– |
1 |
– |
23 |
0.776 × 10−5 | |
Heat: 140°C/4 s |
PET high white |
0.933 |
k23 = 3.27 × 10−6 |
– |
1 |
– |
23 |
2.12 × 10−5 | |
PET white & yellow |
0.925 |
k23 = 3.48 × 10−6 |
– |
1 |
– |
23 |
1.99 × 10−5 | ||
Control |
0.513 |
k23 = 0.280 × 10−6 |
– |
1 |
– |
23 |
24.7 × 10−5 | ||
Vitamin A | |||||||||
Test Samples: |
PET Clear |
0.980 |
k23 = 20.6 × 10−6 |
– |
1 |
– |
23 |
3.36 × 10−4 | |
Storage: 23°C |
PET low white |
0.976 |
k23 = 1.92 × 10−6 |
– |
1 |
– |
23 |
3.61 × 10−4 | |
Light: 700 lux |
PET high white |
0.974 |
k23 = 1.22 × 10−6 |
– |
1 |
– |
23 |
5.67 × 10−4 | |
12 wks |
PET white & yellow |
0.946 |
k23 = 0.977 × 10−6 |
– |
1 |
– |
23 |
7.09 × 10−4 | |
Control |
0.946 |
k23 = 0.139 × 10−6 |
– |
1 |
– |
23 |
49.7 × 10−4 | ||
Controls: |
Vitamin B2 | ||||||||
Storage: 23°C |
PET Clear |
0.998 |
k23 = 43.5 × 10−6 |
– |
1 |
– |
23 |
1.59 × 10−4 | |
Dark |
PET low white |
0.994 |
k23 = 18.5 × 10−6 |
– |
1 |
– |
23 |
3.76 × 10−4 | |
PET high white |
0.974 |
k23 = 11.2 × 10−6 |
– |
1 |
– |
23 |
6.21 × 10−4 | ||
PET white & yellow |
0.998 |
k23 = 7.38 × 10−6 |
– |
1 |
– |
23 |
9.38 × 10−4 | ||
Control |
0.559 |
k23 = 1.070 × 10−6 |
– |
1 |
– |
23 |
64.7 × 10−4 | ||
Vitamin E | |||||||||
Enteral feeding formula (5.5% protein, 3.6% lipid, 11.4% CHO) |
Frias and Vidal-Valverde (2001) |
||||||||
Reconstitution; presterilization (UHT: 136°C/3–4 s); homogenize; add vitamins; pack in glass; sterilize (118°C/9 min); store 4–30°C/0–9 mo. |
|||||||||
α-Tocopherol |
0.874 |
k30 = 1.835 × 10−6 |
3.78 × 105 | ||||||
0.608 |
k20 = 1.598 × 10−6 |
2.46 |
1 |
0.999 |
4–30 |
4.34 × 105 | |||
0.611 |
k4 = 1.250 × 10−6 |
5.55 × 105 | |||||||
γ-Tocopherol |
0.874 |
k30 = 2.300 × 10−6 |
3.01 × 105 |
Frias and Vidal-Valverde (2001) |
|||||
0.608 |
k20 = 1.799 × 10−6 |
4.11 |
1 |
0.999 |
4–30 |
3.85 × 105 |
|||
0.611 |
k4 = 1.210 × 10−6 |
5.73 × 105 | |||||||
δ-Tocopherol |
0.874 |
k30 = 1.943 × 10−6 |
3.57 × 105 | ||||||
0.608 |
k20 = 1.572 × 10−6 |
2.82 |
1 |
0.985 |
4–30 |
4.41 × 105 | |||
0.611 |
k4 = 1.242 × 10−6 |
5.58 × 105 | |||||||
Vitamin E | |||||||||
Vitamin E activity |
0.939 |
k30 = 1.844 × 10−6 |
3.76 × 105 |
Frias and Vidal-Valverde (2001) |
|||||
0.936 |
k20 = 1.603 × 10−6 |
2.50 |
1 |
0.999 |
4–30 |
4.32 × 105 |
|||
0.915 |
k4 = 1.249 × 10−6 |
5.55 × 105 | |||||||
Enteral feeding formula (3.7% protein, 3.9% lipid, 12.5% CHO) | |||||||||
α-Tocopherol |
0.952 |
k30 = 2.126 × 10−6 |
3.26 × 105 | ||||||
0.946 |
k20 = 1.774 × 10−6 |
2.51 |
1 |
0.989 |
4–30 |
3.91 × 105 | |||
0.938 |
k4 = 1.427 × 10−6 |
4.86 × 105 | |||||||
γ-Tocopherol |
0.873 |
k30 = 2.471 × 10−6 |
2.81 × 105 | ||||||
0.775 |
k20 = 1.879 × 10−6 |
3.21 |
1 |
0.964 |
4–30 |
3.69 × 105 | |||
0.772 |
k4 = 1.474 × 10−6 |
4.70 × 105 | |||||||
δ-Tocopherol |
0.920 |
k30 = 2.473 × 10−6 |
2.80 × 105 | ||||||
0.885 |
k20 = 2.057 × 10−6 |
2.68 |
1 |
0.993 |
4–30 |
3.37 × 105 | |||
0.891 |
k4 = 1.620 × 10−6 |
4.28 × 105 | |||||||
Vitamin E activity |
0.952 |
k30 = 2.134 × 10−6 |
3.25 × 105 | ||||||
0.944 |
k20 = 1.777 × 10−6 |
2.54 |
1 |
0.989 |
4–30 |
3.90 × 105 | |||
0.936 |
k4 = 1.428 × 10−6 |
4.85 × 105 | |||||||
Vitamin E | |||||||||
Frying oil |
Mba et al. (2017) |
||||||||
Virgin palm oil |
Deep-fat frying: |
0.98 |
k190 = 7.09 × 10−4 |
978 | |||||
α-Tocopherol |
0.99 |
k180 = 5.81 × 10−4 |
10.5 |
1.6 |
0.999 |
← p-R2* |
1192a | ||
Potatoes peeled, sliced, washed, lightly dried |
0.99 |
k170 = 3.95 × 10−4 |
11.9 |
1 |
0.971 |
170–190 |
1756 | ||
0.99 |
k190 = 8.02 × 10−4 |
865 | |||||||
ϒ-Tocopherol |
0.98 |
k180 = 7.52 × 10−4 |
3.1 |
1.4 |
0.999 |
922a | |||
0.98 |
k170 = 6.73 × 10−4 |
3.6 |
1 |
0.981 |
170–190 |
1030 | |||
Preheat oil 2 hr before frying |
0.93 |
k190 = 2.65 × 10−4 |
2614 | ||||||
δ-Tocopherol |
0.99 |
k180 = 2.44 × 10−4 |
11.0 |
1.5 |
0.999 |
2845a | |||
0.98 |
k170 = 1.35 × 10−4 |
13.8 |
1 |
0.852 |
170–190 |
5134 | |||
30 min intervals: |
0.99 |
k190 = 2.83 × 10−4 |
2448 | ||||||
α-Tocotrienol |
100 g sliced potatoes fried 10 min in 4.5 L hot oil |
0.98 |
k180 = 1.90 × 10−4 |
12.4 |
1.8 |
0.999 |
3644a | ||
0.96 |
k170 = 1.16 × 10−4 |
18.1 |
1 |
0.998 |
170–190 |
5955 | |||
0.99 |
k190 = 7.75 × 10−4 |
894 | |||||||
ϒ-Tocotrienol |
0.99 |
k180 = 6.64 × 10−4 |
4.8 |
1.5 |
0.999 |
1045a | |||
0.99 |
k170 = 6.19 × 10−4 |
4.6 |
1 |
0.949 |
170–190 |
1121 | |||
Aliquots of oil were removed each time interval/stored frozen until analysis |
0.98 |
k190 = 0.834 × 10−4 |
8311 | ||||||
δ-Tocotrienol |
0.99 |
k180 = 0.828 × 10−4 |
24.6 |
1.3 |
0.987 |
8371a | |||
0.99 |
k170 = 0.816 × 10−4 |
0.4 |
1 |
0.968 |
170–190 |
8494 | |||
0.98 |
k190 = 0.696 × 10−4 |
9959 | |||||||
Total carotenoids |
Total heating and fry time = 20 hr |
0.99 |
k180 = 0.564 × 10−4 |
17.0 |
1.5 |
0.999 |
12290a | ||
0.99 |
k170 = 0.426 × 10−4 |
10.0 |
1 |
0.995 |
170–190 |
16271 | |||
Refined canola oil (w/BHA, BHT, DMPS) |
0.98 |
k190 = 5.70 × 10−4 |
1216 | ||||||
α-Tocopherol |
0.99 |
k180 = 4.43 × 10−4 |
10.5 |
1.6 |
0.999 |
1563a | |||
0.99 |
k170 = 3.46 × 10−4 |
10.2 |
1 |
0.999 |
170–190 |
2006 | |||
0.96 |
k190 = 7.80 × 10−4 |
889 | |||||||
ϒ-Tocopherol |
Tocopherol analysis: Normal Phase HPLC |
0.98 |
k180 = 7.28 × 10−4 |
3.6 |
1.4 |
0.996 |
952a | ||
0.99 |
k170 = 6.73 × 10−4 |
3.0 |
1 |
0.999 |
170–190 |
1030 | |||
Frying oil |
0.98 |
k190 = 0.804 × 10−4 |
8621 |
Mba et al. (2017) |
|||||
Total carotenoids |
Carotenoid analysis: UV-VIS/A445 |
0.99 |
k180 = 0.756 × 10−4 |
0.4 |
1.5 |
0.999 |
9169a | ||
0.99 |
k170 = 0.708 × 10−4 |
2.6 |
1 |
0.999 |
170–190 |
9790 | |||
Palm oil: canola oil blend |
0.99 |
k190 = 5.03 × 10−4 |
1377 | ||||||
α-Tocopherol |
0.99 |
k180 = 4.03 × 10−4 |
11.5 |
1.6 |
0.993 |
1719a | |||
0.99 |
k170 = 3.26 × 10−4 |
8.8 |
1 |
0.999 |
170–190 |
2124 | |||
0.99 |
k190 = 5.85 × 10−4 |
1185 | |||||||
ϒ-Tocopherol |
0.99 |
k180 = 4.95 × 10−4 |
4.8 |
1.6 |
0.998 |
1400a | |||
0.99 |
k170 = 4.05 × 10−4 |
7.5 |
1 |
0.998 |
170–190 |
1711 | |||
δ-Tocopherol |
0.97 |
k170 = 1.15 × 10−4 |
– |
– |
– |
170 |
6017 | ||
0.99 |
k190 = 2.20 × 10−4 |
3148 | |||||||
α-Tocotrienol |
0.95 |
k180 = 1.30 × 10−4 |
17.7 |
1.8 |
0.995 |
5324a | |||
0.96 |
k170 = 0.600 × 10−4 |
26.5 |
1 |
0.991 |
170–190 |
11552 | |||
0.99 |
k190 = 5.65 × 10−4 |
1226 | |||||||
ϒ-Tocotrienol |
0.98 |
k180 = 4.55 × 10−4 |
11.2 |
1.6 |
0.999 |
1524a | |||
0.99 |
k170 = 3.95 × 10−4 |
7.3 |
1 |
0.982 |
170–190 |
1756 | |||
0.99 |
k190 = 0.738 × 10−4 |
9392 | |||||||
Total Carotenoids |
0.99 |
k180 = 0.624 × 10−4 |
15.5 |
1.5 |
0.999 |
11108a | |||
* p-R2 = pseudo coefficient of determination |
0.99 |
k170 = 0.528 × 10−4 |
6.8 |
1 |
0.999 |
170–190 |
13128 | ||
Vitamin E | |||||||||
Milk |
Galdi et al. (1989) |
||||||||
Infant formula |
Flexible plastic containers, no headspace |
0.988 |
k45 = 6.25 × 10−6 |
1.11 × 105 | |||||
0.900 |
k37 = 2.59 × 10−6 |
9.4 |
1 |
0.998 |
20–45 |
2.68 × 105 | |||
[15% protein (milk-based); 24% lipids; 57% carbohydrates; 4% vitamin, minerals, water] |
With ferrous sulfate |
0.861 |
k20 = 1.78 × 10−6 |
3.89 × 105 | |||||
0.958 |
k45 = 3.82 × 10−6 |
1.81 × 105 | |||||||
With ferric glycinate |
0.932 |
k37 = 2.50 × 10−6 |
9.6 |
1 |
0.999 |
20–45 |
2.77 × 105 | ||
0.926 |
k20 = 1.04 × 10−6 |
6.66 × 105 | |||||||
Vitamin E | |||||||||
Freeze-dried/rehumidified |
Widicus et al. (1980) |
||||||||
Model system: | |||||||||
α -Tocopherol |
Packaging: 303 × 406 cans (XS headspace) | ||||||||
(48% starch, 34% corn syrup solids, 10.2% soy isolate, 5.1% sucrose, 2.0% NaCl) |
aw = 0.10 |
– |
k37 = 0.557 × 10−5 |
1.24 × 105 | |||||
– |
k30 = 0.345 × 10−5 |
9.5 |
1 |
0.977 |
20–37 |
2.01 × 105 | |||
– |
k20 = 0.225 × 10−5 |
3.08 × 105 | |||||||
aw = 0.24 |
– |
k37 = 0.892 × 10−5 |
0.777 × 105 | ||||||
– |
k30 = 0.432 × 10−5 |
10.8 |
1 |
0.894 |
20–37 |
1.60 × 105 | |||
– |
k20 = 0.310 × 10−5 |
2.24 × 105 | |||||||
aw = 0.40 |
– |
k37 = 1.031 × 10−5 |
0.672 × 105 | ||||||
– |
k30 = 0.436 × 10−5 |
10.4 |
1 |
0.788 |
20–37 |
1.59 × 105 | |||
– |
k20 = 0.363 × 10−5 |
1.91 × 105 | |||||||
aw = 0.65 |
– |
k37 = 1.107 × 10−5 |
0.626 × 105 |
Widicus et al. (1980) |
|||||
– |
k30 = 0.494 × 10−5 |
11.4 |
1 |
0.871 |
20–37 |
1.40 × 105 | |||
– |
k20 = 0.360 × 10−5 |
1.93 × 105 | |||||||
Packaging: |
208 × 006 TDT (no headspace) | ||||||||
aw = 0.10 |
– |
k37 = 0.599 × 10−5 |
1.16 × 105 | ||||||
– |
k30 = 0.326 × 10−5 |
10.1 |
1 |
0.936 |
20–37 |
2.12 × 105 | |||
– |
k20 = 0.224 × 10−5 |
3.09 × 105 | |||||||
aw = 0.24 |
– |
k37 = 0.790 × 10−5 |
0.877 × 105 | ||||||
– |
k30 = 0.410 × 10−5 |
13.1 |
1 |
0.978 |
20–37 |
1.69 × 105 | |||
– |
k20 = 0.226 × 10−5 |
3.07 × 105 | |||||||
aw = 0.40 |
– |
k37 = 0.913 × 10−5 |
0.795 × 105 | ||||||
– |
k30 = 0.419 × 10−5 |
10.8 |
1 |
0.861 |
20–37 |
1.65 × 105 | |||
– |
k20 = 0.315 × 10−5 |
2.20 × 105 | |||||||
aw = 0.65 |
– |
k37 = 0.931 × 10−5 |
0.745 × 105 | ||||||
– |
k30 = 0.451 × 10−5 |
8.8 |
1 |
0.791 |
20–37 |
1.54 × 105 | |||
– |
k20 = 0.385 × 10−5 |
1.80 × 105 | |||||||
Vitamin E | |||||||||
Seaweed (Ascophyllum nodosum) |
Jenson (1969) |
||||||||
α -Tocopherol |
Air-dried/ground | ||||||||
Moisture content: |
10% |
0.954 |
k25 = 0.441 × 10−5 |
1.57 × 105 | |||||
0.883 |
k15 = 0.296 × 10−5 |
10.1 |
1 |
0.880 |
4–25 |
2.34 × 105 | |||
0.881 |
k10 = 0.256 × 10−5 |
2.71 × 105 | |||||||
0.987 |
k4 = 0.111 × 10−5 |
6.24 × 105 | |||||||
15% |
0.923 |
k25 = 0.538 × 10−5 |
1.29 × 105 | ||||||
0.980 |
k15 = 0.354 × 10−5 |
12.5 |
1 |
0.893 |
4–25 |
1.96 × 105 | |||
0.926 |
k10 = 0.261 × 10−5 |
2.66 × 105 | |||||||
0.965 |
k4 = 0.0999 × 10−5 |
6.94 × 105 | |||||||
25% |
0.983 |
k25 = 0.833 × 10−5 |
0.832 × 105 | ||||||
a Values reported by authors. |
0.902 |
k15 = 0.561 × 10−5 |
6.3 |
1 |
0.998 |
4–25 |
1.24 × 105 | ||
0.885 |
k10 = 0.464 × 10−5 |
1.49 × 105 | |||||||
0.902 |
k4 = 0.373 × 10−5 |
1.86 × 105 | |||||||
Multiple Vitamins | |||||||||
Fish feed | |||||||||
Extrusion: |
With Crystalline vitamin |
Marchetti et al. 1999 |
|||||||
Wenger X/185 |
Ascorbic acid |
0.970 |
kRT = 6.30 × 10−6 |
– |
1 |
– |
RT |
1.10 × 10−5 | |
Moisture: 16% |
Biotin |
0.880 |
kRT = 0.316 × 10−6 |
– |
1 |
– |
RT |
22.0 × 10−5 | |
Outlet Temp = 96°C |
Cyanocobalamin |
0.994 |
kRT = 1.73 × 10−6 |
– |
1 |
– |
RT |
4.01 × 10−5 | |
Dry: 95°C/20 min |
Folic acid |
0.817 |
kRT = 1.44 × 10−6 |
– |
1 |
– |
RT |
4.81 × 10−5 | |
Menadione |
0.998 |
kRT = 3.47 × 10−6 |
– |
1 |
– |
RT |
1.20 × 10−5 | ||
Nicotinamide |
0.945 |
kRT = 0.110 × 10−6 |
– |
1 |
– |
RT |
63.0 × 10−5 | ||
Storage: RT/ |
Pantothenic acid |
0.886 |
kRT = 1.13 × 10−6 |
– |
1 |
– |
RT |
6.14 × 10−5 | |
Paper bags |
Pyridoxine |
0.999 |
kRT = 1.86 × 10−6 |
– |
1 |
– |
RT |
3.73 × 10−5 | |
Riboflavin |
0.979 |
kRT = 0.715 × 10−6 |
– |
1 |
– |
RT |
9.70 × 10−5 | ||
Thiamin |
0.937 |
kRT = 0.955 × 10−6 |
– |
1 |
– |
RT |
7.26 × 10−5 | ||
Extrusion: |
With Fat coated vitamin |
Marchetti et al. (1999) |
|||||||
Assay: NR |
Ascorbic acid |
0.964 |
kRT = 0.871 × 10−6 |
– |
1 |
– |
RT |
7.96 × 10−5 |
|
Assay: mo |
Biotin |
0.719 |
kRT = 0.276 × 10−6 |
– |
1 |
– |
RT |
25.1 × 10−5 | |
Assay: mo |
Cyanocobalamin |
0.956 |
kRT = 1.11 × 10−6 |
– |
1 |
– |
RT |
6.23 × 10−5 | |
Assay: mo |
Folic acid |
0.928 |
kRT = 0.523 × 10−6 |
– |
1 |
– |
RT |
13.3 × 10−5 | |
Assay: HPLC |
Menadione |
0.966 |
kRT = 1.03 × 10−6 |
– |
1 |
– |
RT |
6.76 × 10−5 | |
Assay: mo |
Nicotinamide |
0.859 |
kRT = 0.0993 × 10−6 |
– |
1 |
– |
RT |
69.8 × 10−5 | |
Assay: mo |
Pantothenic acid |
0.883 |
kRT = 0.266 × 10−6 |
– |
1 |
– |
RT |
26.1 × 10−5 | |
Assay: mo |
Pyridoxine |
0.997 |
kRT = 0.307 × 10−6 |
– |
1 |
– |
RT |
22.6 × 10−5 | |
Assay: fluorometric |
Riboflavin |
0.991 |
kRT = 0.416 × 10−6 |
– |
1 |
– |
RT |
16.7 × 10−5 | |
Assay: fluorometric |
Thiamine |
0.913 |
kRT = 0.266 × 10−6 |
– |
1 |
– |
RT |
26.0 × 10−5 | |
Pelleting: |
With Crystalline vitamin | ||||||||
Moisture: 5% |
Ascorbic acid |
0.997 |
kRT = 5.79 × 10−6 |
– |
1 |
– |
RT |
1.20 × 10−5 | |
CPM 7000 |
Biotin |
0.986 |
kRT = 0.448 × 10−6 |
– |
1 |
– |
RT |
15.5 × 10−5 | |
Outlet Temp = 85C |
Cyanocobalamin |
0.960 |
kRT = 1.05 × 10−6 |
– |
1 |
– |
RT |
6.59 × 10−5 | |
Folic acid |
0.990 |
kRT = 0.720 × 10−6 |
– |
1 |
– |
RT |
9.63 × 10−5 | ||
Storage: RT/ |
Menadione |
0.993 |
kRT = 3.29 × 10−6 |
– |
1 |
– |
RT |
2.11 × 10−5 | |
Paper bags |
Nicotinamide |
0.994 |
kRT = 0.306 × 10−6 |
– |
1 |
– |
RT |
22.7 × 10−5 | |
Pantothenic acid |
0.999 |
kRT = 1.20 × 10−6 |
– |
1 |
– |
RT |
5.76 × 10−5 | ||
Pyridoxine |
0.971 |
kRT = 1.34 × 10−6 |
– |
1 |
– |
RT |
5.17 × 10−5 | ||
Riboflavin |
0.966 |
kRT = 0.423 × 10−6 |
– |
1 |
– |
RT |
16.4 × 10−5 | ||
Thiamine |
0.993 |
kRT = 0.471 × 10−6 |
– |
1 |
– |
RT |
14.7 × 10−5 | ||
Pelleting: |
With Fat coated vitamin | ||||||||
Assay: NR |
Ascorbic acid |
0.960 |
kRT = 1.09 × 10−6 |
– |
1 |
– |
RT |
6.35 × 10−5 | |
Assay: mo |
Biotin |
0.976 |
kRT = 0.289 × 10−6 |
– |
1 |
– |
RT |
24.0 × 10−5 | |
Assay: mo |
Cyanocobalamin |
0.924 |
kRT = 0.727 × 10−6 |
– |
1 |
– |
RT |
9.54 × 10−5 | |
Assay: mo |
Folic acid |
0.973 |
kRT = 0.253 × 10−6 |
– |
1 |
– |
RT |
29.5 × 10−5 | |
Assay: HPLC |
Menadione |
0.961 |
kRT = 0.814 × 10−6 |
– |
1 |
– |
RT |
8.52 × 10−5 | |
Assay: mo |
Nicotinamide |
0.961 |
kRT = 0.186 × 10−6 |
– |
1 |
– |
RT |
37.3 × 10−5 | |
Assay: mo |
Pantothenic acid |
0.969 |
kRT = 0.439 × 10−6 |
– |
1 |
– |
RT |
15.8 × 10−5 | |
Pelleting: |
Marchetti et al. (1999) |
||||||||
Assay: mo |
Pyridoxine |
0.948 |
kRT = 0.478 × 10−6 |
– |
1 |
– |
RT |
14.5 × 10−5 |
|
Assay: fluorometric |
Riboflavin |
0.967 |
kRT = 0.211 × 10−6 |
– |
1 |
– |
RT |
32.8 × 10−5 | |
Assay: fluorometric |
Thiamine |
0.980 |
kRT = 0.235 × 10−6 |
– |
1 |
– |
RT |
29.5 × 10−5 | |
Miscellaneous bioactive compounds | |||||||||
Ascorbic acid |
Nambi et al. (2016) |
||||||||
Beetroot |
Blanching (0–15 min) |
– |
k90 = 4.44 × 10−2 |
15.61 | |||||
(5 mm3) |
6 time interval sampling |
– |
k85 = 2.80 × 10−2 |
24.72 | |||||
– |
k80 = 1.94 × 10−2 |
14.7 |
1 |
0.950 |
70–90 |
35.75 | |||
– |
k75 = 1.82 × 10−2 |
38.00 | |||||||
– |
k70 = 1.24 × 10−2 |
55.95 | |||||||
Ascorbic acid |
Assay: Indophenol |
– |
k90 = 11.3 × 10−2 |
6.11 | |||||
Green peas |
– |
k85 = 8.01 × 10−2 |
8.65 | ||||||
(~7 +/− 0.5 mm dia) |
– |
k80 = 6.96 × 10−2 |
9.3 |
1 |
0.851 |
70–90 |
9.96 | ||
– |
k75 = 4.98 × 10−2 |
13.92 | |||||||
– |
k70 = 5.56 × 10−2 |
12.46 | |||||||
Ascorbic acid |
– |
k90 = 14.5 × 10−2 |
4.78 | ||||||
Egg plant |
– |
k85 = 9.37 × 10−2 |
7.40 | ||||||
(5 mm3) |
– |
k80 = 7.72 × 10−2 |
11.0 |
1 |
0.930 |
70–90 |
8.98 | ||
– |
k75 = 6.54 × 10−2 |
10.59 | |||||||
– |
k70 = 5.69 × 10−2 |
12.18 | |||||||
Ascorbic acid |
– |
k90 = 4.70 × 10−2 |
14.74 | ||||||
Green pepper |
– |
k85 = 3.22 × 10−2 |
21.51 | ||||||
(5 × 5 × 3 mm) |
– |
k80 = 2.36 × 10−2 |
16.3 |
1 |
0.994 |
70–90 |
29.37 | ||
– |
k75 = 1.77 × 10−2 |
39.09 | |||||||
– |
k70 = 1.26 × 10−2 |
55.14 | |||||||
Phenolics |
Nambi et al. (2016) |
||||||||
Beetroot |
Blanching (0–15 min) |
– |
k90 = 13.6 × 10−2 |
5.09 | |||||
(5 mm3) |
6 time interval sampling |
– |
k85 = 11.8 × 10−2 |
5.85 | |||||
– |
k80 = 10.3 × 10−2 |
9.2 |
1 |
0.987 |
70–90 |
6.72 | |||
– |
k75 = 8.11 × 10−2 |
8.55 | |||||||
– |
k70 = 6.49 × 10−2 |
10.68 | |||||||
– |
k90 = 18.8 × 10−2 |
3.68 |
Nambi et al. (2016) |
||||||
Green peas |
Assay: Folin-Ciocalteau |
– |
k85 = 10.2 × 10−2 |
6.80 | |||||
(~7 +/− 0.5 mm dia) |
– |
k80 = 9.73 × 10−2 |
17.8 |
1 |
0.954 |
70–90 |
7.12 | ||
UV-VIS – A751 |
– |
k75 = 6.41 × 10−2 |
10.81 | ||||||
– |
k70 = 3.93 × 10−2 |
17.62 | |||||||
Phenolics |
– |
k90 = 10.2 × 10−2 |
6.77 | ||||||
Egg plant |
– |
k85 = 6.98 × 10−2 |
9.93 | ||||||
(5 mm3) |
– |
k80 = 5.17 × 10−2 |
11.7 |
1 |
0.946 |
70–90 |
13.41 | ||
– |
k75 = 4.69 × 10−2 |
14.77 | |||||||
– |
k70 = 3.80 × 10−2 |
18.23 | |||||||
Phenolics |
– |
k90 = 15.3 × 10−2 |
4.54 | ||||||
Green pepper |
– |
k85 = 12.0 × 10−2 |
5.79 | ||||||
(5 × 5 × 3 mm) |
– |
k80 = 8.73 × 10−2 |
16.3 |
1 |
0.994 |
70–90 |
7.94 | ||
– |
k75 = 5.75 × 10−2 |
12.06 | |||||||
– |
k70 = 4.24 × 10−2 |
16.34 | |||||||
Antioxidant activity |
Blanching (0–15 min) |
Nambi et al. (2016) |
|||||||
Beetroot |
6 time interval sampling |
– |
k90 = 1.27 × 10−2 |
54.54 | |||||
– |
k85 = 1.15 × 10−2 |
60.43 | |||||||
– |
k80 = 1.03 × 10−2 |
5.4 |
1 |
0.999 |
70–90 |
67.56 | |||
*Assay: % DPPH inhibition |
– |
k75 = 0.925 × 10−2 |
74.93 | ||||||
– |
k70 = 0.817 × 10−2 |
84.84 | |||||||
Antioxidant activity |
UV-VIS – A516 |
– |
k90 = 3.68 × 10−2 |
18.85 | |||||
Green peas |
– |
k85 = 3.51 × 10−2 |
19.75 | ||||||
(~7 +/− 0.5 mm dia) |
– |
k80 = 3.86 × 10−2 |
8.3 |
1 |
0.622 |
70–90 |
17.97 | ||
– |
k75 = 3.13 × 10−2 |
22.13 | |||||||
– |
k70 = 1.70 × 10−2 |
40.70 | |||||||
Antioxidant activity |
– |
k90 = 4.63 × 10−2 |
14.97 | ||||||
Egg plant |
– |
k85 = 3.82 × 10−2 |
18.16 | ||||||
(5 mm3) |
– |
k80 = 1.91 × 10−2 |
15.1 |
1 |
0.879 |
70–90 |
36.35 | ||
– |
k75 = 2.24 × 10−2 |
30.94 | |||||||
– |
k70 = 1.31 × 10−2 |
52.99 | |||||||
Antioxidant activity |
– |
k90 = 2.55 × 10−2 |
27.19 | ||||||
Green pepper |
– |
k85 = 2.16 × 10−2 |
32.11 | ||||||
(5 × 5 × 3 mm) |
– |
k80 = 1.49 × 10−2 |
10.1 |
1 |
0.951 |
70–90 |
46.43 | ||
*DPPH = 2,2-diphenyl-2-picryl-hydrazyl (radical) |
– |
k75 = 1.46 × 10−2 |
47.38 | ||||||
% inhibition DPPH = [(Acontrol-Asample]∙100/[Acontrol] |
– |
k70 = 1.12 × 10−2 |
61.89 |
a Values reported by authors.
Part 73, Subpart A: Color Additives Exempt from Batch Certificationa |
||||
---|---|---|---|---|
21 CFR Section |
Straight Color |
EEC# |
Year Approvedb |
Uses and Restrictions |
73.30 |
Annatto extract |
E160b |
1963 |
Foods generally. |
73.40 |
Dehydrated beets (beet powder) |
E162 |
1967 |
Foods generally. |
73.75 |
Canthaxanthinc |
E161g |
1969 |
Foods generally, ≤ 30 mg/lb of solid or semisolid food or per pint of liquid food; May also be used in broiler chicken feed. |
73.85 |
Caramel |
E150a-d |
1963 |
Foods generally. |
73.90 |
β-Apo-8′-carotenal |
E160e |
1963 |
Foods generally, ≤ 15 mg/lb solid, 15 mg/pt liquid. |
73.95 |
β-Carotene |
E160a |
1964 |
Foods generally. |
73.10 |
Cochineal extract |
E120 |
1969 |
Foods generally |
2009 |
Food label must use common or usual name “cochineal extract”; effective January 5, 2011. |
|||
73.10 |
Carmine |
E120 |
1967 |
Foods generally. |
2009 |
Food label must use common or usual name “carmine”; effective January 5, 2011. |
|||
73.13 |
Sodium copper chlorophyllinc |
E141 |
2002 |
Citrus-based dry beverage mixes ≤ 0.2 percent in dry mix; extracted from alfalfa. |
73.14 |
Toasted partially defatted cooked cottonseed flour |
– |
1964 |
Foods generally. |
73.17 |
Grape color extractc |
E163? |
1981 |
Non-beverage food. |
73.17 |
Grape skin extract (enocianina) |
E163? |
1966 |
Still & carbonated drinks & ades; beverage bases; alcoholic beverages (restrict. 27 CFR Parts 4 & 5). |
73.25 |
Fruit juicec |
– |
1966 |
Foods generally. |
1995 |
Dried color additive. |
|||
73.26 |
Vegetable juicec |
– |
1966 |
Foods generally. |
1995 |
Dried color additive, water infusion. |
|||
73.30 |
Carrot oil |
– |
1967 |
Foods generally. |
73.34 |
Paprika |
E160c |
1966 |
Foods generally. |
73.35 |
Paprika oleoresin |
E160c |
1966 |
Foods generally. |
73.45 |
Riboflavin |
E101 |
1967 |
Foods generally. |
73.50 |
Saffron |
E164 |
1966 |
Foods generally. |
73.53 |
Spirulina extract |
– |
2013 |
Candy and chewing gum. |
2014 |
Coloring confections (including candy and chewing gum), frostings, ice cream and frozen desserts, dessert coatings and toppings, beverage mixes and powders, yogurts, custards, puddings, cottage cheese, gelatin, breadcrumbs, and ready-to-eat cereals (excluding extruded cereals). |
|||
73.59 |
Tomato lycopene extract; tomato lycopene concentratec |
E160 |
2006 |
Foods generally. |
73.60 |
Turmeric |
E100 |
1966 |
Foods generally. |
73.62 |
Turmeric oleoresin |
E100 |
1966 |
Foods generally. |
a The color additives Astaxanthin, Astaxanthin dimethyldisuccinate, Ultramarine blue, Canthaxanthin, Haematococcus algae meal, Synthetic iron oxide, Dried algae meal, Tagetes (Aztec marigold) meal and extract, Corn endosperm oil, Paracoccus pigment, and Phaffia yeast are approved for specific uses in animal food (see 21 CFR 73.35, 73.37, 73.50, 73.75, 73.185, 73.200, 73.275, 73.295, 73.315, 73.352, and 73.355, respectively).
b The year approved is based on the date listed in the “Confirmation of Effective Date” notice for the action as published in the Federal Register.
c Petitioned for use after the 1960 amendments; not provisionally listed.
When dealing with vitamin C, it is important to understand the bioavailability and kinetics of retention in processing and storage of related compounds. Ascorbic acid and dehydroascorbic acid are the chemical forms with primary vitamin activity. Dehydroascorbic acid, however, is not stable to heat, and is rapidly hydrolyzed to 2,3-diketogulonic acid and further breakdown products. Other compounds such as ascorbate-2-phosphate, a fully active compound (Liao and Seib, 1988); ascorbigen, a form of ascorbic acid bound to phenols, with 10–20% bioavailability in guinea pigs (Matano and Kato, 1967); and isoascorbic acid (erythorbic acid) with about 5% vitamin activity and with a limiting effect on the absorption of ascorbic acid (Hornig et al., 1974), may need some consideration as well.
Taking into account the stability of ascorbic acid in food systems during processing, vitamin C as well as thiamine and folic acid are normally considered to be good indicators of the severity of a food process. If these vitamins are well retained, we may safely assume that all other nutrients are well retained during processing. Based on the recent FDA dietary recommendations and admonitions to increase fruit and vegetable, as well as whole grain consumption, the significance of understanding vitamin retention during processing and its bioavailability have become increasingly important.
Since fruits and vegetables are major contributors to micronutrients, in particular vitamin C, a vast number of studies have been published reporting kinetic information on the stability of this compound in blanching, canning, dehydration, high pressure sterilization, pasteurization, and freezing operations (Giannakourou and Taouki, 2003; Selman, 1994; Martins and Silva, 2003; Van den Broeck, et al., 1998; Viera et al., 2015; etc.). Killeit (1994), for example, reviewed vitamin retention during extrusion and pointed out mostly destructive effects, with vitamin C being the most sensitive. He also reported that through modification of the vitamin molecule, there was potential for improved stability. An example cited was the commercially available L-ascorbyl-2-polyphosphate (AsPP), a modified form of ascorbic acid, used for feed applications. An extruded feed for catfish containing AsPP showed improved stability through the process as compared to a traditionally used ethylcellulose-coated ascorbic acid (83% retention vs. 39%) and no losses during storage as compared with 78% loss of the traditionally coated ascorbic acid (Robinson et al., 1989). Reports indicate complete bioavailability of this compound for the animals (Grant et al., 1989). In a similar study, Marchetti et al. (1999) reported 80% loss of ascorbic acid during extrusion of a fortified fish feed when using a pure crystalline form of the vitamin, but only a 48% loss when using an encapsulated form of the vitamin; furthermore, during 6 months storage at room temperature, losses showed an additional 80% loss with the non-encapsulated ascorbic acid compared to <20% loss with the encapsulated form.
As summarized by Clydesdale et al. (1991), other components present in food systems may have a major impact on the kinetics of ascorbic acid degradation by changing the reactivity of the system, thus eventually impacting its bioavailability. For instance, minerals such as iron and copper, vitamin E, flavonoids, amino acids, and sugars can significantly change the retention of ascorbic acid during processing and storage, as well as its bioavailability. Van den Broeck et al. (1998) reported that ascorbic acid found in real food systems such as orange juice and tomatoes had less stability than buffered solutions of ascorbic acid (pH 4–8) subjected to heat (120°C–150°C) or combined pressure/thermal treatment (8.5 kbar [850 MPa]/65°C–80°C). Verbeyst et al. (2013) proposed a mechanistic biphasic model for the degradation of ascorbic acid and the consecutive formation and degradation of dehydroascorbic acid (DHAA) during thermal processing (80°C–140°C) of strawberries at atmospheric and at high pressure (700 MPa, 60°C–110°C), under aerobic and anaerobic conditions. They found oxidation of ascorbic acid to DHAA to be the most critical factor for overall conditions, while the anaerobic reaction was critical only at high temperatures (>120°C) for extended times (Table 3.3). Lavelli and Giovanelli (2003) reported pseudo-first-order kinetics of ascorbic acid degradation in tomato products as related to stability of various carotenoids and phenolics during storage (30°C–50°C/90 days) and found degradation of ascorbic acid even at 30°C.
Light-induced degradation of ascorbic acid in the presence of riboflavin has been a subject of investigation. Several studies suggest that riboflavin is first excit ed by visible light, and then, through an excitation transfer, ascorbic acid is oxidized. The reaction mechanism proposes the formation of H2O2 (Şahbaz and Somer, 1993; Şansal and Somer, 1997).
Thiamine, also known as Vitamin B1, thiamine chloride, aneurin, and antiberiberi vitamin, occurs either in the free thiamine form, as a protein complex, as mono-, di-, or triphosphate esters (TMP, TPP, TTP, respectively), or as a phosphorous protein complex. The structure of the free base form is characterized by a pyrimidine ring linked by a methylene bridge to the 3-nitrogen atom in a substituted thiazole ring; its chemical name is 3-[(4′-amino-2′-methyl-5′-pyrimidinyl) methyl]-5-(2-hydroxyethyl)-4-methylthiazole (Figure 3.10). Thiamine hydrochloride is used as the US Pharmacopeia reference standard and is the form used for food and pharmaceutical fortification, as well as thiamine mononitrate. Thiamine is an essential nutrient required for carbohydrate, nucleic acid, and amino acid metabolism as well as being involved in nerve function; it is converted in vivo to thiamine diphosphate (TPP), the coenzyme in decarboxylation of α-keto acids. More recent work has shown involvement of TPP in the metabolism of 3-methyl-branched fatty acids (Foulon et al., 2003). More detailed reviews on the physiological aspects of thiamine can be found (Bates (2007; Bettendorf (2014). Foods considered to be rich in vitamin B1 include whole grains (cereal germ), nuts, brown rice (or white rice including aleurone layer [silver skin]), pork, egg yolk, yeast, fruit, and vegetables. Thiamine is known as one of the least stable of the water-soluble vitamins. While thiamine has been found unstable in neutral and alkaline solutions, it can withstand up to 120°C for one hour in acidic solutions, although is susceptible to cleavage by sulfites even in an acidic environment. In dry form it is stable to oxidation, but in solution it is very unstable to oxidation and reduction reactions. Since thiamine can exist in many forms, it is obvious that its stability and its kinetics of degradation are highly affected by the relative concentrations of the different forms (Farrer, 1955). Feliciotti and Esselen (1957), studying the thermal destruction of thiamine in pureed meats and vegetables, suggested that its destruction in foods was dependent on the interrelationship of pH and the relative proportions of the free and the combined forms of the vitamin. It has been observed that the enzyme-bound forms, cocarboxylases, appear to be less stable than the free forms. Mulley et al. (1975b) also reported that under identical conditions, cocarboxylase is destroyed faster than thiamine hydrochloride. It appears that the faster destruction of the cocarboxylase may be due to the pyrophosphoric acid group which is the basic difference between the two molecules, and that appears to cause additional reactivity or stress on the cocarboxylase molecule. The authors also reported that the presence of the cocarboxylase form does not affect the destruction of the free thiamine up to concentration levels of 35%. Since this appears to be the situation in most food products, it is expected that the cocarboxylase form will not interfere with the kinetics of degradation.
Figure 3.10 Chemical structures of the vitamin B1 group (thiamine).
A number of factors will be highly influential on the stability of thiamine, including water activity, pH, temperature, ionic strength, and the presence of other compounds. Some of the suggested mechanisms for thiamine degradation are presented in Figure 3.11. The particular instability of thiamine to heat under neutral and alkaline conditions has resulted in various studies on the chemistry of thiamine degradation. However, due to the high complexity of food materials, a number of studies have been carried out in model systems in order to clarify the mechanisms involved in thiamine degradation. Several authors such as Farrer (1955), Beadle et al. (1943), and Greenwood et al. (1943) established that the thermal destruction of thiamine in aqueous and buffered solutions followed a first-order reaction. Farrer and Morrison (1949) studied the thermal degradation of thiamine in buffered solutions and determined that the Arrhenius equation could be used to describe the effect of temperature. Two possible reactions have been considered leading to the degradation of thiamine, namely, (a) the breaking of the “CH-bridge” leaving the pyrimidine and thiazole moieties and (b) the breakdown of the thiazole ring with the production of hydrogen sulfite. Limited efforts have been made to determine the governing mechanism of thiamine degradation in food systems and rather an overall response is commonly monitored. In fact, the lack of comprehensive kinetic data has limited our understanding of the significance of the different mechanisms involved. Dwivedi and Arnold (1973) summarized the most important aspects affecting the degradation of thiamine in food products and model systems; they also determined that the destruction of the vitamer revolved around the breaking of the methylene bridge to form pyrimidine and thiazole moieties.
Figure 3.11 Degradation pathways of thiamine. (1) Dwivedi and Arnold, 1972a; 1973; (2) Dwivedi and Arnold, 1973; (3) Kawasaki and Daira, 1963; (4) Lhoest, 1958; (5) Zima and Williams, 1940; (6) Sykes and Todd, 1951; (7) Sykes and Todd, 1951; (8) Barger et al., 1935; (9) Metzler, 1960; Dwivedi and Arnold, 1972b.
Of great significance to the area of stability of thiamine has been the observations of s everal investigators that thiamine in natural foods is more heat-resistant than in aqueous and buffered systems. Thus, it appears that certain factors will influence the stability of the vitamin. For instance, Frost and McIntire (1944) indicated that α- and β-amino acids and some of their derivatives had a significant stabilizing effect upon thiamine at pH 6.0. In general, this effect became noticeable at pH values above the range 4.5–5.0. Other compounds such as proteins and starch have been found to improve the thermal stability of thiamine; however, the exact mechanisms involved are not well elucidated.
A controversy still exists regarding the role that oxygen plays in the thermal stability of thiamine. In fact, results presented by Williams and Spies (1938), Farrer (1955), and Mulley et al. (1975a) have demonstrated that the thermal degradation of thiamine can be described by a first-order kinetics and that the reaction was not oxidative in nature. On the other hand, other authors have suggested that for the case of products containing oxygen the reaction became a true first-order reaction upon the disappearance of oxygen (Farrer and Morrison, 1949). Fink and Kessler (1985) studied the retention of thiamine in milk in the temperature range from 4 to 150°C. The authors reported that for the range 35 to 50°C and 72 to 85°C, the reaction followed second-order kinetics. With regard to the effect of oxygen, the authors did not observe any effect on the rate of thiamine losses. Dennison et al. (1977) working with a dehydrated food system, also indicated that the presence of oxygen did not significantly affect the degradation of thiamine.
In model systems, looking at the effect of different solutes, Fernández et al. (1986) reported that the degradation of thiamine followed a first-order reaction and that the degradation was affected by the type of solute used in the formulation, increasing in the order sodium chloride, potassium chloride, glycerol, and sodium sulfate. Thus, not only the rate of degradation was affected by water activity, but also by the specific solute. Bell and White (2000) evaluated stability of thiamine in solid model systems using polyvinylpyrrolidone (used in the medical and pharmaceutical industry as a binder or lubricant) and found that thiamine degradation followed a pseudo-first-order reaction with increasing water activity (a w > 0.4–0.77, pH 7.0, 20°C), but suggested that at lower aw (<0.4), a better correlation was found between glass transition temperature (Tg) and B1 degradation rates, indicating that this is a variable that should be recognized in formulating low moisture products.
It has been determined that in food products, compounds such as sulfites, phenols, and amino acids and proteins as well as lipids may have a significant effect on thiamine degradation and its associated kinetic parameters. Of particular significance is the effect of sulfites on thiamine due to the nucleophilicity of the sulfite ion. Hence, the destruction of thiamine by sulfite becomes a key issue in foods claiming to be a significant source of this vitamin (Vanderveen, 1988).
Fox et al. (1997) reported losses of thiamine in ground pork as a result of irradiation but little or no losses during conventional cooking, heat denaturation, or storage. It was also pointed out that the exclusion of oxygen may improve stability of thiamine during irradiation and that stability was dependent on the source of meat and type of cut (Fox et al., 1995). Van Calenberg et al. (1999) showed the effect of irradiation (3 kGy X-rays [0.05 kGy/min] or electrons [5 kGy/min]) on storage stability of thiamine content of packaged mince chicken meat (air or vacuum); samples were irradiated at −18°C and +5°C, followed by storage at those same designated temperatures. Although no major differences in thiamine loss between dose rates were observed after storage, the most notable differences appeared to be the temperature at which the dosing took place indicating better retention at −18°C compared with 5°C (11%–19% vs. 19%–30% loss of thiamine, respectively), the higher of each group being the vacuum-packaged samples and explained as drip/leaching losses.
Whole grains are noted for their relatively high content in B-vitamins and antioxidant potential. Several researchers have monitored and reported losses of thiamine during various steps in the baking process: up to 48% loss of B1 in white bread, depending upon the process, i.e., extended fermentation times resulted in higher levels of B1, B2, and B6 vitamins (Batifoulier et al., 2005); losses of 20%–45% B1 in sourdough bread production (Mihhalevski et al., 2013); and 20%–22% loss of B1 in rye bread compared with up to 56% loss in white wheat bread (Martinez-Villaluenga et al., 2009), indicating the importance of using whole grains, extended fermentation times, and specific cultures.
As previously indicated, retention of thiamine is normally considered to be an indicator of the intensity of thermal processes such as blanching, canning, freezing, extrusion, dehydration, etc. (Ilo and Berghofer, 1998; Selman, 1994). Butz et al. (2007) investigated effect of high pressure processing at elevated temperatures on thiamine and riboflavin in minced fresh pork and model systems (20°C–100°C, 0.1 MPa, 600 MPa). Under matched conditions for models and pork meat, authors found thiamine destruction nearly 30 times higher in the model systems compared with actual meat samples, emphasizing the importance of working with actual food systems when predicting nutritional quality. Further information on kinetic destruction of thiamine is required for less conventional food processes such as gamma irradiation, high pressure, pulse electric fields, and microwave and radio frequency processing.
Riboflavin, or vitamin B2 (also referred to as vitamin G, lactoflavine, and chemically as 7,8-dimethyl-10-(1′-ribityl) isoalloxazine), is a precursor of the flavin cofactors, FAD (flavin adenine dinucleotide [riboflavin-5′-trihydr ogen-diphosphate]) and FMN (flavin-mononucleotide [riboflavin-5′-monophosphate]), which function in many important enzymatic redox reactions in intermediary metabolism (Figure 3.12). Riboflavin exists in dietary sources predominantly in the form of its coenzyme derivatives, FAD and FMN, which in turn can carry out one- and two-electron transfer reactions involved in diverse biochemical catalytic reactions. Henriques et al. (2010) have presented an overview of many of the updated riboflavin biochemical mechanisms, with particular emphasis on deficiencies of the vitamer and their implications on fatty acid metabolism. The actual free form of riboflavin is more frequently found in commercial multivitamin applications. Common biological sources of B2 are similar to most of the other B-vitamins, including eggs, milk, cheese, meats (liver and kidneys), yeast, and leafy green vegetables. From a nutritional perspective, it should be pointed out that, although green plants can synthesize their own free riboflavin and mammals cannot, the relative amounts found in meat sources (as NAD and FMN) are significantly higher than totals found in most plants. In that FAD and FMN occur chiefly in non-covalently-bound forms to enzymes, while covalently-bound flavins are less available for absorption, are all factors to consider when carrying out vitamer analyses. More detailed reviews of the biochemical function of the flavins have been published (Powers, 2003; Henriques et al.; 2010; Pinto and Rivlin, 2014). Riboflavin is relatively stable in foods under ordinary conditions, as long as it is not exposed to light. It has relatively low water solubility (0.067–0.333 mg/ml) and exhibits a fluorescent yellow-green color (Merck, 2002), which can limit its ability for fortification from a visual perspective, although it may be used as a food colorant with potential health benefits (Table 3.4). FMN has slightly higher solubility and may be a better choice for liquid applications; however, color may still be an issue, as this is also used as a colorant in Europe (E101a). Stability of riboflavin is pH dependent, being more stable under acidic conditions, with maximum stability to heat being between pH 2.0 and 5.0 and destruction of the isoalloxazine ring at pH > 7.0 (Ball et al., 1994). With regard to FAD and FMN, they are both readily converted to riboflavin at pH < 5.0 (Russell and Vanderslice, 1990). This factor is actually used as a prestep when analyzing for total riboflavin; however, it should be avoided if analyzing for each of the three vitamers individually.
Figure 3.12 Chemical structures of the vitamin B2 group (riboflavin, FMN, FAD).
Photochemical cleavage of riboflavin under alkaline conditions results in the formation of the highly reactive compound, lumiflavin, which mediates the destruction of other vitamins. Under neutral and acidic conditions, this vitamin loses the ribityl side chain forming lumichrome (Figure 3.13). Both lumichrome and lumiflavin have no biological activity; moreover, the photolysis reaction is irreversible. Work carried out by Woodcock et al. (1982) in pasta products, indicated that lumichrome, a photolysate of riboflavin, was not the only one or the final degradation product. In fact, in these types of products, only 60% of the losses were accounted for by the presence of lumichrome and varied according to the process conditions. Palanuk and Warthesen (1988) studied the kinetics of degradation of riboflavin and lumichrome in milk and observed that the rate of degradation of riboflavin was 2.8 times greater than the rate of lumichrome formation, and that the rate of lumichrome formation was 6.3 times greater than the rate of lumichrome degradation. The combined effect was such that after an increase in lumichrome formation, leveling off of the reaction took place. According to the authors’ model, 23.4% of the riboflavin degraded to lumichrome, indicating that either riboflavin degraded to other products, or that lumichrome became bound to other components in the system, becoming unavailable for determination. Results reported by Furuya et al. (1984) also indicated that lumichrome content in both buffer systems and pasta leveled off during storage, while the concentration of riboflavin continuously decreased. Thus, simple monitoring of the formation of this compound will not be a reliable method to measure the losses of the vitamin. The degradation of riboflavin under aerobic conditions has been generally reported as following first-order reaction kinetics.
Figure 3.13 Degradation pathways of riboflavin. (1) Kuhn et al., 1933; Wagner-Jauregg, 1972; (2) Holmström and Oster, 1961; Kuhn et al., 1933; (3) Holmström and Oster, 1961; (4) Holmström and Oster, 1961; (5) Karrer et al., 1934; (6) Choe et al., 2005.
A list of some of the most important studies with the corresponding rates of degradation is presented in Table 3.3. Although the degradation of the vitamin has often been categorized as being a first-order reaction, the exact approach for the monitoring of the degradation will play a significant role. Woodcock et al. (1982) indicated that lumichrome production in pasta products followed two basic steps. The first stage followed first-order reaction kinetics that proceeded at a fast rate and a second stage that involved the disappearance of lumichrome and could not be easily described in kinetic terms. The photodegradation of riboflavin in milk has been determined to follow first-order kinetics (Singh et al. 1975; and Allen and Parks, 1979). Kinetic parameters were found to be influenced by temperature and the presence of light. From the point of view of kinetics, limited work has been carried out to clearly determine the mechanisms involved in the degradation of riboflavin and their contribution to the overall kinetic values. Based on some of the work reported by several authors, it is evident that the concentration of lumiflavin and lumichrome will influence the kinetic values reported, if these products of the reaction are the ones to be monit ored as a measurement of stability. It is well known through the many studies carried out looking at stability of riboflavin in milk under varied commercial retail light conditions that there is significant loss of shelf-life due to light induced oxidation and development of off-flavors and that proper light barrier packaging is needed (Cladman et al., 1998; Mestdaugh et al., 2005); however, with the recent introduction of LED lighting in commercial spaces, there is a whole new wave of experimental variables to consider. There has been a great deal of concern that LED lighting has potentially imposed new risks of loss in shelf-life quality in milk (De Jesus and Dando, 2016); a key factor pointed out by the authors is the specific wavelength involved for the specific LED light. On the other hand, studies by Brothersen et al. (2016) found exposure to LED at 4000 lx, or fluorescent light at 2200 lx for 24 hours vs. a control (no light) sample, that either light showed some changes in quality, but samples with LED showed less off-flavors than those samples exposed to fluorescent lighting from both a consumer taste panel perspective as well as an analytical analysis of both riboflavin and vitamin A degradation perspectives. It is obvious further work for clarification will need to be carried out.
Studies presented by Toyosaki et al. (1988) indicate that the photolysis mechanism can be described according to the following reactions:
According to the authors, standard riboflavin proceeded by one-phase decomposition under all the conditions studied. Standard riboflavin underwent photolysis in which no active oxygen was produced. On the other hand, milk serum riboflavin was photolyzed by a two-phase decomposition when the intensity of the irradiation was low. The presence of active oxygen was found to be involved in the reaction. Increased irradiation was reported to change the photolysis of the milk serum riboflavin from a two-phase to a one-phase decomposition mechanism, with smaller amounts of active oxygen being produced. Jung et al. (2007) identified formation of a single compound, 2,3-butanedione, during photolysis of riboflavin in phosphate buffer (0.1M, pH 6.5) as analyzed by SPME-GC/MS.
Photosensitization of riboflavin can produce reactive oxygen species such as superoxide anion, singlet oxygen, hydroxyl radical, and hydrogen peroxide. These reactive oxygen species and radicals have been found to affect the decomposition of proteins, lipids, vitamins, and other nutritional components (Choe et al., 2005). For example, Kim et al. (2010) found that in the presence of both riboflavin and light (4°C, 8 hours) in aqueous solutions of anthocyanins (from meoru grape) there was production of singlet oxygen resulting in significant degradation of the anthocyanins. On one hand, this validates the antioxidant properties of anthocyanins, but also cautions that the intentions of using anthocyanins as antioxidants which will be lost if improper storage or combinations of reactant species are present; riboflavin with anthocyanins without the presence of light or anthocyanins without riboflavin but in the presence of light showed little or no degradation of the anthocyanins. Similarly, Yang et al. (2008) found apparent first-order degradation kinetics of isoflavones (daidzein and genistein) from soybeans in the presence of riboflavin and light (7 hours, room temperature), with rate constants of 0.234 and 0.193/hr., respectively. Montaña et al. (2010) also carried out a kinetic and mechanistic study on riboflavin photo-generated reactive oxygen species and determined the induced degradation of isoflavones (quercetin, morin, and rutin), the extent of which depended upon differences in molecular structure of the reactants, which further emphasized the importance of combined reactants in terms of formulation and protective measures that are required for proper storage stability; reaction kinetics were reported to follow first-order kinetics. Cardoso et al. (2012) reviewed the mechanisms of riboflavin as a photosensitizer looking at the effects on overall quality of foods and the effect on human health; they found th at both carotenoids and polyphenols can counteract degradation effects induced by riboflavin exposed to light, although by different mechanisms. Riboflavin is considered to be relatively stable during food processing and storage, except under light, where absorption of light will produce excited triplet state riboflavin. On the other hand, as in the case of most water-soluble vitamins, substantial losses of riboflavin in many food products may be due to leaching during blanching into the process/cooking water. For instance, Prodanov et al. (2004) found significant losses of B-vitamins leached out during soaking and cooking of various legumes with as much as 70% loss of riboflavin from chickpeas. Thus, blanching operations and cooking of vegetables will result in extensive losses of this vitamin. Several authors (Petrou, et al. 2002) have reported kinetic information of vitamin degradation upon cooking, which in the light of the most recent developments in terms of nutritional claims, it has become information of critical importance to product processing and development. In fact, vitamin losses during cooking need to be accounted for when making nutritional claims in a finished product.
Niacin, originally discovered as PP (pellagra-preventative) factor early in the 1900s, and chemically known as C6H5O2N, nicotinic acid, 3-pyridinecarboxylic acid, or pyridine-β-carboxylic acid, is paired with nicotinamide (C6H6ON2, 3-pyridinecarboxylic acid amide) and a variety of pyridine nucleotide structures that all possess similar biological activity, now all considered as part of the vitamin B3 complex (Figure 3.14). This group of niacin vitamers acts as precursors of the coenzymes NAD (nicotinamide adenine dinucleotide) and NADP (NAD-phosphate), involved in carbohydrate, lipid, and amino acid metabolism. Niacin is well known in its therapeutic role to be administered to reduce serum cholesterol (Ganji et al., 2003). Its deficiency has been associated with the well-documented disease pellagra, symptoms of which include diarrhea, dementia, sun-sensitive dermatitis, and potentially death (the “4-D’s of pellagra”). Niacin has been considered the most stable of the water-soluble vitamins; biological activity is generally unaffected by thermal processing, acid, alkali, light, or oxidation. However, losses as high as 30%–70% in the case of lentils have been shown to occur due to leaching in water during cooking or soaking processes (Prodanov et al., 2004). Naturally occurring niacin in plant foods often exists mostly in the form of nicotinic acid in a bound esterified form to glycopeptides and polysaccharides and is not readily available for absorption in humans. As an example, in wheat bran, it was reported that an ester linkage between nicotinic acid and glucose was a mechanism for formation of unavailable niacin in plants (Koetz et al, 1979). For instance, without alkali pretreatment of corn, the naturally occurring niacin is only about 35% available and as little as 50% available in unfortified wheat products (Hepburn, 1971). Niacin from animals is in the more available forms of NAD and NADP coenzymes, along with tryptophan, which works in combination in the absorption of niacin in vivo. Since tryptophan has been shown to alleviate some niacin deficiencies, due to its action as a precursor for biosynthesis of nicotinic acid in vivo, the concept of niacin equivalents (NE) was adopted (Horwitt et al., 1981), such that a conversion factor was developed for tryptophan (1 NE = 1 mg niacin = 60 mg dietary tryptophan). Owing to this fact, a balanced protein diet is important to maintain a required dietary mg NE (RDA, 16–18 mg for adults). Some of the highest sources of niacin include fortified breakfast cereals, enriched flours, yeast, chicken breast meat, roasted peanuts, tuna, and liver (USDA, 2006). Nicotinic acid has significantly lower solubility than nicotinamide (only 0.016 g/ml vs. 1.0 g/ml water, respectively [Merck, 2002]), which impacts the selection of food type used as a vehicle for fortification. Generally, nicotinamide can be used for either dry or liquid products; whereas, nicotinic acid is incorporated more in solid or semisolid foods. It has also been noted that nicotinamide has a threshold above which may result in bitter off-flavors. Several in depth reviews on the biochemical significance of niacin in absorption, transport, and metabolism have been published (Ball, 2004; Kirkland, 2007; Eitenmiller et al., 2008). From a processing perspective, there has not been a great deal published on stability of niacin or its derivatives, perhaps due to its reported higher stability as compared to other vitamins. For instance, Marchetti et al. (1999) found minimal losses of nicotinamide (about 6%–8%) during extrusion processing (96°C outlet temperature, followed by 20 minutes drying at 95°C) of a vitamin supplement blend in fish feed with only 5%–8% loss in finished product after storage for 6 months at room temperature; a microbiological assay (Lactobacillus plantarum 8014) was used for analysis of nicotinamide. In a study on stability of B-complex vitamins during sourdough bread manufacturing, Mihhalevski et al. (2013) reported losses of 25%–50% of nicotinic acid and a concomitant ten-fold increase in nicotinamide, as assayed using an HPLC-MS; this increase was presumed to be due to the microbial activity during the sourdough fermentation step. Within this same baking study, by comparison, there was found a 20%–45% loss of vitamin B1, 50% loss of B2, 45%–65% loss of B6-pyridoxal, and 15% loss of B6-pyridoxine. Muhamed et al. (2015), on the other hand, reported that degradation of nicotinic acid followed first-order kinetics when subjected to temperatures 90°C–120°C as investigated in pure buffered systems as well as in Averrhoa bilimbi fruit puree; authors found 50% losses of nicotinic acid after about 22–28 min at 90°C and 100°C (Table 3.3). In another study on losses of niacin in potatoes (cubed) and niacin model systems, first-order kinetics were followed in a temperature range 50°C–120°C for up to 60 min. with very similar half-lives between the two systems (Table 3.3), but slightly lower reaction rates in potatoes compared to aqueous solutions over the course of the experiment (Nisha et al., 2009). Although it has a higher stability relative to other vitamins, it is still important to consider the impact of processing of an essential nutrient such as niacin (both nicotinic acid and nicotinamide).
Figure 3.14 Chemical structures of the niacin vitamin B3 group (nicotinic acid and nicotinamide).
Vitamin B6 is a collective term referring to a group of vitamers that possess similar biological activity and share the main chemical structure of 2-methyl-3-hydroxy-5-hydroxy methyl pyrimidine compounds. Originally identified by Gyorgy in the 1930s as a curative for dermatitis in rats, it was later referred to as pyridoxine (pyridoxol), which in addition to the structure aforementioned it has attached a hydroxymethyl group in the 4-position of the pyrimidine ring (Figure 3.15). The metabolically active form of B6 is pyridoxal-5′-phosphate. Other common vitamers include pyridoxal (with an aldehyde group at the 4-position) and pyridoxamine (with an aminoethyl group at the 4-position), all of which can be readily interconverted into one form or the other and each can exist in a phosphorylated form (Eitenmiller et al., 2008). Pyridoxine and pyridoxamine and their phosphorylated counterparts are the major form of B6 found in plant sources, whereas, pyridoxal and its phosphorylated form are more prevalent in animal foods. The most common commercially available form is pyridoxine hydrochloride. Limited kinetic information is available for the degradation of the vitamin B6 compounds. Several authors have reported the interconversion of the B6 vitamers. Results presented by Gregory and Hiner (1983) indicate that a bidirectional conversion of pyridoxal and pyridoxamine during processing exists. Prior to this work, Gregory and Kirk (1978) had reported on the rapid conversion of pyridoxamine to pyridoxal during storage at low moisture content in systems containing protein and reducing sugars, although the reverse reaction was not detected. Yonker (1984) had also observed interconversion of pyridoxamine-5′-phosphate to pyridoxamine to pyridoxine and pyridoxal.
Figure 3.15 Chemical structures of the vitamin B6 group (pyridoxine, pyridoxamine, pyridoxal).
Under storage conditions, Gregory and Kirk (1978) found first-order kinetics for the degradation of the different vitamers in model systems. Pyridoxamine appeared to be the vitamer with the highest complexity in its degradation mechanisms and kinetics. In systems fortified with pyridoxamine, the degradation of this vitamer followed first-order kinetics with conversion into pyridoxal through a transamination process. The limiting factor in this case was the degradation of pyridoxal since the reverse reaction, pyridoxal conversion into pyridoxamine, was not significant.
Navankasattusas and Lund (1982) reported on the stability of vitamin B6 vitamers in phosphate buffer solutions and cauliflower puree at high temperature, in the range 110°C–140°C. The authors reported that the thermal degradation of pyridoxamine followed pseudo-first-order reaction kinetics, whereby the degradation of the vitamer appeared to be slightly dependent on the initial concentration, while the degradation of pyridoxine and pyridoxal followed 1.5 and second-order kinetics, respectively. For the case of cauliflower puree, the kinetics of degradation were observed to deviate from first-order reaction kinetics throughout the entire heating time. Working with a model food system simulating a ready-to-eat breakfast cereal, Evans et al. (1981) determined that the degradation of pyridoxine followed first-order kinetics for the range 155°C–200°C.
Limited kinetic information is available with regard to the influence of pH on the stability of the different vitamers, although alkali pH has been shown to enhance the decomposition of all the B6 vitamers. Saidi and Warthesen (1983) evaluated the effect of pH as well as water activity, light, and temperature on B6 vitamer model systems. Pyridoxine was found to be very stable in the pH range 4.0–7.0 when held at 40°C and 60°C for up to 140 days. For the case of pyridoxamine under the same conditions, the authors indicated that the reaction followed first-order kinetics causing more vitamin losses. Pyridoxamine degradation appeared to follow the trend of higher degradation upon an increase in pH. The authors, however, indicated that the effect of pH was not totally clear. Experiments carried out in model systems, indicated that pyridoxal was much more light sensitive than pyridoxine or pyridoxamine. In general, the stability of vitamin B6 has been observed to be influenced by pH, light and temperature; however, additional information is needed to clearly characterize the effect of these parameters on the kinetics of degradation and on the mechanisms involved. Kinetic information on vitamin B6 stability in food products is reported in Table 3.3.
Information reported by Paul and Southgate (1978) indicated a substantial loss (~40%) of vitamin B6 during cooking of vegetables. Losses were significant in both root and leafy vegetables. Their information highlights significant losses of thiamine, folate, vitamin C, and vitamin B6 expected during industrial blanching operations, much of which has been later determined to be accounted for through leaching losses rather than degradation of the individual vitamers, such as the case found by Delchier et al. (2013) where intact folates were found in the discarded waste water of such operations with a total loss of 20%–25% of vitamer from the vegetables.
Vitamin B12 is chemically the largest and most complex of all the vitamins, composed of a central cobalt atom planarly coordinated via nitrogen atoms to a porphyrin-like group referred to as corrin with axial coordination sites occupied by a 5,6-dimethylbenzimidazole base and a cyano group. Vitamin B12 is also referred to as cyanocobalamin and part of a larger group collectively known as cobalamins and plays a critical role in the methylation process as well as in lipid and carbohydrate metabolism. It is synthesized by a select group of microorganisms, and its main source in foods is of animal origin (e.g., meats [beef liver], fish, eggs, milk); consequently, deficiency risks commonly exist among groups with low intake of animal products (Gille and Schmid, 2015). Deficiency is particularly critical during pregnancy and lactation with potential risks of megaloblastic anemia (Pawlak et al., 2013; Griebe, 2017). One of the predominant forms of this vitamin is referred to as coenzyme B12, where the cyano group at the sixth coordination position is substituted by 5-deoxyadenosine, attached to the cobalt atom via a methylene group. Another common form found in foods is the hydroxocobalamin (also called vitamin B12a or hydroxo-B12), where the cyano group is replaced with a hydroxy group (Farquharson and Adams, 1976; Schneider, 1987). Other cobalamins include methyl- (CH3), nitrito- (NO2), and sufito- (HSO3) groups substituting for the cyano group. Vitamin B12 analogues refer to a group where the 5,6-dimethylbenzimidazole base is replaced with other substituent groups (Figure 3.16).
Figure 3.16 Chemical structures of vitamin B12 and cobalamin cofactors. (adapted from Matthews, 1984).
In general, limited kinetic information is available on the stability of vitamin B12. It has been reported, however, that this vitamin is slightly unstable in mild acid or alkaline solutions. In the pH range 4.0 to 7.0, this vitamin appears to have good stability. The presence of compounds such as ascorbic acid has been reported to influence the destruction of this vitamin by authors such as Herbert and Jacob (1974), while others such as Newmark et al. (1976) did not appear to detect any significant difference in food systems containing ascorbic acid. Iron, either ionic or in complexed forms, has been found to provide vitamin stability in the presence of ascorbic acid in liver extracts and pharmaceutical formulations (Shenoy and Ramasarma, 1955). It is considered that the stability of vitamin B12 in food systems is very different from that found in pharmaceutical formulations or model systems, since vitamin B12 in foods is tightly bound. For instance, in liver, cobalamin is present in the form of a coenzyme bound to a liver protein. Stability has been attributed to reduced accessibility of the vitamin for chemical attack.
Information on vitamin B12 retention when food products are heated or processed using microwaves is limited. Watanabe et al. (1998) reported that appreciable losses (~30%–40%) of vitamin B12 occurred when microwave heating raw beef, pork, and milk. The authors also reported that when microwave heating hydroxo vitamin B12, which predominates in foods, two biologically inactive degradation compounds were identified. Very limited information is available on other food-occurring vitamin B12 analogues with different β-ligands, such as methyl vitamin B12 and 5′-deoxyadenosyl vitamin B12. A more recent study on stability of different forms of B12 (commercially prepared cyano- and hydroxo-cobalamins, and an in situ form of B12 from a Propionibacterium freudenreichii culture) during different stages of the bread manufacturing process was carried out by Edelmann et al. (2016). They observed the proofing stage did not significantly affect vitamer levels, but 21%–31% of the hydroxocobalamin was lost during the baking step with straight- and sponge-dough processes; whereas, the cyanocobalamin form and in situ prepared B12 were stable. In sourdough baking, however, both commercial vitamers had losses (23% of cyanocobalamin and 44% of hydroxocobalamin), as well as the in situ B12, as determined by both micro (using L. delbrueckii) and HPLC methods of analysis. The authors found comparable results between methods of analysis for the commercial vitamers, but the micro method was not suitable for analysis of the in situ B12, perhaps due to the presence of other growth stimulating compounds, and thus resulting in overestimation. Considering the importance of B12 in the diet from a nutritional perspective, being able to incorporate this nutrient in a staple food form such as bread would facilitate better nutrition.
Folates or folacin refer to a large group of heterocyclic derivatives with similar biological function and a common basic structure, N-[4-[{(2-amino-1, 4-dihydro-4-oxo-6-pteridinyl)-methyl} amino] benzoyl] glutamic acid, with or without additional L-glutamic acid residues conjugated via peptide linkages through the γ–carboxyl groups of succeeding glutamate molecules. Since its discovery as an important dietary factor in the early 1930s, it has undergone a series of name changes including vitamin M, vitamin U, vitamin Bc, B9, and L. casei factor. Folate deficiencies have become increasingly a worldwide concern at all socioeconomic levels. It is a common cause of megaloblastic anemia and is either directly or indirectly responsible for the defective synthesis of nucleic acids, frequently occurring in newborn infants. This is usually found due to a folate deficiency during gestation often subsequently resulting in intellectual disability. This group of compounds, of great nutritional significance, has not received adequate attention from the point of view of kinetics. In fact, a large number of parameters can affect the stability of folates, including pH, water activity, temperature, oxygen availability, light, metal traces, etc. Moreover, the stability is dependent upon the particular vitamer under consideration. Some of the most important derivatives of this group include 5-methyltetrahydrofolic, tetrahydrofolic, dihydrofolic, 5-formyltetrahydrofolic, and folic acids. Due to complications in the separation of this extremely large number of individual derivatives in this group of vitamins, a thorough analysis for the stability of the different vitamers has seldom been carried out. However, because of their individual biological activity, they each need to be taken into consideration. In fact, the literature is very scarce when it comes to the stability of folates in foods other than the parent compound, folic acid. Most information corresponds to model systems or buffer solutions, except for cases such as apple and tomato juices, for which kinetic information on 5-methyl tetrahydrofolate (Mnkeni and Beveridge, 1983) as well as on folic acid (Mnkeni and Beveridge, 1982) has been reported. Several authors, including Hawkes and Villota (1986), working with model systems, indicated that folic acid had greater stability as compared to tetrahydrofolic acid and 5-methyl-tetrahydrofolic acid, also biologically available compounds. It was also indicated that the degradation of these three folates followed first-order kinetics within narrow temperature ranges.
Oxidation of tetrahydrofolate (THF) or dihydrofolate (DHF) generally results in loss of the side chain, especially at neutral and low pH (Maruyama et al. 1978). THF has been shown to follow a number of degradation pathways in the presence of air, where both the rate and the mechanisms involved are highly dependent on the pH of the system (Reed and Archer, 1980). It should be mentioned that under neutral and acidic conditions, tetrahydrofolate is degraded to p-aminobenzoyl glutamates and pterin products with no vitamin activity. At higher pH, DHF is a product of the reaction with vitamin activity, but undergoes further oxidation to compounds without any activity. On the other hand, as summarized by Hawkes and Villota (1989a), folic acid is stable under anaerobic conditions in alkaline environment, although as reported by Temple et al. (1981), opening of the pyrimidine ring forming 2-pyrazine carboxylic acid will occur over long periods of storage. Under aerobic conditions, however, degradation will result in cleavage of the side chain to p-aminobenzoyl glutamic acid plus pterin-6-carboxylic acid. Acid hydrolysis, on the other hand, in the presence of oxygen yields a 6-methyl pterin. Hawkes and Villota (1986) indicated that the stability of folic acid, tetrahydrofolic acid, and 5-methyltetrahydrofolic acid decreased with a decrease in pH for the range 7.0–2.0. Folic acid solutions have also been shown to be sensitive to light and may undergo photodecomposition to p-aminobenzoyl-glutamic acid plus pterin-6-carboxylic acid (Lowry et al., 1949).
Most of the literature information appears to indicate that the degradation of folates follows a true first-order reaction. However, the effect of initial concentration has almost never been monitored. Studies have indicated that initial concentration is an important consideration for the kinetics of folate degradation, thus, following pseudo-first-order reaction kinetics. It has also been pointed out that the temperature range studied will affect the mechanism of degradation of the folates, thus resulting in different energies of activation (Hawkes, 1988).
Based on the work presented by different authors and summarized by Hawkes and Villota (1989a), it is clear that the presence of oxygen affects the specific pathways of degradation of folic acid. Considering the oxidative pathways for folic acid, it is obvious that aerobic and anaerobic degradation of the vitamin may occur simultaneously (Figure 3.17). This is of particular importance when fortifying food products subjected to various deleterious processing techniques such as in the case with spray dried fortified formulations (Hawkes and Villota, 1989b). Because of the high complexity existing in food systems, seldom has a clear characterization of the mechanisms involved been reported along with kinetic information. Li et al. (2011) reported on the stability of folic acid incorporated into a complex matrix utilizing a reconstituted fortified extruded rice product, “Ultra Rice”. The composition was a rice flour base with added nutrients including vitamins A and B1, stabilizers, and different sources of iron and titanium dioxide whitener, used to fortify white rice in developing countries. They found degradation during storage (4°C, 60% RH) to follow pseudo-first-order kinetics with greater than 60% retention of folic acid after 9 months, regardless of the iron source used, although there were some detrimental effects with the presence of titanium dioxide used as a whitening agent. Although there was no mention of folate encapsulation in this particular study, Shrestha et al. (2012) found improved stability by using an encapsulated form of 5-methyl THF during extrusion over a range of temperatures (100–150°C), with retentions of 84%–94.5% with the encapsulated form vs. the non-encapsulated form (65.3%–83.2%).
Figure 3.17 Degradation pathways of folic acid. (1) Hutchings et al., 1948; (2) Waller et al., 1950; (3) Baugh et al., 1979; (4) Temple et al., 1981; (5) Stokstad et al., 1948; (6) Brown et al., 1974; and Maruyama et al., 1978; (7) Lowry et al., 1949; (8) Reed and Archer, 1979. (from Hawkes and Villota, 1989a).
The degradation of folic acid and its derivatives due to oxygen is well documented, although our understanding of the kinetic mechanisms involved is limited. Ruddick et al. (1980) reported that the degradation of 5-methyltetrahydrofolate (5-methyl THF) in phosphate buffer pH 7.3 initially followed pseudo-first-order reaction kinetics, but followed a second-order reaction with limited oxygen supply. Similar findings were reported on the methyl derivative in pH 7.0 phosphate buffer under simulated UHT heating conditions in the presence of controlled oxygen concentrations (Viberg et al., 1997). Day and Gregory (1983) have also reported that for folic acid and 5-methyl THF, the reaction was a second-order for the case of phosphate buffer at pH 7.0. Thermal degradation of food (spinach and green bean purees) and model systems as a function of oxygen concentration (0 or 40 kPa at 45°C–85°C, 3–4 hrs.) were evaluated by Delchier et al. (2014). They found that vegetable purees (~70%–75% 5-methyl THF) were stable in the absence of oxygen, but had significant degradation in the presence of oxygen; total folic acid showed a rapid decrease in concentration, followed by a leveling off due to stability of the formyl derivatives and presence of other minor components (e.g., THF, PteGlu, 10-CHO-PteGlu). It appeared that neither first- or second-order kinetics were followed when monitoring total folate over the entire time period, but seemed to follow first-order for 5-methylTHF degradation when monitored individually. It is clear that multiple competing component interactions and mechanisms are occurring and important to consider. Liu et al. (2012) found first-order degradation kinetics of buffered solutions of L-5-methylTHF (calcium salt) in an oxygen atmosphere and demonstrated an increasing protective effect upon addition of sodium ascorbate at increasing concentration levels. Also reported was a protective effect on the folate when added to skim or soy milk when exposed to similar conditions. Matrix composition as with the structural components of biological materials will always be important factors to consider when developing predictive models. With the advent of high pressure processing, Nguyen et al. (2003) reported kinetics of folic acid and 5-methyltetrahydrofolic acid degradation as affected by the combined treatment of temperature and pressure. This is discussed further in a separate section on the effect of high pressure on quality of foods (Section 3.4.1).
For the particular case of folate degradation, an added problem corresponds to the methodology by which folates are determined. At the time of the first edition of this chapter, it was pointed out that since microbiological tests were more widely accepted because of their ability to monitor the bioavailability of the different folates, less valid kinetic information has become available for the stability of these individual vitamers. Unfortunately, over the past decade, not much has changed in that respect. Rader et al. (2000) point out in a discussion on compliance for mandatory folic acid fortification of enriched cereal grain products in the U.S. that a more accurate methodology for free folic acid is needed over traditional microbiological assays. This concern is targeted particularly for distinguishing between specific forms of folate and total versus free folates. The need for better methodology impacts not only health concerns and proper nutritional labeling, but also costs and problems associated with over fortification of food products. It should be stressed that from the point of view of kinetics, the specificity and accuracy of the assay procedure is of critical importance to mathematically describe and understand the mechanisms of deterioration involved in the reaction. Moreover, the fact that free and bound folates have different stability, accurate techniques to monitor both are required. Unfortunately, a great deal of technical work is still needed to measure folates in food systems using selective and accurate techniques such as HPLC-MS. Release of the bound folates also needs to be properly controlled. Current methods for the measurement of bound folates have not yet reached the level of development needed to use the information in kinetic studies. Some more recent studies have shown some progress in the methodology in folate analysis through a stable isotope liquid chromatography-mass spectrometric (LC-MS) method for the quantitation of folic acid and 5-methyltetrahydrofolic acid in food systems (Pawlosky and Flanagan, 2001; Thomas et al., 2003; and Doherty and Beecher, 2003).
In summary, although some information is available for the stability and kinetics of folates as reported in Table 3.3, a better understanding of the mechanisms taking place in food systems is still needed.
Pantothenic acid (or the salt form, pantothenate), D (+)-N-(2,4-dihydroxy-3,3-dimethylbutyryl)-β-alanine, is a member of the B-complex vitamins, also referred to as vitamin B5, “chick antidermatitis factor”, or “yeast growth factor”. It is ubiquitously present in almost all plant and animal tissue and is an essential precursor for the biosynthesis of coenzyme A. The biochemistry of pantothenic acid has been recently reviewed (Miller and Rucker, 2012; Gonzalez-Lopez et al., 2016). Prevalent sources of pantothenic acid include chicken, lean beef, potatoes, oat cereals, tomatoes, eggs, broccoli, whole grains (Rucker and Bauerly, 2012), liver, kidney, queen bee royal jelly, rice bran, peanuts, and peanut butter (Merck, 2001; Kelly, 2011). Only the natural dextrorotary form has vitamin activity. Pantothenic acid is most stable in the pH range 4–7. It undergoes alkaline hydrolysis to yield pantoic acid and β-alanine (Frost, 1943), or γ-lactone and pantoic acid under acid hydrolysis. In its acid form, it is present as a water soluble viscous yellow oil, and in its salt form as calcium pantothenate, it is a colorless crystalline substance. This vitamin has also been reported to be susceptible to thermal decomposition. Frost and McIntire (1944) determined that hydrolysis of pantothenic acid in the temperature range 10–100°C and in the pH range 3.7–4.0 followed first-order kinetics. Hamm and Lund (1978) working with buffer systems and meat and pea purees indicated that pantothenic acid was more stable in food products than in model systems, thus clearly indicating that the stability of this vitamin improved due to the presence of other compounds in food products. The degradation appeared to follow first-order kinetics (Table 3.3). The authors also indicated that for the systems studied, the vitamin was quite heat stable, contrary to other results reported in the literature indicating vitamin instability during processing (Schroeder, 1971). Cheng and Eitenmiller (1988) also reported that steam blanching, water blanching, canning, and frozen storage caused losses of pantothenic acid in spinach and broccoli to a different degree. Water blanching, in particular, resulted in large losses of pantothenic acid in both spinach and broccoli. More recently, Muhamed et al. (2015) reported appreciable amounts of pantothenic acid in tropical Averrhoa bilimbi fruits, along with nicotinic acid and catechin, recoverable for use as food supplements. The kinetics of these three components were investigated at temperatures ranging from 90°C to 120°C, as quantified by HPLC analysis, and found to follow first-order kinetics (Table 3.3); it was indicated that of those three components, pantothenic acid had the highest sensitivity to temperature change, based on their energy of activation. First-order kinetics for pantothenic acid degradation was also demonstrated by Gutzeit et al. (2007b) during storage of Sea Buckthorn juice stored at 25°C–40°C, resulting in a 18% loss after 7 days at ambient temperature. In general, however, it appears that due to problems associated with assay procedures, kinetic data are limited and inconclusive. Some of the pantothenic acid analogues include panthenol (pantothenol), pantethine (two pantetheine molecules linked by a disulfide bridge), and a calcium salt (Ca-pantothenate) which is commercially available and commonly used in extruded feeds for animals (chemical structures presented in Figure 3.18).
Figure 3.18 Chemical structures of pantothenic acid and some of its analogs, pantothenol, calcium pantothenate, and pantethine. (adapted from Rucker and Bauerly, 2012).
Biotin, also known as vitamin B7 (formerly vitamin H, “egg white injury factor”, coenzyme R) and chemically as hexahydro-2-oxo-1-H-thiene[3,4-d]imidazole-4-pentanoic acid, is a highly biologically active growth factor found in all living cells. The structure of biotin consists of fused imidazole and tetrahydrothiophene rings and a carboxyl-containing side chain. In the case of the biotin derivative, oxybiotin, the sulfur of the tetrahydrothiophene ring is replaced by oxygen, making it a tetrahydrofuran ring, and acts as a substitute for biotin in vivo (Figure 3.19). Biotin plays an essential role as a coenzyme in carboxylation, trancarboxylation, and decarboxylation reactions and functions in catalyzing critical steps in metabolism of fatty acids, amino acids, and in gluconeogenesis; it is also reported to influence regulation of gene expression (Zempleni et al., 2012). Its deficiency has been found to result in dermatitis and perosis in chicks and poults, basically reducing the activity of biotin-dependent enzymes (Dobson, 1970); other deficiencies of biotin in various animals, including mice, have shown to result in potential birth defects (Mock et al., 2003). Although there have not been many reports on deficiencies in humans, lack of biotin has been found to cause thinning of hair, skin rashes, lethargy, and depression. Zempleni and Mock (1999) and more recently Mock (2017) have reviewed biotin biochemistry from a nutritional requirement perspective as well as a potential therapeutic agent. Currently, there is no official USDA listing of biotin contents in foods; however, based on reports from other major population areas, the average intake of biotin has been estimated around 35–70 μg/day (Zempleni and Mock, 1999). Watanabe et al. (2014) have published tables of biotin contents of selected food items based on common foods in Japan, estimating biotin consumption to be about 50 μg/day for adults; they suggest this data could serve as a basis for developing more official required levels at a global level.
Figure 3.19 Some chemical structures of biotin and derivatives (from Scheiner, 1985).
Some of the richest sources of biotin are beef liver, yeast, peanuts, kidney, chocolate, egg yolk, soybeans, mushrooms; it can also be synthesized by bacteria in the gut, although it is unclear as to how much can be absorbed (Bhagavan and Ha, 2015). Suri and Tanumihardjo (2016) have reported biotin contents in whole-grain maize flour to be 7.3 and 1.4 μg/100 g in degermed maize flour, based on microbiological assays, indicating a reasonable source of biotin. Biotin occurs naturally as the d-isomer and is present as in a conjugated or bound form to proteins and polypeptides. In fact, raw egg whites can produce a biotin deficiency due to the glycoprotein, avidin, which forms a complex with biotin, rendering it unavailable. However, since egg white is heat labile, prolonged heating of egg white denatures avidin and destroys its biotin-binding capacity. The d-isomer has about twice the biological activity of the d,l-isomer, where the l-isomer is biologically inactive. Biotin is reported as stable to heat, oxygen, in moderately acid (pH 4.0) and neutral solutions up to pH 9.0, but less stable under alkaline conditions (Merck, 2001; Marcus, 2015). Hoppner and Lampi (1993) reported on relative losses of biotin and pantothenic acid in various legumes and found biotin to be significantly more stable. After 24 hours soaking, followed by conventional cooking for 20 minutes, they found 90% retention of biotin compared to only 44% pantothenic acid, but no mention was made of their kinetics of degradation. It is expected that the cooking and processing of foods can convert biotin to the oxidized forms. It has been reported that the different biotin derivatives such as desthiobiotin, oxybiotin, biotinol, norbiotin, biotin sulfoxide, and biotin sulphone have different biological activities. However, limited information is available on the stability of biotin and its derivatives. It was not until 1966 that biotin became more important commercially, particularly in fortification of feeds for livestock such as poultry and swine as well as pets. Watson and Marsh (2001) developed a patent for a biotin supplement for animals to withstand extrusion processing. Several reviews on the biochemistry of biotin have been published (Gyorgy and Langer, 1968; Zempleni et al., 2012; Mock, 2017), but few pertaining to stability in processing. Although advances have been made on the analysis of this vitamin (Sim et al., 2016), most efforts are working with pure vitamins, and not accounting for the difficulties of extraction from foods. Most analyses to date still use microbiological assays which lack chemical specificity, as well as producing confounding results due to the fact most biotin in foods is bound to protein. Avidin and Streptavidin-binding assays have also been used, but, again, anomalies may occur since biotin derivatives with similar structure may interfere with proper levels of true biotin being reported. Watanabe (2015) also points out critical aspects of developing more global standardized tables; researchers will need to be cognizant of consistency of methodology, sampling techniques, and documentation of different types of processing to which various food types may be subjected. It is clear that quantitative assessments of biotin still present a challenge, and that more work in this area is needed. Understandably, this contributes to the lack of information on stability data during processing of foods.
Vitamin A is generally classified into two ma in groups possessing biological activity: (a) C20 unsaturated hydrocarbons including retinol and its derivatives from animal origin and (b) C40 unsaturated hydrocarbons including carotene and a number of other provitamin A carotenoids of plant origin. Vitamin A is a generic descriptor for all β-ionone derivatives with the biological activity of all-trans-retinol (also referred to as vitamin A alcohol or vitamin A1). Provitamin A carotenoid is a generic descriptor for all carotenoids with the qualitative activity of β-carotene. Natural forms of vitamin A predominantly occur in the more stable form of all-trans-retinyl esters, along with small levels of 13-cis-retinol as found in fish livers. Other natural retinyl derivatives present include esters of 3-dehydroretinol (vitamin A2, with ~40% retinol activity) and retinal (vitamin A aldehyde with ~90% retinol activity). Commercially available forms of synthetic vitamin A may be found as either retinol acetate or palmitate and can be supplied in crystalline form or as concentrates in oil, emulsions, or in encapsulated forms. Similarly, different forms of provitamin A carotenoids are available. Some of the carotenoids with significant provitamin A activity include β-carotene (100%); 3,4-dehydro-β-carotene (75%); β-apo-8′-carotenal (72%); β-apo-12′-carotenal (120%); 3-hydroxy-β-carotene (50%–60%); α-carotene (50%–54%); and γ-carotene (42%–50%) (Bauernfeind, 1972). Because of the wide variety of forms of vitamin A and provitamin A carotenoids, labeling requirements report total vitamin A activity in terms of “retinol equivalents” (RE), where one RE is equivalent to 1 µg retinol, 6 µg β-carotene, and 12 µg other provitamin carotenoids. In terms of international units (IU), one RE = 3.33 IU retinol or 10 IU β-carotene (NRC, 1980).
A variety of pathways have been proposed to describe the destruction or autooxidation of carotenoids, depending on the process conditions, the presence of light, the presence of oxygen, and the composition of the system including peroxidizing lipids or enzymatic activity. A summary of the most important mechanisms is presented in Figure 3.20. It appears that at high temperatures, the destruction of carotenoids results in fragmentation including the formation of aromatic compounds. In the absence of oxygen, trans–cis isomerization seems to be one of the most important mechanisms of deterioration. Light catalyzed oxidation appears to result primarily in the formation of mutachrome. In general, the degradation of carotenoids has been considered to be an autooxidation reaction involving the formation of free radicals, thus giving origin to a propagation reaction and finally, a termination stage. A variety of approaches have been taken to describe the kinetics of carotenoid degradation. For instance, Ramakrisnan and Francis (1979a), using a microcrystalline cellulose/starch model system, stated that since this is an autooxidative process, the two principal reactants are oxygen and carotenoids, and since oxygen is in excess, the reaction is expected to follow first-order reaction kinetics. Other authors such as Chou and Breene (1972), Baloch et al. (1977c), Stefanovich and Karel (1982), Goldman et al. (1983), and Pesek and Warthesen (1987, 1988) have also reported that a first-order reaction would describe within limits, the degradation of carotenoids in model systems. On the other hand, authors such as Quackenbush (1963) working with corn, Baloch et al. (1977a,b) working with carrots, and Stefanovich and Karel (1982) working with butternut squash, sweet potato, and yellow corn, also concluded that first-order kinetics could describe the degradation of carotenoids, although the model did not take into account an induction period. Haralampu and Karel (1983) working with dehydrated sweet potato, indicated that the degradation of β-carotene was described with the use of pseudo-first-order reaction kinetics. Taking into consideration that carotenoid degradation is a chain reaction, other authors such as Alekseev et al. (1968), Finkel’shtein et al. (1974), Gagarina et al. (1970), Goldman et al. (1983), Stefanovich and Karel (1982), and Smith-Molina (1983) have applied a simplified free radical recombination model to describe the autooxidation of carotenoids. Finkel’shtein et al. (1973) indicated that the autooxidation of β-carotene followed the same basic trends regardless of the conditions, namely, (a) an induction period, (b) an acceleration period, (c) a stationary induction period, and (d) a retardation period.
Figure 3.20 Some mechanisms of β-carotene degradation. (1) Seely and Myer, 1971; (2i) Seely and Myer, 1971; (2ii) Pesek and Warthesen, 1988; (3) Seely and Myer, 1971; (4) Walter et al., 1970; (5) Sweeney and Marsh, 1971, 1970; (6i) Ishiwatari, 1980; Mader, 1964; Day and Erdman, 1963; (6ii) Ishiwatari, 1980; (6iii) Schreir et al., 1979; (6iv) Onyewu et al., 1982; (6v) Ouyang et al., 1980; (7) Chen et al., 1995.
Limited information is available with regard to the effect of initial concentration on the degradation of carotenoids. Budowski and Bondi (1960) working with model systems, indicated that the higher the initial concentration of carotenoids, the shorter the induction period, with an associated faster reaction rate. Gagarina et al. (1970) also indicated that when working with β-carotene in chloroform, the time required for complete consumption of the carotene was shorter upon an increase in the initial concentration. Similarly, Stefanovich and Karel (1982), working with β-carotene in a model system, observed that the kinetics of degradation were dependent on the initial concentration. The authors indicated that the dependence was related to the thickness of the carotene layer since the diffusion of oxygen becomes a limiting factor in the oxidation reaction. Smith-Molina (1983) indicated that in liquid systems the rate of degradation of carotenoids increased with an increase in the initial concentration. The high mobility of the reactants including free radicals was assumed to be the reason for the observed trends. The author also reported that when taking into consideration the history of the sample, systems where degradation of carotenoids had proceeded to a larger extent were also more reactive. Similarly, Goldman et al. (1983) observed that carotene degradation was strongly affected by the presence of free-radical initiators.
Although a certain amount of information is available for the kinetics of degradation of carotenoids, limited work has been done in trying to follow the most important mechanisms of deterioration on the degradation of carotenoids in food systems (Table 3.3). Moreover, analytical techniques have been limited in their ability to monitor isomerization of the carotenoids, which is expected to be one of the most critical changes occurring as a result of processing.
Working at high temperatures, Wilkinson et al. (1981) indicated that the destruction of vitamin A in beef liver puree, measured as trans-retinol, followed a first-order reaction. Wilkinson et al. (1982) indicated that increased concentrations of copper increased the losses of vitamin A, whereas increased pH (5.6–7.0) resulted in a decrease. The authors appeared to believe that changes in the copper concentration modified the mechanism by which the vitamin was lost.
Chen et al. (1995) reported effects of different processing techniques on stability of various carotenoids in carrot juice including α-carotene, β-carotene, and lutein. Depletion and/or conversion of the trans-isomeric forms to various cis-forms of the vitamers were monitored by HPLC. It was reported that acidification of fresh carrot juice to pH 4.0, followed by heating to 105°C/25 sec showed little change. HTST heating at 110°C/30 sec and 120°C/30 sec showed progressively higher levels of loss of the trans-carotenoids with the predominant cis-isomers being 13-cis-β-carotene, followed by 13-cis-lutein and 15-cis-α-carotene. Retort processing (121°C/30 min) showed the highest level of carotenoid destruction with formation of 13, 15-di-cis-β-carotene. Color changes as monitored by Lab-values showed decreases that paralleled losses of the trans-forms and increase in cis-forms. Lin and Chen (2005) indicated that in tomato juice during storage, both temperature and light would influence the proportion of isomers that predominate over time (4–35°C/12 wks). For instance, they found that all-trans-β-carotene degraded to di-cis-, 9-cis-, and 13-cis-β-carotene isomers after storage under light depending on temperature. In the absence of light, degradation products included 5-cis-, 9-cis-, and 13-cis-β-carotene, again, depending on temperature.
In food systems the effect of water on carotene oxidation appears to be dependent on composition (Kanner et al. 1978). As reported by Arya et al. (1979) and Maloney et al. (1966) an increase in water content could mobilize the pro-oxidant factors in the matrix or expose new sites in the matrix resulting in accelerated oxidation. On the other hand, Haralampu and Karel (1983) indicated that for the case of sweet potato flour, the degradation of β-carotene was inversely proportional to the water activity. With respect to the photosensitized oxidation of β-carotene, mutachrome has been identified to be the most important oxidation product, although other compounds such as aurochrome and a number of compounds absorbing in the violet and near ultraviolet region have also been detected. The 5,6-monoepoxide was not detected in significant amounts, although this compound is unstable and can be converted into mutachrome by acid traces and catalysts (Seely and Meyer, 1971). The authors determined that 5,6-monoepoxide was not the first product of photochemical oxidation. Pesek and Warthesen (1988) working with model dispersions indicated that the photodegradation of β-carotene followed a first-order reaction that was affected by temperature; the physical state of the sample, frozen vs. liquid; and the microenvironment. The authors also indicated that the presence of cis-isomers and the rate of their formation was larger than that of their degradation. Moreover, it had been previously shown by Zechmeister (1944) that the cis-isomers may convert back to the all-trans form, which is more stable, or undergo further degradation. Lemmens et al. (2011) have discussed the overall isomerization of all-trans-β-carotene and subsequent formation of different cis-isomers (9-, 13-, 15-) during thermal processing of carrot puree (80–150°C). They proposed a fractional conversion model which considers the interconversion reactions between all-trans-β-carotene and its cis-isomers until an equilibrium state is reached during prolonged heating. This would be plausible due to a protective effect of the carrot structural matrix; hence, an important factor when developing models for real food systems.
Heat stability studies of α-carotene and β-carotene indicate that β-carotene is about 1.9 times more susceptible to heat damage than α-carotene during normal blanching and cooking operations (Baloch et al. 1977a). With regard to cooking losses, Sweeney and March (1971), indicated that heating promotes the cis-trans isomerization of carotenoids in vegetables, with an increase of the cis isomers. In general, literature reports clearly indicate the instability of carotenoids at high temperatures such as those encountered in canning and drying operations, particularly in high temperature-long time type processes, while freezing and low temperature processing normally results in much lower losses.
Of critical importance in processing, particularly fruits and vegetables, would be the isomerization of all-trans-β-carotene sensitized by chlorophylls. As reported by O’Neil and Schwartz, (1995), the photoisomerization of β-carotene sensitized by chlorophyll will result in 9-, 13-, and 15-cis-β-carotene primarily, with a higher ratio of the 9-cis-isomer.
Most past studies on degradation of β-carotene as a function of temperature have been carried out with relatively static conditions at individual temperatures, without necessarily considering the dynamics of the specific industrial process of concern. González-Reza et al. (2015) studied degradation kinetics of β-carotene nanocapsules as used in a matrix subjected to a scraped surface heat exchanger. The process variables considered, other than temperature, were volumet ric flow (2.4 × 10−6–4.8 × 10−6 m3/sec), steam pressure (49–147 kPa), and rotor speed (10.4–31.2/sec); dispersion matrix composition was a 0.5 g carboxymethyl cellulose (CMC)/100 g water incorporating the equivalency of 70 μg/ml of β-carotene in nanocapsules. Using a traditional Arrhenius relationship for degradation of the active component to determine rate constants and Ea’s, the authors developed a fractional factorial RSM (response surface methodology) design model to factor in the influences of processing variables. They found the most influencing of the variables towards β-carotene degradation were steam pressure and volumetric flow rate, with optimal values for maximizing retention at 98 kPa and 4.4 × 10−6 m3/sec, respectively and a rotor speed of 38.29/sec. Optimum values for rate constant were reported at 0.049 min−1 and Ea at 171.5 kJ/mol (41 kcal/mol), with a total loss of β-carotene at 6.93%.
Vitamin D has been closely scrutinized over the past decades due to many reoccurring incidences of its hypovitaminosis worldwide (Kumar et al., 2009; Edmonds, 2010; Vierucci et al., 2013; Cashman et al, 2016). Vitamin D is well recognized for its role in growth and bone health. Originally in the early 1920s, the term vitamin D was given to the active component present in cod liver oil, which could cure or prevent rickets, a disease resulting in weakness and deformation of the bones. Later, the introduction of vitamin D fortified milk in the 1930s in the U.S. essentially eliminated rickets, as caused by a vitamin D deficiency. However, emerging scientific research indicates more far-reaching health benefits of vitamin D; other symptoms associated with its deficiency have been identified including increased risk of cancer, heart disease, infection, multiple sclerosis, diabetes, rheumatoid arthritis, and depression in the elderly (Mazahery and von Hurst, 2015; Lips, 2010; Milaneschi et al., 2010). Along with the fact that the incidence of rickets seems to be reemerging, due to lack of exposure to the sun in certain winter climates along with increased usage of sunscreen in warm climates (Lamberg-Allardt, 2006; Engelsen, 2010; Lips, 2010) in combination with a lack of general foods with high vitamin D content, recommendations are being made to increase the minimum required daily dosage of vitamin D from its current minimum (U.S.) of 400 IU to 1000 IU/day, particularly for the elderly. In 2016, the U.S. Food and Drug Administration announced that it would allow for manufacturers of milk and plant-based milk and yogurt alternatives to add more vitamin D to their products; to further emphasize the importance of this vitamin, starting in (2020), it will be a nutrient required to be declared on the new U.S. Nutrition Facts label (IDFA, 2016). Other products looking more seriously at being considered a good source of vitamin D fortification include bread products (D3 [Nikooyeh et al, 2016] and orange juice (D2 and D3 [Biancuzzo et al., 2010]). Some investigators have also warned of potential differences between the bioavailability of these two vitamers (Itkonen et al, 2016; Tripkovic et al., 2012), despite prior claims of biological equivalency. In fact, studies have been shown in vivo that vitamin D3 is significantly more potent than D2 as monitored by serum levels of the active 25-hydroxyvitamin D metabolite (Heaney et al., 2011; Aramas et al., 2004); this impact can also be influenced by available calcium both in fortified products and in serum levels. There has also been research on synergistic reactions between some forms of vitamin D and vitamin K derivatives in enhancing the maintenance of bone health (Torbergsen et al., 2015). This makes it even more imperative to definitively identify the appropriate derivatives to ensure proper maximum biological availability and stability through various types of processing. Quantitative and analytical data collection for relevant vitamin D derivatives and their rates of degradation in associated products will be critical.
The most important forms of vitamin D are D2 (ergocalciferol) and D3 (cholecalciferol). Vitamin D2, generally sourced from plant materials such as yeast or fungi, is formed by ultraviolet irradiation of the provitamin ergosterol. Similarly, D3, sourced from animal products such as lanolin or fish oil, is formed from the provitamin 7-dehydrocholesterol. The following are also considered to be provitamin D compounds: 22, 23-dehydroergosterol, 7-dehydro-sitosterol, 7-dehydrostigmasterol, and 7-dehydro-campesterol. The D provitamins do not have any vitamin activity unless the B ring is opened between carbons 9 and 10, and a double bond is formed between carbons 10 and 19 forming the 3(beta)-hydroxy-9, 10-seco-5, 7,10(19)-triene derivative (Figure 3.21). Limited information is available on the stability of the provitamin D compounds and the active derivatives, although this vitamin has been reported to be susceptible to oxygen and light. Photochemical transformations of provitamin D give origin to the anti-9:10 isomers, while thermal isomerization yields the syn-9:10 isomers, procalciferol and isopyrocalciferol (Sebrell and Harris, 1971). Yamada et al. (1983) indicated that vitamin D undergoes 1,4-cycloaddition and ene-type reactions with singlet oxygen, generating: a) two carbon (6) epimers of 6,19-epidioxyvitamin D (55%–65% yields) and b) two carbon (6) epimers of the Δ4,7,10(19) 6-hydroperoxide (15%–25% yields). Figure 3.21 presents some of the reaction pathways for Vitamin D as affected by light and heat. With regard to kinetic information, our understanding of the stability of vitamin and provitamin D in food systems is almost non-existent. Li and Min (1998), however, reported first-order rate constants (2 phases) for the degradation of vitamin D2 in model systems as a function of riboflavin concentration in the presence of light. The authors indicated riboflavin acted as a photosensitizer and accelerated the oxidation of vitamin D2 by singlet oxygen under light , but had no effect on stability in the absence of light. Further studies showed that the presence of carotenoids could quench singlet oxygen activity and provide stability to vitamin D2 in model systems. Li et al. (2000) reported quenching rate constants for retinol, retinyl acetate, fucoxanthin, and β-carotene (1.22 × 108, 5.98 × 108, 1.78 × 109, 5.00 × 109 M−1s−1, respectively) and indicated that with increasing number of carotenoid double bonds (5, 6, 10, 11, respectively), the quenching rate constant of carotenoid increased. Saffert et al. (2009) studied the effect of package light transmittance on vitamin content (D3, A, and B2) in fortified UHT low and whole fat and pasteurized whole milk; they found major losses of all vitamins after 12 weeks storage at 23°C in clear PET bottles (65% loss of D3, >90% loss of A and 100% loss of B2). By using a high density pigmented PET, it minimized losses to about 20% of the vitamin D, but still had significant losses of the other vitamins A and B2, which were clearly less stable to light; some stability data was calculated and presented in Table 3.3.
Figure 3.21 Some reaction pathways as affected by light or heat for the D vitamers. (adapted from Miller and Norman, 1984 and Li et al., 2000).
Although little actual kinetic data is available for degradation of vitamin D in food systems, with increased awareness for the need of fortification of vitamin D, several authors have reported on general stability during different processes. For instance, Hanson and Metzger (2010) have evaluated vitamin D3 fortification at levels of 100–250 IU/serving in HTST-processed 2% fat milk, UHT 2% fat chocolate milk, and low-fat strawberry yogurt and found no significant vitamin D3 losses during processing or normal shelf-life and no impact on flavor at elevated vitamin D levels; vitamin analysis was carried out using a pre-extraction/saponification step, followed by HPLC. Kazmi et al. (2007) investigated Vitamin D3 fortification by means of two methods, one with pre-dissolved crystalline D3 and the other emulsified D3 in cheddar cheese, yogurt, and ice cream. They found that during three month storage in cheese, the emulsified form was the more stable form; however, in yogurt and ice cream, either form retained suitable retention over the expected life time of the products. Wagner et al. (2008) found similar stability with vitamin D3 incorporated in hard cheeses at different stages of the process, including processing, ripening for 1 year at 3–8°C, or after thermal treatment at 232°C for 5 min.; any losses of vitamin D were accounted for by the amount entrained in the whey. Ganeson et al. (2011) also found Cheddar cheese to be a suitable vehicle for vitamin D3 fortification (emulsion format) with 9 months storage and 90% retention of vitamin D3 and no flavor impact up to 400 IU/serving. Jakobsen and Knuthsen (2014) investigated retention of vitamin D3 in different products such as eggs and margarine as well as both vitamins D3 and D2 in bread. They found stability of vitamin D3 was dependent upon the type of process used. In the case of heating eggs and margarine in an oven at “normal” baking temperatures, retention was at only 39%–45%; however, at frying temperatures, retention was at 82%–84%, similarly for boiled eggs. Retention in bread during baking showed D3 retention at 69%–85% and D2 at 73%–89%; this was also dependent upon the type of bread formula being used. Overall indications showed potential for fortification with vitamin D3 or D2, but optimization of cooking procedures should be taken into account. Success in fortification with vitamin D, of any form, will depend on reliable, repeatable analyses, which have been a challenge, particularly when it comes to extraction from food systems. Rybakova et al. (2008) have reviewed various vitamin D methods and determined HPLC is most likely the method of choice for reliability in a quality control environment.
Tocopherols, or compounds with vitamin E activity, are methyl-substituted hydroxychromans with an isoprenoid side chain. Overall, there are eight different forms of vitamin E identified and are composed of two homologous series: a) four tocopherols with a saturated side chain and b) four tocotrienols with a side chain unsaturated between carbons 3′ and 4′, 7′ and 8′, and 11′ and 12′ (Parrish, 1980), each of which is characterized by the number and position of methyl groups on the chromanol ring (i.e., trimethyl [α-], dimethyl [β- or γ-], or monomethyl [δ-form]), as illustrated in Figure 3.22. Vitamin E is synthesized by plants and predominantly found in plant oils; α-tocopherol is usually found in leaves and other green parts of the plant associated with the chloroplasts; whereas, β-, γ-, δ-vitamers generally occur outside those regions. Wheat germ, olive, and sunflower oils are rich sources of α-tocopherol, while corn and soy oils are rich in γ-tocopherol. Some plant tissues (germ fractions) contain tocotrienols, often in an esterified form, unlike the tocopherols which are present in the free alcohol form. Bioavailability of the E-vitamers has been shown to be dependent upon general fat intake, not only because of the inherent vitamin E content of the consumed food, but when taking vitamin E supplements, the presence of fat aids absorption in vivo (Hayes et al., 2001). It is considered that α-tocopherol is the compound with the most significant biological activity of all the E-vitamers, although it is also the least resistant to oxidation; since tocopherols are mono-ethers of a hydroquinone, they can be easily oxidized. Currently, α-tocopherol is the only form that has been established as being maintained in human plasma and consequently is the only one officially recognized as being a contributor to the RDA (FNB, 2000). In itself, chemically synthesized α-tocopherol can exist as a racemic mixture o f eight stereoisomers (designated as all-rac-α-tocopherol), however, not all have the same biological activity, and only half of those are officially recognized as contributors including the naturally occurring RRR-α-tocopherol and three other 2R-stereoisomeric forms (formerly referred to as dl-α-tocopherol). This, of course, can create further complications in proper calculation of actual levels to be labeled correctly on food packaging. Currently, the IU of vitamin E equals 1 mg all-rac-α-tocopheryl acetate, 0.67 mg RRR-α-tocopherol, or 0.74 mg RRR-α-tocopheryl acetate (FNB, 2000; Trabor, 2007). Some relative biological activities of the various α, β, γ, δ-forms of vitamin E, as based on animal studies, have been reported; it shows that non-α-tocopherols may have less than 20% activity of α-tocopherol, and yet the γ-form is the most prevalent in diets (Combs, 2008). However, suggestions have been made that γ-tocopherol may have greater impact than α-tocopherol in the prevention of Alzheimer’s and cardiovascular diseases (Usoro and Mousa, 2010 and Cordero et al., 2010, respectively), a factor to be considered in the importance of the mechanistic breakdown analysis of vitamin E. Supplements are often in the form of α-tocopherol esters such as α-tocopherol-acetate, -succinate, or -nicotinate; these all have greater stability in terms of shelf-life than naturally occurring α-tocopherol and can be readily hydrolyzed in the gut and absorbed as α-tocopherol (Cheeseman et el. 1995). As a natural antioxidant, tocopherols have been a topic of eminent interest in terms of biological activity; its functions have often been considered widespread such as has been implicated in helping reduce a variety of disease processes, such as deteriorating immune defenses, cataracts, and lipid peroxidation occurring in LDL during atherogenesis, a major cause of coronary heart disease (Hayes et al., 2001). At present there are no confirmatory studies for absolute corroboration of these claims, although it has been suggested that that in special circumstances under controlled population sets, there have been cases of improvement (Vardi et al., 2013). Comprehensive summaries of the most influential factors on the stability of tocopherols and reviews on their biochemical significance have been presented by Bauernfeind (1977, 1980) and Traber (2007), respectively.
Figure 3.22 Chemical structures of vitamin E indicating methyl group positioning for α-, β-, γ-, δ-forms and the stereoisomeric chiral centers at the 2, 4′, 8′ positions (adapted from Merck, 2001 and Trabor, 2007).
Storage studies carried out by Widicus et al. (1980) indicated that the degradation of α-tocopherol followed a first-order reaction in model systems not containing fat. Although, the presence of an autooxidation mechanism was not observed, the involvement of oxygen in the degradation of this compound was determined.
A number of studies have indicated that α-tocopherol is highly susceptible to degradation depending on moisture content, temperature, light, alkali, and the presence of metal ions such as iron and copper. Moreover, tocopherols have been found to be more unstable in peroxidizing systems. One of the main decomposition products of oxidized tocopherols in vivo is α-tocopherolquinone, although several others have been determined in vitro as well including dimers, trimers, dihydroxy compounds, and other quinones (Csallany et al., 1970; Csallany and Draper, 1963; Skinner and Parkhurst, 1964). The chemistry, antioxidant properties, and decomposition products of tocopherols and tocotrienols and their differentiating factors have been reviewed (Kamal-Eldin and Appelqvist, 1996). Some of the α-tocopherol structures and some of their pathways for their degradation are illustrated in Figure 3.23.
Figure 3.23 Some mechanisms of α-tocopherol degradation. (1) John et al., 1939; John and Emte, 1941; (2) Frampton et al., 1960, 1954; (3) Knapp and Tappel, 1961; (4) Knapp and Tappel, 1961; (5) Skinner and Alaupovic, 1963; Nelan and Robeson, 1962; (6) Dürckheimer and Cohen, 1962; Schnudel et al., 1972; (7) Schnudel et al., 1972; (8) Nelan and Robeson, 1962; (9) Csallany and Draper, 1963.
Due to the high instability of this vitamin, processing in particular has been reported to be detrimental to the stability of tocopherols. For instance, Thomas and Calloway (1961) indicated severe α-tocopherol losses (41%–65%) in various meat products as a result of canning. Livingston et al. (1968) reported losses of α-tocopherol ranging from 5% to 33% during the drying of alfalfa. Avocados are known as a good source of vitamin E (2 mg/100 mg fresh produce) and have become a subject for evaluation. Recent studies have shown that ultrasonic application for preservation (power densities 1000–5000 W/L at 23°C and 40°C) decreases natural vitamin E content of the fruit, but addition of the bioavailable α-tocopherol acetate holds up to the process more e fficiently, and thus can replace losses of natural vitamin E during such a process (Fernandes et al., 2016). It is speculated that the presence of H2O2 during the process may have initiated oxidative reactions with the naturally occurring antioxidant, α-tocopherol.
Widicus et al. (1980) indicated that for a non-lipid containing model system the degradation of α-tocopherol was directly related to the water activity, thus suggesting that the system was highly dependent on the rate of diffusion of the reactants. The reaction followed first-order kinetics. Similarly, Jensen (1969) reported higher stabilities of α-tocopherol during the storage of seaweed meal at lower moisture contents for the range 10%–25%. Frias and Vidal-Valverde (2001) reported on the stability of α-, β-, and δ-tocopherols, vitamin A, and thiamine during storage of enteral feeding formulas. Analysis of their data is presented in Table 3.3, along with some of the most relevant information on vitamin E stability in food systems.
Considerable losses of tocopherols have been reported during the storage of oils, as influenced by temperature, time, and the presence of other antioxidants. Since tocopherols are highly susceptible to free radical oxidation, it is obvious that their stability is influenced by the levels of lipid oxidation taking place in a food system. It has also been found that the relative stabilities of natural tocopherols may vary according to the biological source. For instance, Chow and Draper (1974) found that both vitamin E oxidation and peroxide formation occurred more rapidly in corn oil than in soybean oil. In the case of deep-fat frying of potato slices in palm, canola, and a 1:1 blend of oils (170°C–190°C), it was reported that kinetic deterioration of various vitamin E analogues followed an Arrhenius relationship using a fractional order of kinetics greater than one [1.4–1.8], (Mba et al., 2017). By observation of their data, it appears that the γ-forms are less sensitive to changes in temperature than the α-forms for either the tocopherols or tocotrienols. Choe (2013) subjected sunflower oil to temperatures between 40°C and 80°C, with and without light up to 30 days; the author measured degree of oxidation through peroxide value (POV) and conjugated dienoic acid (CDA) values as well as tocopherol degradation by HPLC. Trends showed greater stability of γ-tocopherol compared with α-tocopherol with respect to both type of light conditions.
With regard to the influence of metal traces, Cort et al. (1978) reported that both α- and γ-tocopherols were degraded by Fe3+ and Cu2+. Chelating compounds such as ascorbic acid and EDTA appeared to inhibit the Cu2+ oxidation, while ascorbic acid prevented the Fe3+ oxidation of tocopherols in alcohol solutions.
Tocopherols have been reported to combine with various proteins and amino acids, thus modifying their stability. The conjugate appears to be a protein-tocopherol linkage without the involvement of lipids (Voth and Miller, 1958). Binding affinities of proteins and free amino acids have shown a similar behavior, whereby an increase in the negative charge resulted in an increase in the binding of tocopherols. Thus, relatively positive amino acids such as lysine, arginine, and histidine do not participate in the binding of the tocopherols or modify the affinity of proteins for binding (Voth and Miller, 1958).
Fortification of foods with Vitamin E has become increasingly more important. Vitamin E is important in human nutrition since it has potent antioxidant activity, thus preventing the damage of cells through the inactivation of free radicals and oxygen species (Diplock, 1994). Due to its antioxidant activity, vitamin supplementation has been found to be effective on pigment and lipid stability in food products such as frozen beef. Lanari et al. (1994) demonstrated through kinetic analysis that vitamin E supplementation stabilized the oxymyoglobin complex by enhancing the deoxymyoglobin oxygenation and by decreasing the oxymyoglobin autoxidation rate. Vitamin E enhanced the pigment and lipid stability of frozen beef, stored in the dark or under constant illumination. Lanari et al. (1993) also indicated the significance of dietary supplementation of Holstein steers with vitamin E in delaying surface discoloration of meat after repeated freeze-thaw cycles and during dark storage or illuminated display. Similarly, Houben et al., 2000 studied the benefits of vitamin E supplementation to the diet of beef bulls on the color stability and lipid oxidation of minced beef. The authors corroborated previous studies on the proposed mechanisms of the vitamin E color stabilizing activity, which calls for indirectly delaying the oxidation of oxymyoglobin via direct inhibition of lipid oxidation. Others have researched introduction of vitamin E through various types of emulsions either as part of lipid-containing food components such as cream cheese or mayonnaise (Schneider et al., 2012) or as nanoemulsions that have potential for food systems as well as pharmaceutical delivery products (Saberi et al., 2013).
Vitamin K is a generic term referring to a group of lipid soluble bicyclic naphthoquinone derivatives with a common 2-methyl-1,4-naphthoquinone ring structure (menadione) and a hydrophobic polyisoprenoid side chain attached at the 3-carbon position of the nucleus; this side chain may vary in length and degree of saturation, with up to 15 units reported (Figure 3.24). It functions as a cofactor (in its reduced form, dehydro-vitamin K [KH2]) for the enzyme, γ-carboxyglutamyl carboxylase, which is required to catalyze the conversion of specific peptide-bound glutamate residues to γ-carboxy-glutamates (Gla). This γ-carboxylation is accompanied by oxidation of (KH2) to vitamin-K-epoxide which is then recycled back to vitamin K, completing this cycle. Although these vitamin K-dependent Gla-proteins have been traditionally known mostly for their importance as blood coagulation factors (e.g., prothrombin) in warm blooded animals, over the past couple of decades, advances in research have found these Gla-proteins to be more diverse in structure and function and present in many different cell and tissue types. Additional areas of human physiology include bone and cartilage health (Bügel, 2003; Torbergsen et al., 2015; Shea et al., 2015), arterial calcification inhibition (Vossen et al., 2015; Dourado Villa et al., 2017), brain and energy metabolism, immune response, and general cellular growth regulation (Vermeer, 2012). Synergistic reactions have also been shown between vitamins K and D in terms of calcium absorption and regulation of calcification (Iwamoto et al., 2005; Shea and Booth, 2007). Several reviews on some of the more recent studies on vitamin K and its biologically significant derivatives further clarify their roles in nutrition, and ongoing research has been published (Shearer et al., 2012; Shearer and Newman, 2014; Shea and Booth, 2016; Schwalfenberg, 2017). Furthering knowledge on elucidating reaction mechanisms relevant to metabolic pathways and identification of the most health relevant K-derivatives has led to reestablishing the importance of vitamin K in the diet and fortification in foods. As evidence of new relevant vitamin K derivatives emerges, further clarification of chemical structures and reaction pathways will evolve; this is important to the food scientist in order to understand what vitamers are the most critical to study for predicting their stability during processing and storage.
Figure 3.24 Some chemical structures of vitamin K and derivatives. (adapted from Berruti, 1985; Daines et al., 2003; Shearer and Newman, 2015; Fujii and Kagechika, 2017).
The most common naturally occurring forms of vitamin K are known as K1 (phylloquinone) and K2 (a group of vitamers known as menaquinones). Phylloquinone, also referred to as 3-phytyl-menadione, has a chemical structure established as 2-methyl-3-phytyl-1, 4-naphthoquinone. K1, having a similar phytyl side chain as chlorophyll, is found in the chloroplasts of plants forming part of the electron transport system in photosynthesis. Most notably, this side chain contains only one double bond at the 2–3 side chain position as compared to those of the K2 group (Figure 3.24). K1 is considered the primary source of vitamin K in the diet; common natural K1 sources are ubiquitously found in green and leafy vegetables and various plant oils, such as rapeseed, soybean, and olive oils. Although relatively heat stable, vitamin K1 is sensitive to light and oxidation. Ferland and Sandowski (1992) reported large ranges of up to 140–200 μg K1/100 g in rapeseed and soybean oils, 55 μg K1/100 g in olive oil, but as low as 3 μg K1/100 g in corn or peanut oils. They reported relatively good stability during cold processing, some losses with heat, but significant losses when exposed to sun or fluorescent light. Davidson et al. (1996), on the other hand, reported partial transformation of vitamin K1 to 2′, 3′-dihydrovitamin K1 (dK1) during hydrogenation. Peterson et al. (2002) carried out an assessment of vitamin K1 and dK1 in various types of commercial vegetable oils, fats, spreads, and salad dressings and found significant amounts of both in many of the plant-based oils as analyzed by HPLC, following a hexane extraction and purification step; they pointed out that the dK1 levels were dependent upon the degree of hydrogenation of the specific fats. Centi et al. (2015) indicated lower in vivo absorption rates for dK1 compared with vitamin K1. With the new required labeling after 2006 and converting away from trans-fat, this has become less of an issue, particularly for baked products containing less hydrogenated oils.
Vitamin K2 includes a group of derivatives with a similar central structure to K1, but with varying side chain length and multiple double bonds. K2 terminology is abbreviated as MK-n, where M is the menadione central bicyclic ring structure, K stands for vitamin K, and n represents the number of isoprenoid groups attached as the side chain (Figure 3.24). In earlier citations, one of the first vitamin K2 structures was referred to as farnoquinone, or MK-6. Since its discovery, several additional forms with higher nutritional activity have been found, including MK-4, MK-7, MK-8, and MK-9, with increasing numbers indicating lengthening of the side chain and increased hydrophobicity. Vitamin K2 can be found predominantly as MK-4 in egg yolks, avian fowl livers (e.g., geese, chicken), meats, and butter; as mostly MK-8 and MK-9 in fermented dairy products (e.g., cheeses); MK-7 in fermented soybeans (natto); and higher menaquinones (i.e., MK-10) can be synthesized by obligate and facultative anaerobic bacteria, including those from the microflora in the gut (Shearer et al., 2012; Schurgers and Vermeer, 2000). Vitamin K2’s general structure is 2-methyl-3-all-trans-polyprenyl-1, 4-naphtho-quinones with the MK-4 as one of the more biologically available derivatives; its chemical structure has been defined as either 2-methyl-3-(3,7,11,15-tetramethyl-2,6,10,14-hexadecatetraenyl)-1,4-naphthalene-dione; menatetrenone; or vitamin K2(20). Schurgers and Vermeer (2000) have reported levels of vitamins K1 and K2 with a relative distribution of the various MK-n’s in several food products; analyses were conducted with a solvent extraction based on food type, followed by reverse phase high pressure liquid chromatography (HPLC).
Still very limited information is available for the kinetics of degradation and stability of vitamin K in foods. Indyk (1988), working with vitamin K1 dissolved in hexadecane, observed stability of this vitamin to mild heat treatment, even in the presence of oxygen. Vitamin K was found to be susceptible to degradation and isomerization in the presence of light even at low intensity. The loss of the isomers, cis and trans, was described by zero-order kinetics, indicating the possibility of an autooxidation mechanism. Losses of either isomer did not result in the formation of the other. Several competing decomposition pathways have been proposed for the photolysis of vita min K depending upon conditions. A study on phylloquinone content in processed sea buckthorn berry juice and concentrate showed losses of 36–54% with additional losses during storage of 18%–32%; however, storage of freshly harvested berries resulted in phylloquinone increasing to levels ranging from 21% to 186% (Gutzeit et al., 2007a).
A third group of vitamin K derivatives includes a series of synthetic variations which have been developed over time, each in theory progressively improved over its predecessor. The basis for the activity of vitamin K revolves around the naphthoquinone nucleus (Figure 3.24). Menadione (2-methyl-1, 4-naphthoquinone, or often referred to as vitamin K3) was the first commercially available product with reportedly three times the biological activity of K1. Over time it was shown to have some serious side effects and was no longer in use for a number of years; however, more recent studies have been using this derivative in extreme cases. Menadione formed the basis, however, for later synthetic versions including menadione sodium bisulfite (MSB) and a later version, menadione sodium bisulfite complex (MSBC). It is reportedly water-soluble, stable to light and air, but not heat. Minimal information is available on kinetic stability. Other K-analogues include synthetic variations such as menadiol diacetate (acetomenaphthone, K4), menadiol sodium diphosphate, and menadione dimethylpyrimidinol bisulfite (Figure 3.24).
Pigments are complex compounds that absorb and reflect light in the wavelength of the visible region. In the original writing of this section, it was more or less assumed that the color pigments under discussion were associated with those naturally present in a given food product (i.e., chlorophyll in green peas, β-carotene in carrots, hemoglobin in meats, etc.). Other colors added to processed foods, usually artificial, were not discussed. Since then, food trends have grown exponentially in the direction of utilizing natural color additives in processed foods; thus, stability of these natural colors has become even more critical in terms of both the reactive substrates to which they are added as well as the stability of the raw natural pigments as supplied to food factories. With increasing numbers, types, sources, new methods of pigment extraction and processing, it becomes continually more crucial and challenging to monitor stability in order to best develop models to help the food industry predict retention and shelf life of food products and raw materials.
Color remains to be one of the first single most notable characteristics of food that often predetermines a consumer’s judgement on food quality (Spence, 2016), so, obviously, color stability is still an extremely important factor in foods. Over a decade ago, Griffiths (2005) reviewed acceptable synthetic and natural colors used in the US food industry and indicated a trend for an increased use of colors particularly in novelty snacks, desserts, and beverages, further emphasizing the importance of color stability in foods; this trend continues today, but mostly in the direction of natural colors. With increased awareness over health and safety concerns over synthetic food colorants and their potential toxicity, greater emphasis is being placed on more natural alternatives to meet consumer expectations (Amchova et al., 2015; Martins et al., 2016). Wrolstad and Culver (2012) more recently reviewed alternatives to artificial colors, and as new natural colorants have become more available, the numbers of acceptable color ingredients has been in constant flux; Table 3.4 presents natural colors approved for use in food in the US as of November 2017 (US FDA, 2017). Based on the US Code of Federal Regulations (CFR), natural colorant replacements must meet targets for hue, stability in specific application, and cost. These are rigid criteria to fall under as natural colors hardly ever meet the intensity of artificial dyes requiring significantly higher concentrations and creating potential off-flavors, increased cost, and decreased stability. Colorants such as carotenoids including β-carotene, annatto, paprika, and particularly lycopene are known to exhibit antioxidant activity. Flavonoids, including the anthocyanin group, have also been attributed to having health benefits such as antioxidant properties, anti-inflammatory effects, lowered blood pressure, and anti-tumor properties. Another group of colorants, known as the curcuminoids found in turmeric, are also found to have similar health-related properties as well as antithrombic effects and antimicrobial activity (Taylor, 1996). More recently, a new group of natural blue colors, phycocyanins, have been approved for use as colorants in certain types of foods and have potential health benefits as well as aesthetic appeal; they have been reported to have nutritional and antioxidant benefits (Eriksen, 2008). Overall changes in color may be due to a number of reactions such as pigment degradation or polymerization, interaction with other components in the food product, non-enzymatic browning, oxidation of tannins, and other reactions. The following section discusses some of the major sources of color pigments that are naturally present or added to processed foods and their relative stability to processing and/or storage conditions.
Recent market trends moving towards incorporating more natural ingredients in processed foods has spurred a great deal of effort in replacing artificial colors with natural counterparts. Since natural blue color is rare and one of the more challenging hues to provide both appealing color and stability in different food types, research emphasis has been on a replacement for artificial FD&C Blue #1 (“brilliant blue”). The main focus has been on phycocyanins, blue water-soluble pigment-protein complexes belonging to the phycobiliprotein (PBP) family. Two additional important members of this group include allophycocyanins (turquoise/aqua) and phycoerythrins (red/pink), (Glazer, 1989; Singh et al., 2015), although others have been cited (MacColl, 1998). They may be found in cyanobacteria (often referred to as blue-green algae, e.g., Arthrospira platensis [formerly known as Spirulina platensis] and A. maxima) and certain eukaryote algae, such as Rhodophytes, Cryptomonades, and Glaucophytes, with colors ranging over a broad spectrum from red, orange, and yellow to blue-green (Glazer, 1989). Pigmentation of these organisms is a composite of contributions, not only from the predominating phycobiliproteins, but also the presence of chlorophyll and carotenoids, making it critical for their proper separation for consistent quality control in terms of color and stability. Phycobiliproteins, in themselves, contribute distinctive coloration depending upon the nature of their protein environment an d their covalently attached tetrapyrrole prosthetic groups (Figure 3.25); the three main PBP groups as mentioned above are categorized based on their energy levels: the highest level being the phycoerythrins (or phycoerthrocyanin); intermediate level, the phycocyanins; and lowest level, the allophycocyanins (MacColl, 1998). Their energy levels are characterized by their maximum absorption wavelengths (λmax); for instance, phycocyanin has a characteristic cobalt/gentian blue color with a λmax around 610–620 nm (depending on which specific type it is, C- or R-phycocyanin [prefixes original terminology derived from their algal source, but currently refer more to their λmax ranges and prosthetic group attachments, independent of source]), and also emits fluorescence at about 650 nm. On the other hand, allophycocyanin absorbs and emits at λmax around 650–655 nm, while phycoerythrin has a λmax between 540 and 575 nm (Glazer and Hixson, 1975; Glazer, 1989; MacColl, 1998; Singh et al., 2015). It should be pointed out that bilins (phycobilins) which absorb light energy and transfer this energy to other bilins are called donors, and those that both absorb excitation energy and fluoresce are called acceptors (Glazer, 1989).
Figure 3.25 Structures of important peptide-linked phycobilin chromophores (tetrapyrrole prosthetic groups) that make up the phycobiliproteins from cyanobacteria and red algae. (adapted from Glazer, 1989, 1994a,b and MacColl, 1998).
At the molecular level, the phycobiliproteins are comprised of polypeptides with covalently bound open-chain linear tetrapyrroles (referred to as phycobilins or bilins) that act as light energy absorbing (“light-harvesting”) chromophores, similarly to chlorophyll, but in different spectral regions (Glazer, 1989, 1994a,b). The basic structure of each of the phycobiliproteins consists of two dissimilar α- and β-polypeptide subunits, each of which have a specific amino acid sequencing (Apt et al., 1995) and contain one or more of these phycobilins covalently attached via thioether linkages to specific cysteinyl residues; in the case of certain phycoerythrins, γ-polypeptide subunits have also been identified (Glazer, 1989; Liu et al., 2005). There are currently four phycobilins identified from cyanobacteria and red algae (Figure 3.25); they include phycocyanobilin, phycoerythrobilin, phycoviolobilin (phycobiliviolin), and phycourobilin (Glazer, 1994a,b; MacColl, 1998). The phycobiliproteins (with attached phycobilins) are assembled in organized cellular structures called phycobilisomes (PBS), and they make up the major mass (~85%) of the total PBS protein complex (total mass reported 6000–8000 kDa, Glazer, 1994a,b). Some typical examples of phycobiliproteins and their phycobilin polypeptide linkages are presented in Table 3.5. Biochemical and structural analyses of phycobiliproteins have shown αβ monomers to be assembled into a disc-like trimeric (αβ)3 or hexameric (αβ)6 configuration along with additional specific “linker” polypeptide chains (generally without phycobilins attached and colorless), which further aid in the organizational formation of the phycobilisomes into two main structural domains of a core substructure (allophycocyanins) and peripheral rods (close-in phycocyanins and further-out phycoerythrins, depending upon the organism and growth conditions) adhering to the stroma side of the thylakoid membrane (Yu and Glazer, 1982; Arteni et al., 2009; Singh et al., 2015). It has been proposed that these highly organized geometrical phycobilisome structures allow transferal of absorbed light energy to chlorophyll-a of photosystem II within the cyanobacteria species, allowing their adaptability to the photosynthetic process to varying light growing conditions, referred to as complementary chromatic adaptation (MacColl, 1998; Ojit et al., 2015). Their molecular weight (MW) varies according to their aggregation state, pH, temperature, protein concentration, ionic strength, and solvent (Mishra et al., 2008), with the MW range for aggregates varying anywhere from 110 to 120 kDa for trimers (e.g., allophycocyanins), ~250 kDa for hexamers (e.g., phycoerythrins) and 20–40 kDa for monomers, depending on the type of phycobiliprotein and species origin (Glazer, 1994a; Glazer and Cohen-Bazire, 1971). Their structural configuration and function have been under constant review over the past decades as new species of cyanobacteria/microalgae are researched and taxonomic nomenclature has adapted (Cohen et al., 1995; MacColl, 1998; Liu et al., 2005; Kupka and Scheer, 2008; Kasai et al., 2009; Singh et al., 2015; Saer and Blankenship, 2017). Pigment color and intensity will depend on species of origin, their growth environment, extraction methods, and purity of separation of phycocyanin from other pigment contributors. These will be important factors for the bioengineer in developing the most efficient extraction process for phycocyanin pigments, predicting stability, and maintaining a constant color range, when final use is as a food colorant.
Commercially produced phycocyanin, known as Spirulina, is most commonly obtained from the blue-green cyanobacterium, Anthrospira platensis, under the class Cyanophyceae. Anthrospira platensis contains three types of phytopigments: 1. chlorophyll-a (green pigment), 2. carotenoid-based pigment (orange-yellow), and 3. phycobiliproteins (blue-red pigments). Despite its recent acceptance as a “natural” blue food colora nt in the U.S. (chewing gum/candy, 2013 and other confectionery, beverages, desserts, etc. 2014, US FDA, 2017), A. platensis has been historically used as a food source for thousands of years. Arthrospira strains have high nutritional value with high levels of γ-linolenic acid, α-tocopherol, β-carotene, protein levels above 60%, rich in vitamin B’s and minerals (Ciferri, 1983; Spolaore et al., 2006; Borowitzka, 2013), as well as pharmaceutical potentials such as antioxidants, anti-inflammatory, anti-carcinogenic, etc. (Eriksen, 2008). Mechanisms of action as an antioxidant for phycocyanin have been reviewed by Romay et al. (2003); studies have shown phycocyanin to be an efficient scavenger of oxygen free radicals. Lisi et al. (2000) and Bhat and Madyastha (2000) have suggested a mechanism involving the phycobilin chromophore in the scavenging activity of the protein. Using kinetic models, they showed that micromolar concentrations of phycocyanins are able to reduce peroxy radicals by half, indicating high antioxidant activity for this compound. Based on work by Chepelev et al., (2006) and MacLean et al. (2008) on general mechanisms of pyrroles, it may be speculated that the highly conjugated double bonds within the tetrapyrrole are susceptible to autoxidation through their active NH-groups, resulting in the H-transferal to peroxy radicals.
Phycobilinsb (Attached to Cys-Residues of Phycobiliprotein Subunits) | |||||
Phycobilins |
Phycobiliprotein (Examples) |
α-subunits/β-subunits |
|||
Phycocyanobilin |
PCB |
620–650 |
C-Phycocyanin |
α | |
β |
![]() |
||||
Allophycocyanin |
α |
β |
|||
Phycoerythrobilin |
PEB |
540–565 |
C-Phycoerythrin |
α |
![]() |
β |
![]() |
||||
Phycoviolibilin (Phycobiliviolin) |
PVB (PXB) |
568 |
Phycoerythrocyanin |
α |
![]() |
β |
|||||
Phycourobilin |
PUB |
490 |
Phycocyanin WH8501 |
α |
![]() |
β |
![]() |
a Adapted from Glazer (1994a); from bMacColl (1998).
The wide variety of phycocyanin sources and diverse growing habitats of numerous cyanobacteria and eukaryote algae makes the study and understanding of the extracted pigments’ stability in food products a challenge. Traditionally, the organism of choice for production of phycocyanin has been Arthrospira platensis, grown photoautotrophically in alkaline media in open ponds rich in nutrient salts in tropical and/or subtropical climates. In this case, the high pH and alkalinity help inhibit possible contaminating and competing microorganisms, resulting in potentially higher yields and purity of the final product, barring other cross contamination that may occur in externally uncontrolled environments. Alternative production techniques including photoautotrophic, mixotrophic, heterotrophic, and recombinant methods, as well as various extraction and purification methods and their effect on total yields of pigment have been reviewed (Eriksen, 2008). With increased demands for this pigment/nutrient compound, new extraction methods have been explored as well as new sources of organisms. For instance, some phycocyanins found in the Synechoccocus lividus, strain I may thrive in hot springs at 73°C; whereas, the S. lividus, strain III only tolerates temperatures up to 55°C (MacColl et al., 1974). Another phycocyanin found in Cyanidium caldarium (red alga) grows at temperatures up to 57°C and pH as low as pH 0.05. Although thermophiles may contain slightly different polypeptide amino acid sequences making it stable under higher temperature growing conditions, there may still be different degrees of dissociation and levels of protein denaturation in vitro (Eisele et al., 2000). Once the phycobiliproteins are extracted from the phycobilisomes, the general structural organization is disrupted, and dissociation can occur, so it is difficult to predict exactly the behavior of these pigments based on their growth environment. Other species that may have higher phycocyanin pigment yield potential include Galdieria sulphuraria as discussed by Eriksen (2008) and Sørenson et al. (2013) and Anabaena circinalis (Ojit et al., 2015). Singh et al. (2009) studied optimization of growth medium on phycocyanin production in Phormidium ceylanicum using response surface methodology and found an optimum recovery efficiency of C-phycocyanin from crude extract to be 63.5%. Background knowledge of pigment source, growing conditions, and extraction methods used will be of utmost importance for consistent product quality and understanding of various mechanisms of degradation that may occur.
Furuki et al., 2003 conducted a study on efficiency of phycocyanin extraction from Arthrospira platensis by using ultrasonic radiation to disrupt cells; they reported first-order degradation kinetics for color with respect to the length of time of the irradiation exposure and higher purity of extract with a higher ultrasonic frequency (f u ) = 28 kHz compared to f u = 20 kHz. Moraes et al. (2011), on the other hand, describe various extraction procedures (chemical [organic vs, inorganic acid treatment]; physical [freeze/thaw, sonication, homogenization], and enzymatic [lysozyme]) for C-phycocyanin from Spirulina (A. platensis); they found a method using combined sonication with glass beads being highly efficient with yields above 43%. A further purification strategy was developed using ion exchange chromatography to achieve analytical grade product (Moraes and Kalil (2009). Purity (P) of an extracted phycocyanin pigment is often evaluated on the basis of a ratio of absorbancies (A) of the phycocyanobilin (in this case, A 620) and aromatic amino acids (A 280) such that level of purity for phycocyanin would be defined as P = A 620/A 280 > 0.7 for food grade, 3.9, reactive grade, or ≫4.0, analytical grade. It should be kept in mind, however, that color intensity of a pigment extract is dependent upon both overall concentration and purity, and does not account for differentiation between phycocyanin and allophycocyanin. Yoshikowa and Belay (2008) developed a 2-wavelength method (620, 650 nm, λmax, respectively) to monitor level and purity of these two phycocyanins.
Thermal degradation kinetic data have been reported on a liquid phycocyanin extract from Arthrospira platensis (Spirulina) at pH 5–6, at temperatures between 50°C and 65°C, using first-order models. The authors found highest stability at pH 6 between 50°C and 55°C, followed by pH 5, 57°C–65°C, but increasingly unstable at pH 7 with increasing tempera ture (Antelo et al., 2008, Table 3.6). Sarada et al. (1999) reported on phycocyanin stability as affected by different types of extraction and drying procedures for A. platensis, finding about 50% loss with either cross-flow, oven, or spray drying. Generally, they found maximum stability during storage at pH 5.0–7.5 at 9°C and reduced stability at temperatures >40°C. Chaiklahan et al. (2012) found similar results, with A. platensis having a maximum stability at pH 5.5–6.0 with decreasing stability at temperatures >47°C; however, the addition of 20%–40% glucose or sucrose or 2.5% sodium chloride significantly increased retention at pH 7.0 and 60°C; similar results were found by Martelli et al. (2014) with addition of sugar or honey during processing 25°C–80°C. Mishra et al. (2008) found citric acid addition at 4 mg/ml to help stabilize phycocyanins from A. platensis up to 45 days at 35 ± 5°C with negligible loss as compared with a control phycocyanins without preservative stored at 0°C. Similarly, Colla et al. (2017) found increased degradation of non-extracted solid mass A. platensis in powdered form with increasing temperatures 25°C–50°C, particularly when exposed to light, with more than 50% loss of color pigment within 30 days storage at elevated temperatures; they emphasized the importance of low temperature storage and use of proper light-restricting packaging.
Kannaujiya and Sinha (2016) investigated thermostability of phycocyanin and phycoerythrin extracted from cyanobacterium, Nostoc sp. Strain HKAR-2 as affected by the presence of various preservatives (including benzoic, citric, ascorbic acids, sucrose, and calcium chloride) during storage over a temperature range 4°C–40°C; highest stabilities were found using benzoic, citric acids and sucrose, respectively at 5 mM concentration levels.
Most work on replacement of artificial blue color up to this point has focused on phycocyanins obtained from A. platensis (Spirulina), and this is currently the only accepted natural blue colorant allowed in foods in the US, although still not yet in Canada. However, it bears mentioning some work on other naturally derived sources of blue colorant that have been researched. Newsome et al. (2014) have extensively reviewed blue colorants from a variety of biological sources and classified them into seven structural classes and have evaluated them according to their potential use as food colorants, along with the physical and regulatory challenges that would be required to finalize usage as a new colorant in food products. One example in particular that has received attention is an iridoid-derived color pigment referred to as Gardenia blue from the fruit of the Gardenia jasminoides Ellis, and is currently used as a natural colorant in food and beverages in parts of Asia, although not currently accepted in the US, Canada, or Europe. The iridoids are a group of monoterpenoids with a cyclopentanodihydropan ring structure and exist in several different forms of which several hundred have been identified, and the iridoid geniposide from G. jasminoides has been the most studied (Pintea, 2008). Upon its initial extraction from the fruit, it is in the form of the colorless iridoid geniposide and gardenoside. Following extraction, geniposide is hydrolyzed with β-glucosidase, yielding genipen and glucose, which is transformed into the blue pigment through reactions with amino acids, glycine, lysine, or phenylalanine (Paik et al., 2001). Sadano (2011) patented a process for preparation of this colorant in Japan and filed an application in the US in 2013. Escheverry et al. (2011) also developed a patent for a similar blue pigment derived from Genipa Americana fruit (huito juice). Jespersen et al. (2005) also discusses multiple sources of natural blue pigments, including phycocyanins, gardenia blue, and indigo and discusses their stability to heat and light; they found phycocyanins have the greatest versatility in terms of the bright blue appearance in different applications, even though they had relatively low stability. It should be mentioned here that certain anthocyanins and metallocomplexes of such, under strict pH conditions may also act as a blue colorant; however, as pointed out in a later section, these are relatively unstable. A further review of natural sources of blue pigments has been published (Buchweitz, 2016).
Chlorophylls refer collectively to a group of pigments providing color to green plant tissues. They range in color from a bright green to a dull olive brown and are often used as indicators of product quality of processed green vegetables, as measured by the intensity of their green color. The predominant green colored pigments include chlorophylls a and b at a reported ratio of about 3:1 as naturally occurring in plants. Both are derivatives of a tetrapyrrole phorbin (porphyrin ring with C9–C10 isocyclic ring) chelated with a centrally located magnesium atom and a C7 20-carbon phytol chain (Figure 3.26). Their main differences are their substituent groups at the C3 position and perceived color; chlorophyll a has a methyl group and is blue-green, and chlorophyll b has a formyl group with a yellow–green color (Belitz and Grosch, 1987). Isomeric forms may also exist as chlorophylls a′ and b′ or pheophytins a′ and b′, due to epimerization at the C10 center located on the isocyclic ring. Other less common forms that exist include chlorophyll c and chlorophyll d, isolated from marine algae. Chlorophyllides a and b are the respective acid derivatives of chlorophylls a and b resulting from enzymatic (e.g., naturally occurring chlorophyllase) or chemical hydrolysis of the C7 propionate ester and cleavage of the phytol chain; they too possess a green color. The main transformation or degradation products of chlorophylls a and b are respectively pheophytin a and b, which are formed through the replacement of the central magnesium of the porphyrin ring with hydrogen atoms. Also, pheophorbides a and b may be formed through the removal of the phytol chain from the pheophytins or through magnesium loss from the chlorophyllides. These degradation products all exhibit a dull-olive brown color.
Figure 3.26 Selected mechanisms of chlorophyll degradation. (1) Aronoff, 1966; (2) Schaber et al., 1984.; (3) Seely, 1966.; (4) Clydesdale et al., 1972.; (5) Jones et al., 1963.; (6) Schwartz and von Elbe, 1983.; (7) Jones et al., 1962.; (8) Minguez-Mosquera et al., 1989.; (9) Wagenknecht et al., 1952; (10) Canjura et al., 1999.
It has long been reported by many investigators that chlorophylls are susceptible to thermal treatment, being transformed into predominantly the dull green pheophytins a and b (Schwartz and von Elbe, 1983; LaBorde and von Elbe, 1994; Steet and Tong, 1996a,b; Heaton et al., 1996a,b; and Gunawan and Barringer, 2000). These compounds may also further degrade to pyropheophytin or other products through the destruction of the porphyrin ring. Schwartz and von Elbe (1983) working with spinach indicated that pyropheophytin was a predominant product of the thermal breakdown of chlorophylls and that its formation followed first-order kinetics. Heaton et al. (1996a) developed a general mechanistic model for rates of chlorophyll degradation to pheophytin, chlorophyllide and pheophorbide in green plant tissue, including models such as coleslaw, pickles, and olives. Their claim was that this model could discriminate between pathways of degradation and enable quantitative definition on which pathways were operational or predominate under different conditions. This would also allow better comparison of rates of chlorophyll degradation between various commodities. For instance, Heaton et al (1996b) found no significant change over time with chlorophyllide in coleslaw, but with pickles and olives, the formation of chlorophyllide with further degradation to pheophorbide was a predominant reaction pathway. Some of this variation may be due to the relative activity levels of chlorophyllase present, as well as pH and other environmental factors. This type of approach is important in understanding the mechanisms for discoloration and should aid the food processor in determining optimum shelf life.
Other factors influencing the stability of chlorophylls include light, oxygen, water activity, irradiation, pH, presence of metal traces, and enzymatic activity. Lajolo and Lanfer Marquez (1982) indicated higher rates of degradation with water activity in a spinach model system at 38.6°C. Similarly, the authors observed an increase in the rates of chlorophyll degradation upon a decrease in pH for the range 5.9–6.8. These results confirm the well-known and most common mechanism for chlorophyll degradation through its acid-catalyzed transformation into pheophytin (Figure 3.26). This reaction has been reported by several authors to follow first-order kinetics. The mechanisms by which chlorophylls degrade, of course, depend upon the process under consideration. For instance, Minguez-Mosquera et al. (1989) found that chlorophyllides were intermediary products in the fermentation of olives, and that the ratio of the various degradation products, including chlorophyllides a, b; pheophytins a, b; and pheophorbides a, b, were very dependent upon pH of the system (Figure 3.26).
Gunawan and Barringer (2000) studied the effect of acid (pH 3–8) and microbial growth on stability of green color of blanched broccoli under low temperature storage (7°C). Through HPLC determination, they found only conversion of chlorophylls to pheophytins. This conversion was greater at lower pH and fit a first-order kinetic model. Some isomers were also isolated, including chlorophylls a′ and b′, present in the blanched broccoli, and pheophytins a′ and b′ after acidification. The authors also found that chlorophyll degradation was dependent on the type of acid used. Acids containing a benzene ring resulted in more rapid color change than acids with a simple carbon chain; perhaps due to the hydrophobicity of the aromatic acids, they were able to diffuse more easily through the lipid membrane surrounding the chloroplasts. They also found that microbial growth increased loss of color and proposed two possible mechanisms by which this may occur. The first was simply that production of acid metabolite products would lower the pH and, thus, decrease chlorophyll stability. The second mechanism was due to the breakdown of the cellular structure of the broccoli, as evidenced by surface holes observed by scanning electron microscopy. This could result in exposing the chloroplasts more directly to the acidic medium.
Ryan-Stoneham and Tong (2000) developed a mathematical model to predict chlorophyll concentration as a function of time, temperature, and pH using pea puree as a model. Since pH naturally lowers during heating due to acid formation, the authors used a specially designed reactor to automatically adjust the pH of the medium to keep it constant during heating. They found that degradation of both chlorophylls a and b followed first-order kinetics. Reaction rate constants and energies of activation are presented in Table 3.6, as calculated by the conventional Arrhenius equation. The authors reported through the use of their modified model, factoring in pH as a variable, that the energies of activation were independent of pH.
Commodity |
Process/Conditions |
r2 |
kT value (min−1) |
Ea (kcal/mol) |
Reaction Order |
r2 |
Temp. Range (°C) |
t1/2 (min) |
Reference |
|
---|---|---|---|---|---|---|---|---|---|---|
Phycocyanins | ||||||||||
Cyanobacterium – Arthrospira platensis (formerly known as Spirulina platensis)* |
Antelo et al. (2008) |
|||||||||
Phycocyanin (PC) |
0.93 |
k65 = 17.40 × 10−2 |
3.98 | |||||||
0.94 |
k62 = 15.01 × 10−2 |
4.62 | ||||||||
Cultures: |
0.97 |
k60 = 6.60 × 10−2 |
10.50 | |||||||
pH 5.0 |
Grown in 450 L open outdoor bioreactor |
0.94 |
k57 = 2.40 × 10−2 |
87.4 |
1 |
0.94 |
50–65 |
28.88 | ||
0.97 |
k55 = 1.20 × 10−2 |
57.77 | ||||||||
Water supplemented with 20% Zarrouk medium |
0.93 |
k53 = 0.180 × 10−2 |
385.08 | |||||||
0.95 |
k50 = 0.060 × 10−2 |
1155.25 | ||||||||
0.95 |
k62 = 46.73 × 10−2 |
1.48 | ||||||||
Filtered, pressed, |
0.92 |
k60 = 22.85 × 10−2 |
3.03 | |||||||
pH 6.0 |
extruded, |
0.96 |
k57 = 3.60 × 10−2 |
135.6 |
1.0 |
0.96 |
50–62 |
19.25 | ||
dried 50°C, 6 hr, |
0.95 |
k55 = 0.300 × 10−2 |
231.05 | |||||||
frozen −18°C, |
0.94 |
k53 = 0.120 × 10−2 |
577.62 | |||||||
ground, sieved |
0.96 |
k50 = 0.048 × 10−2 |
144405 | |||||||
pH 7.0 |
0.95 |
k60 = 10.80 × 10−2 |
6.42 | |||||||
Extraction, |
0.93 |
k57 = 8.40 × 10−2 |
8.25 | |||||||
pH 7.0 |
Centrifugation, |
0.96 |
k55 = 0.600 × 10−2 |
111.2 |
1.0 |
0.88 |
50–60 |
115.52 | ||
Vacuum filtered |
0.97 |
k53 = 0.180 × 10−2 |
385.08 | |||||||
0.97 |
k50 = 0.120 × 10−2 |
577.62 | ||||||||
pH 5.0 |
Antelo et al. (2008) |
|||||||||
10% sorbitol |
0.94 |
k62 = 2.34 × 10−2 |
28.87 | |||||||
20% sorbitol |
0.88 |
k62 = 1.38 × 10−2 |
57.75 | |||||||
30% sorbitol |
0.95 |
k62 = 1.74 × 10−2 |
– |
1 |
– |
62 |
38.50 | |||
40% sorbitol |
0.93 |
k62 = 1.32 × 10−2 |
57.75 | |||||||
50% sorbitol |
0.94 |
k62 = 3.60 × 10−2 |
192.53 | |||||||
pH 6.0 |
Antelo et al. (2008) |
|||||||||
10% sorbitol |
Analysis: |
0.96 |
k62 = 4.62 × 10−2 |
14.43 | ||||||
20% sorbitol |
Spectrophotometric |
0.95 |
k62 = 3.00 × 10−2 |
23.10 | ||||||
30% sorbitol |
PC (mg/cm3) = |
0.98 |
k62 = 7.20 × 10−2 |
– |
1 |
– |
62 |
115.52 | ||
40% sorbitol |
(A615–0.474 × A652)/5.35 |
0.98 |
k62 = 6.60 × 10−2 |
115.52 | ||||||
50% sorbitol |
0.95 |
k62 = 3.60 × 10−2 |
192.53 | |||||||
pH 7.0 | ||||||||||
10% sorbitol |
0.92 |
k62 = 4.02 × 10−2 |
16.50 | |||||||
20% sorbitol |
0.90 |
k62 = 2.40 × 10−2 |
28.88 | |||||||
30% sorbitol |
0.92 |
k62 = 1.80 × 10−2 |
– |
1 |
– |
62 |
38.50 | |||
40% sorbitol |
0.94 |
k62 = 1.26 × 10−2 |
57.77 | |||||||
50% sorbitol |
0.92 |
k62 = 3.60 × 10−2 |
192.53 | |||||||
*Kasai et al. (2009) | ||||||||||
Phycocyanins | ||||||||||
Cyanobacterium – Arthrospira platensis (Spirulina platensis) |
Chaiklahan et al. (2012) |
|||||||||
Phycocyanin and Allophycocyanin | ||||||||||
Cultured in Zarrouk’s medium in 100 L outdoor open raceway ponds |
– |
k74 = 10.7 × 10−2 |
6.5 | |||||||
– |
k69 = 9.28 × 10−2 |
7.5 | ||||||||
– |
k64 = 7.35 × 10−2 |
9.4 | ||||||||
pH 5.0 |
– |
k59 = 3.20 × 10−2 |
23.9 |
1 |
0.983 |
47–74 |
21.6 | |||
Extraction/w/100 mM phosphate buffer (pH 7.0) |
– |
k55 = 2.02 × 10−2 |
34.4 | |||||||
– |
k51 = 1.12 × 10−2 |
62.1 | ||||||||
Centrifuged/filtered/freeze-dried |
– |
k47 = 0.60 × 10−2 |
116.5 | |||||||
– |
k74 = 7.07 × 10−2 |
9.7 | ||||||||
30 mg powder/30 ml citrate buffer (pH 5, 6, 7) |
– |
k69 = 4.81 × 10−2 |
14.5 | |||||||
— |
k64 = 2.47 × 10−2 |
28.1 | ||||||||
pH 6.0 |
Samples incubated 240 min |
– |
k59 = 1.50 × 10−2 |
28.8 |
1 |
0.992 |
47–74 |
46.4 | ||
Analysis: UV-VIS A280; A620; A652 |
– |
k55 = 0.75 × 10−2 |
92.7 | |||||||
– |
k51 = 0.41 × 10−2 |
167.0 | ||||||||
– |
k47 = 0.22 × 10−2 |
309.4 | ||||||||
mg/ml |
– |
k74 = 13.6 × 10−2 |
5.3 |
Chaiklahan et al. (2012) |
||||||
CPC = [A620 − 0.474 (A652)]/5.34 |
– |
k69 = 11.56 × 10−2 |
6.0 |
|||||||
APC = [A652 − 0.208 (A620)]/5.09 |
– |
k64 = 7.76 × 10−2 |
8.9 | |||||||
pH 7.0 |
– |
k59 = 3.09 × 10−2 |
29.9 |
1 |
0.962 |
47–74 |
22.8 | |||
– |
k55 = 1.46 × 10−2 |
47.5 | ||||||||
– |
k51 = 0.64 × 10−2 |
108.3 | ||||||||
– |
k47 = 0.54 × 10−2 |
128.6 | ||||||||
Phycocyanin and Allophycocyanin |
Chaiklahan et al. (2012) |
|||||||||
Effect of preservative: |
Glucose | |||||||||
0 |
0.99 |
k60 = 3.62 × 10−2 |
19.1 | |||||||
30 mg powder/30 ml citrate buffer (pH 7) |
2.5 |
0.95 |
k60 = 3.62 × 10−2 |
19.1 | ||||||
5 |
0.98 |
k60 = 3.65 × 10−2 |
19.0 | |||||||
10 |
0.97 |
k60 = 3.27 × 10−2 |
– |
1 |
60 |
21.2 | ||||
Preservative added at designated % in 30 ml soln. |
20 |
0.93 |
k60 = 2.06 × 10−2 |
33.6 | ||||||
40 |
0.98 |
k60 = 1.57 × 10−2 |
44.1 | |||||||
Sucrose | ||||||||||
2.5 |
0.99 |
k60 = 3.52 × 10−2 |
19.7 | |||||||
5 |
0.81 |
k60 = 3.11 × 10−2 |
22.3 | |||||||
10 |
0.93 |
k60 = 2.96 × 10−2 |
– |
1 |
60 |
23.4 | ||||
20 |
0.82 |
k60 = 2.31 × 10−2 |
30.0 | |||||||
40 |
0.96 |
k60 = 1.73 × 10−2 |
40.1 | |||||||
NaCl | ||||||||||
2.5 |
0.94 |
k60 = 1.02 × 10−2 |
68.0 | |||||||
5 |
0.93 |
k60 = 0.79 × 10−2 |
87.7 | |||||||
10 |
0.95 |
k60 = 0.88 × 10−2 |
– |
1 |
60 |
78.8 | ||||
20 |
0.95 |
k60 = 1.01 × 10−2 |
68.6 | |||||||
Phycocyanins |
||||||||||
Spirulina platensis |
Biomass protected from light/up to 63 days/25, 40, 50°C |
0.827 |
k50 = 3.94 × 10−5 |
1.76 × 104 |
Colla et al. (2017) |
|||||
0.910 |
k40 = 2.19 × 10−5 |
10.1 |
1 |
0.996 |
25–50 |
3.16 × 104 | ||||
0.830 |
k25 = 1.03 × 10−5 |
6.70 × 104 | ||||||||
Petri dishes/foil |
Fluorescent light for 90 days/25°C |
0.980 |
k25 = 3.38 × 10−5 |
– |
1 |
– |
25 |
2.05 × 104 | ||
Gelatin capsules |
0.964 |
k25 = 1.65 × 10−5 |
– |
1 |
– |
25 |
4.21 × 104 | |||
Amber glass |
0.977 |
k25 = 2.63 × 10−5 |
– |
1 |
– |
25 |
2.64 × 104 | |||
Petri dishes |
UV light for 60 days/25°C |
0.971 |
k25 = 3.51 × 10−5 |
– |
1 |
– |
25 |
1.98 × 104 | ||
Gelatin capsules |
0.968 |
k25 = 2.86 × 10−5 |
– |
1 |
– |
25 |
2.43 × 104 | |||
Ambe r glass |
0.968 |
k25 = 2.28 × 10−5 |
– |
1 |
– |
25 |
3.04 × 104 | |||
Phycocyanins |
||||||||||
Cyanobacterium (Nostoc sp. Strain HKAR-2) |
Kannaujiya and Sinha (2016) |
|||||||||
Effect of added preservative: | ||||||||||
Phycocyanin (PC) |
Control |
0.986 |
k40 = 60.2 × 10−6 |
1.15 × 104 | ||||||
Cultures grown in BG-11 medium/no N2/pH 7.0/20 + 2°C/daylight fluorescent tubes (94 mol photon m−2s−1/14/10 light/dark cycle) |
0.987 |
k25 = 26.7 × 10−6 |
12.73 |
1 |
0.992 |
4–40 |
2.59 × 104 | |||
0.964 |
k4 = 4.34 × 10−6 |
15.98 × 104 | ||||||||
CaCl2 |
0.885 |
k40 = 53.5 × 10−6 |
1.30 × 104 | |||||||
0.980 |
k25 = 22.9 × 10−6 |
12.55 |
1 |
0.995 |
4–40 |
3.02 × 104 | ||||
0.993 |
k4 = 3.98 × 10−6 |
17.42 × 104 | ||||||||
Ascorbic acid |
0.989 |
k40 = 43.8 × 10−6 |
1.58 × 104 | |||||||
0.963 |
k25 = 19.3 × 10−6 |
12.64 |
1 |
0.993 |
4–40 |
3.60 × 104 | ||||
Extraction, |
0.936 |
k4 = 3.21 × 10−6 |
21.60 × 104 | |||||||
Separation of PC/PE, |
Sucrose |
0.987 |
k40 = 18.5 × 10−6 |
3.74 × 104 | ||||||
Freeze-dry, |
0.932 |
k25 = 6.88 × 10−6 |
12.39 |
1 |
0.999 |
4–40 |
10.08 × 104 | |||
Dissolved pH 7 K-buffer (0.1 mg/ml) |
0.996 |
k4 = 1.39 × 10−6 |
49.82 × 104 | |||||||
Citric acid |
0.964 |
k40 = 9.82 × 10−6 |
7.06 × 104 | |||||||
Preservative Conc: 5.0 mM |
0.965 |
k25 = 6.25 × 10−6 |
10.11 |
1 |
0.966 |
4–40 |
11.09 × 104 | |||
Storage: 30 days |
0.936 |
k4 = 1.25 × 10−6 |
55.44 × 104 | |||||||
UV-VIS: |
Benzoic acid |
0.993 |
k40 = 5.60 × 10−6 |
12.38 × 104 | ||||||
Final purity ratio: A615/A280 = 3.19 |
0.980 |
k25 = 4.81 × 10−6 |
9.97 |
1 |
0.897 |
4–40 |
14.40 × 104 | |||
0.997 |
k4 = 0.764 × 10−6 |
90.72 × 104 | ||||||||
Phycocyanins |
||||||||||
Cyanobacterium (Nostoc sp. Strain HKAR-2) |
Kannaujiya and Sinha (2016) |
|||||||||
Effect of added preservative: | ||||||||||
Phycoerythrin (PE) |
Control |
0.903 |
k40 = 37.03 × 10−6 |
1.87 × 104 | ||||||
Cultures grown in BG-11 medium/no N2/pH 7.0/20+2°C/daylight fluorescent tubes (94 mol photon m−2s−1/14/10 light/dark cycle) |
0.862 |
k25 = 20.93 × 10−6 |
9.87 |
1 |
0.986 |
4–40 |
3.31 × 104 | |||
0.942 |
k4 = 4.86 × 10−6 |
14.26 × 104 | ||||||||
CaCl2 |
0.832 |
k40 = 34.38 × 10−6 |
2.02 × 104 | |||||||
0.993 |
k25 = 19.28 × 10−6 |
11.95 |
1 |
0.973 |
4–40 |
3.60 × 104 | ||||
0.990 |
k4 = 2.99 × 10−6 |
23.18 × 104 | ||||||||
Ascorbic acid |
0.893 |
k40 = 28.31 × 10−6 |
2.45 × 104 | |||||||
Extraction, |
0.971 |
k25 = 17.83 × 10−6 |
11.94 |
1 |
0.955 |
4–40 |
3.89 × 104 | |||
Separation of PC/PE, |
0.842 |
k4 = 2.507 × 10−6 |
27.65 × 104 | |||||||
Freeze-dry, |
Sucrose |
0.907 |
k40 = 22.92 × 10−6 |
3.02 × 104 | ||||||
Dissolved pH 7 K-buffer (0.1 mg/ml) |
0.919 |
k25 = 11.19 × 10−6 |
13.48 |
1 |
0.980 |
4–40 |
6.19 × 104 | |||
0.953 |
k4 = 1.45 × 10−6 |
47.95 × 104 | ||||||||
Citric acid |
0.923 |
k40 = 18.51 × 10−6 |
3.74 × 104 | |||||||
Preservative Conc: 5.0 mM |
0.996 |
k25 = 9.08 × 10−6 |
15.18 |
1 |
0.970 |
4–40 |
7.63 × 104 | |||
Storage: 30 days |
0.923 |
k4 = 0.834 × 10−6 |
83.09 × 104 | |||||||
UV-VIS: |
Benzoic acid |
0.995 |
k40 = 8.44 × 10−6 |
8.21 × 104 | ||||||
Final Purity Ratio: A563/A280 = 7.3 |
0.942 |
k25 = 6.25 × 10−6 |
16.94 |
1 |
0.905 |
4–40 |
11.09 × 104 | |||
0.964 |
k4 = 0.285 × 10−6 |
243.36 × 104 | ||||||||
Chlorophyll |
||||||||||
Asparagus |
Heated in distilled water |
Lau et al. (2000) |
||||||||
Fresh/whole bud segment |
(5–120 min) |
0.95 |
k98 = 0.013 |
53 | ||||||
Color measure: Lab-values/hue angle (h) |
0.91 |
k90 = 0.0087 |
12.9 |
1 |
– |
70–98 |
80 | |||
0.98 |
k80 = 0.005 |
139 | ||||||||
0.96 |
k70 = 0.0029 |
239 | ||||||||
Fresh/whole butt segment |
– |
k98 = 0.0167 |
42 | |||||||
– |
k90 = 0.0069 |
13.2 |
1 |
– |
70–98 |
100 | ||||
– |
k80 = 0.0054 |
128 | ||||||||
– |
k70 = 0.0032 |
217 | ||||||||
Broccoli juice |
Fresh broccoli liquified |
Weemaes et al. (1999b) |
||||||||
Chlorophyll a |
Heat in 800 ml sealed vials |
– |
k120 = 0.1224 |
5.7 | ||||||
– |
k110 = 0.0611 |
11.3 | ||||||||
(0–180 min) |
– |
k100 = 0.0284 |
17.0 |
1 |
– |
80–120 |
24.4 | |||
HPLC |
– |
k90 = 0.0187 |
37.1 | |||||||
– |
k80 = 0.0101 |
68.6 | ||||||||
Chlorophyll b |
– |
k120 = 0.0564 |
12.3 | |||||||
– |
k110 = 0.027 |
25.7 | ||||||||
– |
k100 = 0.0128 |
16.0 |
1 |
– |
80–120 |
54.2 | ||||
– |
k90 = 0.0083 |
83.5 | ||||||||
– |
k80 = 0.0055 |
126.0 | ||||||||
Total chlorophyll |
– |
k120 = 0.0943 |
7.4 |
Weemaes et al. (1999b) |
||||||
– |
k110 = 0.0489 |
14.2 |
||||||||
– |
k100 = 0.0229 |
16.5 |
1 |
– |
80–120 |
30.3 | ||||
– |
k90 = 0.0149 |
46.5 | ||||||||
– |
k80 = 0.0085 |
81.5 | ||||||||
Brussel sprouts |
Total chlorophyll |
Dietrich and Neumann (1965) |
||||||||
Whole or halves |
Water blanched, wire mesh immersion |
0.999 |
k100 = 0.5639 |
12.29 |
||||||
0.996 |
k93.3 = 0.04603 |
12.9 |
1 |
0.949 |
87.8–100 |
15.06 | ||||
0.980 |
k87.8 = 0.03113 |
22.27 | ||||||||
Steam blanched |
0.998 |
k115.6 = 0.12 |
5.78 | |||||||
0.991 |
k100 = 0.0689 |
12.3 |
1 |
0.987 |
87.8–115.6 |
10.06 | ||||
0.993 |
k93.3 = 0.05027 |
13.79 | ||||||||
0.996 |
k87.8 = 0.03476 |
19.94 | ||||||||
Green beans |
Total chlorophyll |
Dietrich et al. (1959) |
||||||||
Whole |
Water blanched, wire mesh immersion |
0.998 |
k100 = 0.04872 |
14.23 |
||||||
(cross-cut) |
0.999 |
k93.3 = 0.04293 |
5.2 |
1 |
0.999 |
87.8–100 |
16.15 | |||
0.994 |
k87.8 = 0.03847 |
18.02 | ||||||||
Whole |
Steam blanched |
0.996 |
k100 = 0.07599 |
9.12 | ||||||
Spectrophotometric |
0.996 |
k93.3 = 0.05322 |
9.2 |
1 |
– |
87.8–100 |
13.02 | |||
A534/A556 |
0.956 |
k87.8 = 0.005027 |
138.00 | |||||||
Green beans (cross-cut) |
Water blanched |
– |
k100 = 0.0931 |
– |
1 |
– |
100 |
– |
Walker (1964) |
|
Olives (pickled) |
Heated water bath |
Sánchez et al. (1991) |
||||||||
(0–60 min) | ||||||||||
Surface color: | ||||||||||
S-value (560, 590, 635 μ) |
Color via |
0.974 |
k90 = 0.004488 |
157.00 | ||||||
Spec-20 |
0.988 |
k80 = 0.003707 |
7.2 |
1 |
0.970 |
70–90 |
187.00 | |||
0.942 |
k70 = 0.0025282 |
274.00 | ||||||||
L-value |
Color via |
0.914 |
k90 = 0.0031997 |
217.00 | ||||||
Hunter |
0.972 |
k80 = 0.001757 |
10.5 |
1 |
0.937 |
70–90 |
394.00 | |||
0.946 |
k70 = 0.001367 |
506.00 | ||||||||
B-value |
Color via |
0.963 |
k90 = 0.0034653 |
200.00 | ||||||
Hunter |
0.964 |
k80 = 0.003329 |
5.1 |
1 |
0.836 |
70–90 |
208.00 | |||
0.921 |
k70 = 0.002309 |
300.00 | ||||||||
Chlorophyll |
||||||||||
Peas, whole |
Total chlorophyll |
Gold and Weckel (1959) |
||||||||
Blanched |
Packed in 2% salt in cans |
– |
k137.8 = 0.382 |
16.1 |
1.81 |
|||||
– |
k126.7 = 0.219 |
(16.1)a |
1 |
0.999 |
115.6–137.8 |
3.17 | ||||
Spectrophotometric analysis, Hunter colorimeter |
– |
k115.6 = 0.124 |
5.59 | |||||||
Unblanched |
– |
k137.8 = 0.312 |
14.3 |
2.22 | ||||||
– |
k126.7 = 0.208 |
(12.6)a |
1 |
0.992 |
115.6–137.8 |
3.33 | ||||
– |
k115.6 = 0.115 |
6.03 | ||||||||
Peas, puree |
pH 6.5 |
– |
– |
22a |
1 |
– |
79.4–137.8 |
– |
Lenz and Lund (1977b) |
|
Peas, puree |
Freeze-dried/rehydrated |
Ryan-Stoneham and Tong (2000) |
||||||||
Chlorophyll a |
pH 5.5 (w/control) |
– |
k100 = 0.16 |
4.3 | ||||||
– |
k90 = 0.08 |
16.3 |
1 |
0.994 |
80–100 |
8.7 | ||||
– |
k80 = 0.046 |
15.1 | ||||||||
pH 6.2 (w/control) |
– |
k100 = 0.082 |
8.5 | |||||||
– |
k90 = 0.046 |
17.2 |
1 |
0.997 |
80–100 |
15.1 | ||||
– |
k80 = 0.022 |
31.5 | ||||||||
pH 6.8 (w/control) |
– |
k100 = 0.034 |
20.4 | |||||||
– |
k90 = 0.016 |
18.1 |
1 |
0.996 |
80–100 |
43.3 | ||||
– |
k80 = 0.0085 |
81.6 | ||||||||
pH 7.5 (w/control) |
– |
k100 = 0.017 |
40.8 | |||||||
– |
k90 = 0.008 |
18.9 |
1 |
0.998 |
80–100 |
86.6 | ||||
– |
k80 = 0.004 |
173.0 | ||||||||
Chlorophyll b |
pH 5.5 (w/control) |
– |
k100 = 0.077 |
9.0 |
Ryan-Stoneham and Tong (2000) |
|||||
– |
k90 = 0.039 |
16.4 |
1 |
0.996 |
80–100 |
17.8 | ||||
– |
k80 = 0.022 |
31.5 | ||||||||
pH 6.2 (w/control) |
– |
k100 = 0.031 |
22.4 | |||||||
– |
k90 = 0.015 |
14.8 |
1 |
0.969 |
80–100 |
46.2 | ||||
– |
k80 = 0.01 |
69.3 | ||||||||
pH 6.8 (w/control) |
– |
k100 = 0.013 |
53.3 | |||||||
– |
k90 = 0.006 |
17.1 |
1 |
0.986 |
80–100 |
115.5 | ||||
– |
k80 = 0.0035 |
198.0 | ||||||||
pH 7.5 (w/control) |
– |
k100 = 0.008 |
86.6 | |||||||
– |
k90 = 0.0031 |
18.1 |
1 |
0.950 |
80–100 |
223.6 | ||||
– |
k80 = 0.002 |
346.6 | ||||||||
Peas, puree |
Freeze-dried/rehydrated |
Steet and Tong (1996a) |
||||||||
MWKR system |
– |
*k90 = 0.0344 |
20 |
|||||||
– |
k90 = 0.0376 |
18 | ||||||||
Chlorophyll a |
HPLC |
– |
k80 = 0.017 |
19.5 |
1 |
– |
70–90 |
41 | ||
– |
k80 = 0.0175 |
0.997 |
40 | |||||||
– |
k70 = 0.0075 |
92 | ||||||||
– |
k70 = 0.0074 |
94 | ||||||||
– |
k90 = 0.0152 |
46 |
Steet and Tong (1996b) |
|||||||
– |
k90 = 0.016 |
43 |
||||||||
Chlorophyll b |
HPLC |
– |
k80 = 0.008 |
17.1 |
1 |
– |
70–90 |
87 | ||
– |
k80 = 0.0086 |
0.997 |
81 | |||||||
– |
k70 = 0.0039 |
178 | ||||||||
– |
k70 = 0.0039 |
94 | ||||||||
Total green color |
Lab color |
– |
k90 = 0.0 184 |
38 | ||||||
(a-value) |
– |
k90 = 0.0187 |
37 | |||||||
– |
k80 = 0.0092 |
18.2 |
1 |
– |
70–90 |
75 | ||||
– |
k80 = 0.0087 |
0.999 |
80 | |||||||
* replicates |
– |
k70 = 0.0043 |
161 | |||||||
– |
k70 = 0.0042 |
165 | ||||||||
Peas, puree |
Freeze-dried/rehydrated |
Steet and Tong (1996b) |
||||||||
MWKR system | ||||||||||
Chlorophyll a |
HPLC |
– |
*k120 = 0.2672 |
2.59 | ||||||
– |
k120 = 0.2536 |
2.73 | ||||||||
– |
k110 = 0.137 |
20.4 |
1 |
0.998 |
100–120 |
5.06 | ||||
– |
k110 = 0.1324 |
5.24 | ||||||||
– |
k100 = 0.0652 |
10.63 | ||||||||
– |
k100 = 0.063 |
11.00 | ||||||||
Chlorophyll b |
HPLC |
– |
k120 = 0.107 |
6.48 | ||||||
– |
k120 = 0.1007 |
6.88 | ||||||||
– |
k110 = 0.0537 |
18.2 |
1 |
0.995 |
100–120 |
12.91 | ||||
– |
k110 = 0.0557 |
12.44 | ||||||||
– |
k100 = 0.0311 |
22.29 | ||||||||
– |
k100 = 0.0284 |
24.41 | ||||||||
Total green color |
Lab color |
– |
k120 = 0.154 |
4.50 |
Steet and Tong (1996b) |
|||||
(a-value) |
– |
k120 = 0.1547 |
4.48 |
|||||||
– |
k110 = 0.0774 |
20.3 |
1 |
0.999 |
100–120 |
8.96 | ||||
– |
k110 = 0.0766 |
9.05 | ||||||||
– |
k100 = 0.0383 |
18.10 | ||||||||
*replicates |
– |
k100 = 0.0381 |
18.19 | |||||||
Peas Whole |
Packed in distilled water in No. 303 cans (Hunter colorimeter) |
17.5a |
1 |
– |
98.9–126.7 |
– |
Rao et al. (1981) |
|||
reen peas |
Koca et al. (2006) |
|||||||||
Chlorophyll a |
Heat: Blanching of whole peas in buffer solns. | |||||||||
– |
k100 = 13.3 × 10−2 |
5.21 | ||||||||
pH 5.5 |
– |
k90 = 11.8 × 10−2 |
14.2 |
1 |
0.944 |
70–100 |
5.87 | |||
Buffers: 0.1M citric/0.1M dihydrogen phosphate |
– – |
k80 = 5.09 × 10−2 k90 = 1.17 × 10−2 |
13.6 | |||||||
k70 = 2.74 × 10−2 |
25.3 | |||||||||
Cooled in ice, mashed, and analyzed |
– |
k100 = 7.37 × 10−2 |
9.4 | |||||||
pH 6.5 |
– |
k90 = 3.62 × 10−2 |
12.1 |
1 |
0.965 |
70–100 |
19.14 | |||
– |
k80 = 2.83 × 10−2 |
24.5 | ||||||||
– |
k70 = 1.64 × 10−2 |
42.3 | ||||||||
Analysis: acetone extraction, HPLC |
– |
k100 = 1.82 × 10−2 |
38.1 | |||||||
pH 7.5 |
– |
k90 = 1.73 × 10−2 |
4.9 |
1 |
0.871 |
70–100 |
40.1 | |||
– |
k80 = 1.50 × 10−2 |
46.2 | ||||||||
– |
k70 = 1.01 × 10−2 |
68.6 | ||||||||
Chlorophyll b |
Heat: Blanching of whole peas in buffer solns. |
Koca et al. (2006) |
||||||||
– |
k100 = 0.53 × 10−2 |
131 | ||||||||
pH 5.5 |
– |
k90 = 0.25 × 10−2 |
10.5 |
1 |
0.786 |
70–100 |
277 | |||
Buffers: 0.1M citric/0.1M dihydrogen phosphate |
– |
k80 = 0.14 × 10−2 |
495 | |||||||
– |
k70 = 0.16 × 10−2 |
433 | ||||||||
– |
k100 = 0.39 × 10−2 |
178 | ||||||||
pH 6.5 |
Cooled in ice, mashed, and anlyzed |
– |
k90 = 0.14 × 10−2 |
11.5 |
1 |
0.832 |
70–100 |
495 | ||
k80 = 0.12 × 10−2 |
578 | |||||||||
– |
k70 = 0.09 × 10−2 |
770 | ||||||||
Analysis: acetone extraction, HPLC |
k100 = 0.16 × 10−2 |
433 | ||||||||
pH 7.5 |
– |
k90 = 0.12 × 10−2 |
7.0 |
1 |
0.997 |
70–100 |
578 |
Koca et al. (2006) |
||
– |
k80 = 0.09 × 10−2 |
770 | ||||||||
– |
k70 = 0.07 × 10−2 |
990 | ||||||||
Green peas (pH 5.5) |
– |
k100 = 2.69 × 10−2 |
25.8 |
Koca et al. (2006) |
||||||
Δ -a-value |
Heat: Blanching of whole peas in buffer solns. |
– |
k90 = 2.16 × 10−2 |
8.4 |
1 |
0.944 |
70–100 |
32.1 | ||
– |
k80 = 1.24 × 10−2 |
55.9 | ||||||||
– |
k70 = 1.08 × 10−2 |
64.2 | ||||||||
Buffers: 0.1M citric/0.1M dihydrogen phosphate |
– |
k100 = 2.79 × 10−2 |
24.8 | |||||||
Δ -a/b-value |
k90 = 2.12 × 10−2 |
9.5 |
1 |
0.995 |
70–100 |
32.7 | ||||
Cooled in ice, mashed, and anlyzed |
– |
k80 = 1.40 × 10−2 |
49.5 | |||||||
– |
k70 = 0.92 × 10−2 |
75.3 | ||||||||
k100 = 0.55 × 10−2 |
126 | |||||||||
Δ h-value |
– |
k90 = 0.39 × 10−2 |
8.2 |
1 |
0.996 |
70–100 |
178 | |||
Analysis: CIE-Lab Minolta CR-300 |
– |
k80 = 0.28 × 10−2 |
248 | |||||||
k70 = 0.21 × 10−2 |
330 | |||||||||
Green peas (pH 6.5) |
– |
k100 = 1.80 × 10−2 |
38.5 | |||||||
Δ -a-value |
Heat: Blanching of whole peas in buffer solns. |
– |
k90 = 0.97 × 10−2 |
12.3 |
1 |
0.974 |
70–100 |
71.4 | ||
— |
k80 = 0.76 × 10−2 |
91.2 | ||||||||
– |
k70 = 0.39 × 10−2 |
178 | ||||||||
Buffers: 0.1M citric/0.1M dihydrogen phosphate |
– |
k100 = 1.91 × 10−2 |
36.3 |
Koca et al. (2006) |
||||||
Δ -a/b-value |
— |
12.0 |
1 |
0.999 |
70–100 |
59.2 | ||||
– |
k80 = 0.76 × 10−2 |
91.2 | ||||||||
Cooled in ice, mashed, and anlyzed |
– |
k70 = 0.46 × 10−2 |
151 | |||||||
– |
k100 = 0.39 × 10−2 |
178 | ||||||||
Δ h-value |
– |
k90 = 0.23 × 10−2 |
12.1 |
1 |
0.994 |
301 | ||||
Analysis: CIE-Lab Minolta CR-300 |
– |
k80 = 0.16 × 10−2 |
433 | |||||||
– |
k70 = 0.09 × 10−2 |
770 | ||||||||
Green peas (pH 7.5) |
– |
k100 = 0.60 × 10−2 |
116 |
Koca et al. (2006) |
||||||
Δ -a-value |
Heat: Blanching of whole peas in buffer solns. |
– |
k90 = 0.41 × 10−2 |
11.2 |
1 |
0.885 |
70–100 |
169 | ||
– |
k80 = 0.18 × 10−2 |
385 | ||||||||
– |
k70 = 0.18 × 10−2 |
385 | ||||||||
Buffers: 0.1M citric/0.1M dihydrogen phosphate |
– |
k100 = 0.62 × 10−2 |
118 | |||||||
Δ -a/b-value |
– |
k90 = 0.55 × 10−2 |
9.1 |
1 |
0.8 00 |
70–100 |
126 | |||
– |
k80 = 0.23 × 10−2 |
301 | ||||||||
Cooled in ice, mashed, and anlyzed |
– |
k70 = 0.25 × 10−2 |
277 | |||||||
– |
k100 = 0.12 × 10−2 |
578 | ||||||||
Δ h-value |
– |
k90 = 0.12 × 10−2 |
8.9 |
1 |
0.799 |
70–100 |
578 | |||
Analysis: CIE-Lab Minolta CR-300 |
– |
k80 = 0.05 × 10−2 |
1386 | |||||||
– |
k70 = 0.05 × 10−2 |
1386 | ||||||||
Thompson seedless grapes (Vitis vinifera) |
Zheng et al. (2014) |
|||||||||
Total chlorophyll |
Fresh grapes homogenized/heated in covered 50 mm dia. glass beakers/w/stirring up to 30 min (7 pts) |
0.966 |
k80 = 4.46 × 10−2 | |||||||
Natural pH 3.4 |
0.982 |
k70 = 2.89 × 10−2 | ||||||||
0.991 |
k60 = 2.80 × 10−2 | |||||||||
0.965 |
k50 = 1.76 × 10−2 |
8.35 |
1 |
0.935 |
20–80 | |||||
Analysis: |
0.986 |
k40 = 1.67 × 10−2 | ||||||||
Acetone extraction/UV-VIS/664 nm |
0.953 |
k30 = 0.766 × 10−2 | ||||||||
0.859 |
k20 = 0.306 × 10−2 | |||||||||
Natural pH 3.4 |
0.871 |
k20 = 0.296 × 10−2 |
Zheng et al. (2014) |
|||||||
pH 2.0 |
0.917 |
k20 = 2.13 × 10−2 | ||||||||
pH 3.0 |
pH adjust: HCl/NaOH (<2 ml vol added) |
0.916 |
k20 = 0.423 × 10−2 | |||||||
pH 4.0 |
0.895 |
k20 = 1.54 × 10−2 | ||||||||
pH 5.0 |
0.970 |
k20 = 2.28 × 10−2 |
– |
1 |
– |
20 | ||||
pH 6.0 |
0.911 |
k20 = 0.883 × 10−2 | ||||||||
pH 7.0 |
0.957 |
k20 = 0.711 × 10−2 | ||||||||
pH 8.0 |
0.904 |
k20 = 1.24 × 10−2 | ||||||||
pH 9.0 |
0.984 |
k20 = 0.682 × 10−2 | ||||||||
Chlorophyll |
||||||||||
Spinach |
Pureed in pyrex tubes |
Gupte et al. (1964) |
||||||||
Chlorophyll a | ||||||||||
pH 6.5 |
– |
k148.9 = 0.658 |
1.05 | |||||||
– |
k143.3 = 0.5099 |
1.36 | ||||||||
– |
k137.8 = 0.3947 |
15.4 |
1 |
0.999 |
126.7–148.9 |
1.76 | ||||
– |
k132.6 = 0.3056 |
(143)a |
2.27 | |||||||
– |
k126.7 = 0.2365 |
2.93 | ||||||||
Chlorophyll b |
pH 5.5 |
– |
k148.9 = 0.3024 |
2.29 | ||||||
– |
k143.3 = 0.2667 |
2.60 | ||||||||
– |
k137.8 = 0.235 |
7.6 |
1 |
0.999 |
126.7–148.9 |
2.95 | ||||
– |
k132.6 = 0.2072 |
3.35 | ||||||||
– |
k126.7 = 0.1828 |
3.79 | ||||||||
Spinach |
Schwartz and von Elbe (1983) |
|||||||||
Chlorophyll a |
Pureed in cans (natural pH) |
0.992 |
ak126 = 0.2666 |
27.3 |
2.60 | |||||
0.994 |
k121 = 0.1777 |
(25.2)a |
1 |
0.998 |
116–126 |
3.90 | ||||
HPLC analysis |
0.984 |
k116 = 0.11 |
6.30 | |||||||
Chlorophyll b |
0.982 |
k126 = 0.1195 |
24.7 |
5.80 | ||||||
0.998 |
k121 = 0.0845 |
(22.5)a |
1 |
0.995 |
116–126 |
8.20 | ||||
0.996 |
k116 = 0.0537 |
12.91 | ||||||||
Pheophytin a |
– |
k126 = 0.07877 |
24.5 |
8.80 | ||||||
– |
k121 = 0.05545 |
(20.7)a |
1 |
0.996 |
116–126 |
12.50 | ||||
– |
k116 = 0.03555 |
19.50 | ||||||||
Pheophytin b |
– |
k126 = 0.1035 |
16.9 |
6.70 | ||||||
– |
k121 = 0.07877 |
(15.7)a |
1 |
0.999 |
116–126 |
8.80 | ||||
– |
k116 = 0.05975 |
11.60 | ||||||||
Chlorophyll |
||||||||||
Spinach, puree |
Blanched/freeze-dried/rehumidified |
Lajolo and Lanfer Marquez (1982) |
||||||||
Chlorophyll a | ||||||||||
pH 5.9 | ||||||||||
no glycerol |
aw |
g H2O/100 g | ||||||||
0.11 |
– |
– |
k56.7 = 2.00 × 10−5 |
62.0 |
1 |
– |
46–56.7 |
34.7 × 103 | ||
– |
k46 = 0.083 × 10−5 |
325 × 103 | ||||||||
0.32 |
5.9 |
– |
k56.7 = 13.95 × 10−5 |
5.0 × 103 | ||||||
6.0 |
– |
k46 = 2.30 × 10−5 |
34.0 |
1 |
0.999 |
38.6–56.7 |
30.1 × 103 | |||
6.4 |
– |
k38. 6 = 0.717 × 10−5 |
96.7 × 103 | |||||||
0.52 |
8.3 |
– |
k56.7 = 17.67 × 10−5 |
3.9 × 103 | ||||||
10.9 |
– |
k46 = 5.58 × 10−5 |
21.0 |
1 |
0.997 |
38.6–56.7 |
12.4 × 103 | |||
12.2 |
– |
k38.6 = 2.82 × 10−5 |
24.6 × 103 | |||||||
0.75 |
17.7 |
– |
k32 = 6.25 × 10−5 |
11.1 × 103 | ||||||
29.2 |
– |
k38.6 = 13.40 × 10−5 |
9.7 |
1 |
– |
32–38.6 |
5.2 × 103 | |||
38.0 |
– |
k32 = 18.83 × 10−5 |
3.7 × 103 | |||||||
0.75 |
17.7 |
– |
k32 = 6.25 × 10−5 |
11.1 × 103 | ||||||
29.2 |
– |
k38.6 = 13.40 × 10−5 |
9.7 |
1 |
– |
32–38.6 |
5.2 × 103 | |||
38.0 |
– |
k32 = 18.83 × 10−5 |
3.7 × 103 | |||||||
pH 5.9 | ||||||||||
with glycerol |
aw |
g H2O/100 g | ||||||||
0.32 |
8.5 |
– |
k38.6 = 7.20 × 10−5 |
– |
1 |
– |
38.6 |
9.6 × 103 | ||
0.32 |
6.1 |
– |
k38.6 = 3.85 × 10−5 |
– |
1 |
– |
38.6 |
18.0 × 103 | ||
0.52 |
14.1 |
– |
k38.6 = 10.28 × 10−5 |
– |
1 |
– |
38.6 |
6.7 × 103 | ||
0.32 |
– |
– |
k38.6 = 1.83 × 10−5 |
– |
1 |
– |
38.6 |
37.9 × 103 | ||
0.52 |
12.6 |
– |
k38.6 = 6.58 × 10−5 |
– |
1 |
– |
38.6 |
10.5 × 103 | ||
0.32 |
5.4 |
– |
k38.6 = 1.03 × 10−5 |
– |
1 |
– |
38.6 |
67.3 × 103 | ||
0.52 |
10.2 |
– |
k38.6 = 6.63 × 10−5 |
– |
1 |
– |
38.6 |
10.5 × 103 | ||
0.75 |
27.7 |
– |
k38.6 = 51.87 × 10−5 |
– |
1 |
– |
38.6 |
1.3 × 103 | ||
0.32 |
5.0 |
– |
k38.6 = 1.00 × 10−5 |
– |
1 |
– |
38.6 |
69.3 × 103 | ||
0.52 |
10.2 |
– |
k38.6 = 5.18 × 10−5 |
– |
1 |
– |
38.6 |
13.4 × 103 | ||
0.75 |
27.7 |
– |
k38.6 = 21.78 × 10−5 |
– |
1 |
– |
38.6 |
3.2 × 103 | ||
Chlorophyll |
||||||||||
Yerba Maté leaves (Ilex paraguariensis Saint Hilaire) |
Schmalko et al. (2005) |
|||||||||
Blanched leaves (16 + 5%, wb) | ||||||||||
Chlorophyll a |
Air-dried to reach desired MC |
0.993 |
k80 = 9.06 × 10−3 |
76.5 | ||||||
aw (0.789–0.812) |
0.998 |
k70 = 3.57 × 10−3 |
15.58 |
1 |
0.975 |
50–80 |
194.1 | |||
Leaves ground to 40 mesh |
0.996 |
k60 = 2.46 × 10−3 |
282.1 | |||||||
0.980 |
k50 = 1.03 × 10−3 |
670.8 | ||||||||
0.993 |
k80 = 7.64 × 10−3 |
90.7 | ||||||||
aw (0.652–0.690) |
Water activities equilibrated over specified saturated salt solns. |
0.998 |
k70 = 2.34 × 10−3 |
21.75 |
1 |
0.988 |
50–80 |
296.0 | ||
0.997 |
k60 = 0.963 × 10−3 |
719.5 | ||||||||
0.995 |
k50 = 0.415 × 10−3 |
1670.2 | ||||||||
0.995 |
k80 = 3.76 × 10−3 |
184.4 | ||||||||
aw (0.497–0.514) |
Pigment extraction: acetone: water |
0.995 |
k70 = 2.22 × 10−3 |
24.59 |
1 |
0.975 |
50–80 |
312.2 | ||
0.988 |
k60 = 0.618 × 10−3 |
1121.0 | ||||||||
0.993 |
k50 = 0.157 × 10−3 |
4424.3 | ||||||||
Analysis: HPLC UV-VIS |
0.995 |
k80 = 1.71 × 10−3 |
404.6 | |||||||
aw (0.260–0.305) |
0.996 |
k70 = 1.11 × 10−3 |
23.48 |
1 |
0.971 |
50–80 |
626.3 | |||
0.994 |
k60 = 0.263 × 10−3 |
2632.2 | ||||||||
0.994 |
k50 = 0.088 × 10−3 |
7846.9 | ||||||||
0.993 |
k80 = 1.09 × 10−3 |
634.9 | ||||||||
aw (0.105–0.111) |
0.990 |
k70 = 1.02 × 10−3 |
21.55 |
1 |
0.924 |
50–80 |
680.7 | |||
0.998 |
k60 = 0.230 × 10−3 |
3013.7 | ||||||||
0.992 |
k50 = 0.077 × 10−3 |
9041.1 | ||||||||
Chlorophyll b |
Air-dried to reach desired MC |
0.994 |
k80 = 4.95 × 10−3 |
140.1 |
Schmalko et al. (2005) |
|||||
aw (0.789–0.812) |
996.000 |
k70 = 1.88 × 10−3 |
17.22 |
1 |
0.969 |
50–80 |
369.7 |
|||
Leaves ground to 40 mesh |
0.998 |
k60 = 1.32 × 10−3 |
523.8 | |||||||
0.997 |
k50 = 0.442 × 10−3 |
1569.4 | ||||||||
0.980 |
k80 = 3.76 × 10−3 |
184.2 | ||||||||
aw (0.652–0.690) |
Water activities equilibrated over specified saturated salt solns. |
0.995 |
k70 = 1.02 × 10−3 |
24.12 |
1 |
0.990 |
50–80 |
681.8 | ||
0.997 |
k60 = 0.398 × 10−3 |
1740.1 | ||||||||
0.994 |
k50 = 0.147 × 10−3 |
4726.0 | ||||||||
0.990 |
k80 = 1.67 × 10−3 |
416.3 |
Schmalko et al. (2005) |
|||||||
aw (0.497–0.514) |
0.993 |
k70 = 0.993 × 10−3 |
24.74 |
1 |
0.976 |
50–80 |
697.8 | |||
0.986 |
k60 = 0.233 × 10−3 |
2970.6 | ||||||||
0.997 |
k50 = 0.072 × 10−3 |
9671.8 | ||||||||
0.997 |
k80 = 0.965 × 10−3 |
718.3 | ||||||||
aw (0.260–0.305) |
0.997 |
k70 = 0.557 × 10−3 |
20.29 |
1 |
0.988 |
50–80 |
1245.2 | |||
0.995 |
k60 = 0.178 × 10−3 |
3886.8 | ||||||||
0.993 |
k50 = 0.072 × 10−3 |
9671.8 | ||||||||
0.997 |
k80 = 0.828 × 10−3 |
836.8 | ||||||||
aw (0.105–0.111) |
0.998 |
k70 = 0.633 × 10−3 |
19.66 |
1 |
0.958 |
50–80 |
1094.4 | |||
0.998 |
k60 = 0.185 × 10−3 |
3746.7 | ||||||||
0.994 |
k50 = 0.070 × 10−3 |
9902.1 | ||||||||
a-value |
Air-dried to reach desired MC |
0.985 |
k80 = 1.25 × 10−3 |
556.7 |
Schmalko et al. (2005) |
|||||
aw (0.789–0.812) |
0.988 |
k70 = 0.888 × 10−3 |
10.90 |
1 |
0.971 |
50–80 |
780.3 |
|||
Leaves ground to 40 mesh |
0.990 |
k60 = 0.602 × 10−3 |
1152.0 | |||||||
0.989 |
k50 = 0.287 × 10−3 |
2415.1 | ||||||||
0.948 |
k80 = 1.49 × 10−3 |
465.2 | ||||||||
aw (0.652–0.690) |
Water activities equilibrated over specified saturated salt solns. |
0.994 |
k70 = 0.463 × 10−3 |
18.52 |
1 |
0.975 |
50–80 |
1496.0 | ||
0.991 |
k60 = 0.265 × 10−3 |
2615.6 | ||||||||
0.994 |
k50 = 0.117 × 10−3 |
5941.3 | ||||||||
0.992 |
k80 = 0.862 × 10−3 |
804.4 | ||||||||
aw (0.497–0.514) |
0.991 |
k70 = 0.307 × 10−3 |
20.83 |
1 |
0.980 |
50–80 |
2260.3 | |||
0.986 |
k60 = 0.178 × 10−3 |
3886.8 | ||||||||
0.994 |
k50 = 0.048 × 10−3 |
14341.0 | ||||||||
0.993 |
k80 = 2.50 × 10−4 |
2772.6 |
Schmalko et al. (2005) |
|||||||
aw (0.260–0.305) |
Color Touch Colorimeter CIELAB scale |
0.995 |
k70 = 1.33 × 10−4 |
14.40 |
1 |
0.999 |
50–80 |
5198.6 |
||
0.991 |
k60 = 0.733 × 10−4 |
9452.0 | ||||||||
0.990 |
k50 = 0.370 × 10−4 |
18904.0 | ||||||||
0.995 |
k80 = 1.02 × 10−4 |
6817.8 | ||||||||
aw (0.105–0.111) |
0.990 |
k70 = 1.43 × 10−4 |
15.66 |
1 |
0.798 |
50–80 |
4835.9 | |||
0.995 |
k60 = 0.483 × 10−4 |
14341.0 | ||||||||
0.988 |
k50 = 0.150 × 10−4 |
46209.8 | ||||||||
Anthocyanins | ||||||||||
Blackberry juice | ||||||||||
(cyanidin-3-glucoside) |
Debicki-Pospišil, et al. (1983) |
|||||||||
Control |
– |
k70 = 0.001178 |
15.0 |
588 |
||||||
– |
k50 = 0.00035 |
(14.8)a |
1 |
0.998 |
24–70 |
1,980 | ||||
– |
k24 = 0.0000395 |
17,548 | ||||||||
With furfural |
– |
k70 = 0.001395 |
13.2 |
497 | ||||||
– |
k50 = 0.0005067 |
(13.0)a |
1 |
0.996 |
24–70 |
1,368 | ||||
– |
k24 = 0.0000717 |
9,667 | ||||||||
HMF |
– |
k70 = 0.001478 |
13.1 |
469 | ||||||
– |
k50 = 0.0005783 |
(12.7)a |
1 |
0.992 |
24–70 |
1,199 | ||||
– |
k24 = 0.000078 |
8,887 | ||||||||
benzaldehyde |
– |
k70 = 0.001927 |
11.3a |
1 |
– |
24–70 |
360 | |||
formaldehyde |
– |
k70 = 0.003367 |
6.8a |
1 |
– |
24–70 |
206 | |||
Cyanidin-3-glucoside |
Debicki-Pospišil, et al. (1983) |
|||||||||
Control (in citrate buffer) |
– |
k70 = 0.00096 |
20.5 |
722 |
||||||
– |
k50 = 0.0001823 |
(20.1)a |
1 |
0.998 |
24–70 |
3,802 | ||||
– |
k24 = 0.00000933 |
74,290 | ||||||||
With furfural |
– |
k70 = 0.001217 |
17.9 |
570 | ||||||
– |
k50 = 0.0003067 |
(17.4)a |
1 |
0.996 |
24–70 |
2,260 | ||||
– |
k24 = 0.0000217 |
31,940 | ||||||||
HMF |
– |
k70 = 0.001525 |
18.8 |
455 | ||||||
– |
k50 = 0.0003683 |
(14.9)a |
1 |
0.995 |
24–70 |
1,882 | ||||
– |
k24 = 0.00002183 |
31,750 | ||||||||
Anthocyanins |
||||||||||
Boysenberry juice (A520/A420) |
0.907 |
k100 = 0.001546 |
(20)a |
1 |
– |
20–120 |
488 |
Ponting et al. (1960) |
||
Black currant (Ribes nigrum) Juice |
Hellström et al. (2013) |
|||||||||
Total anthocyanins |
From frozen concentrate |
– |
k21 = 22.8 × 10−6 |
0.304 × 105 | ||||||
– |
k9 = 5.88 × 10−6 |
18.17 |
1 |
0.999 |
4–21 |
1.16 × 105 | ||||
65 Bx; dil. 1:30 + 100 mg benzoic acid/L (pH 3.27) |
– |
k4 = 3.39 × 10−6 |
2.05 × 105 | |||||||
Delphinidin 3-glucoside |
– |
k21 = 28.8 × 10−6 |
0.241 × 105 | |||||||
k9 = 7.14 × 10−6 |
19.75 |
1 |
0.999 |
4–21 |
0.971 × 105 | |||||
Storage: capped 50 ml tubes/2–3 ml air headspace |
– |
k4 = 3.56 × 10−6 |
1.95 × 105 | |||||||
Delphinidin 3-rutinoside |
– |
k21 = 25.4 × 10−6 |
0.273 × 105 | |||||||
– |
k9 = 6.49 × 10−6 |
19.09 |
1 |
0.999 |
4–21 |
1.07 × 105 | ||||
Stored dark up to 22 wks. |
– |
k4 = 3.39 × 10−6 |
2.05 × 105 | |||||||
Cyanidin 3-glucoside |
– |
k21 = 2.14 × 10−6 |
0.034 × 105 | |||||||
– |
k9 = 5.46 × 10−6 |
19.50 |
1 |
0.999 |
4–21 |
1.27 × 105 | ||||
– |
k4 = 2.72 × 10−6 |
2.55 × 105 | ||||||||
Cyanidin 3-rutinoside |
Analysis: HPLC λ = 518 nm/MS |
– |
k21 = 19.6 × 10−6 |
0.354 × 105 | ||||||
– |
k9 = 5.13 × 10−6 |
19.01 |
1 |
0.999 |
4–21 |
1.35 × 105 | ||||
– |
k4 = 2.62 × 10−6 |
2.64 × 105 | ||||||||
Anthocyanins | ||||||||||
Chokeberry (Aronia mitchurinii) Juice |
Hellström et al. (2013) |
|||||||||
Total anthocyanins |
From frozen whole berries, mashed |
– |
k21 = 10.2 × 10−6 |
0.678 × 105 | ||||||
– |
k9 = 2.89 × 10−6 |
15.39 |
1 |
0.987 |
4–21 |
2.40 × 105 | ||||
65 Bx; dil. 1:30 + 100 mg benzoic acid/L (pH 3.27) |
– |
k4 = 2.12 × 10−6 |
3.28 × 105 | |||||||
Cyanidin 3-galactoside |
– |
k21 = 9.78 × 10−6 |
0.709 × 105 | |||||||
– |
k9 = 2.69 × 10−6 |
19.15 |
1 |
0.995 |
4–21 |
2.58 × 105 | ||||
Storage: capped 50 ml tubes/2–3 ml air headspace |
– |
k4 = 1.27 × 10−6 |
5.46 × 105 | |||||||
Cyanidin 3-glucoside |
k21 = 10.9 × 10−6 |
0.635 × 105 | ||||||||
k4 = 3.95 × 10−6 |
17.03 |
1 |
0.973 |
4–21 |
1.75 × 105 | |||||
Stored dark up to 22 wks |
– |
k21 = 1.17 × 10−6 |
4.06 × 105 | |||||||
Cyanidin 3-arabinoside |
k21 = 11.3 × 10−6 |
0.615 × 105 | ||||||||
Analysis: HPLC λ = 518 nm/MS |
– |
k9 = 3.27 × 10−6 |
18.53 |
1 |
0.994 |
4–21 |
2.12 × 105 | |||
– |
k4 = 1.56 × 10−6 |
4.46 × 105 | ||||||||
Anthocyanins | ||||||||||
Chokeberry juice cont. - |
– |
k21 = 9.39 × 10−6 |
0.738 × 105 |
Hellström et al. (2013) |
||||||
Cyanidin 3-xyloside |
– |
k9 = 2.33 × 10−6 |
18.13 |
1 |
0.997 |
4–21 |
2.97 × 105 |
|||
– |
k4 = 1.43 × 10−6 |
4.85 × 105 | ||||||||
Crowberry (Empetrum nigrum) Juice |
Hellström et al. (2013) |
|||||||||
Total anthocyanins |
From frozen concentrate |
– |
k21 = 31.5 × 10−6 |
0.220 × 105 |
||||||
k9 = 9.42 × 10−6 |
16.49 |
1 |
0.999 |
4–21 |
0.736 × 105 | |||||
65 Bx; dil. 1:30 + 100 mg benzoic acid/L (pH 3.27) |
– |
k4 = 5.59 × 10−6 |
1.24 × 105 | |||||||
Delphinidin 3-galactoside |
– |
k21 = 47.4 × 10−6 |
0.146 × 105 | |||||||
– |
k9 = 9.99 × 10−6 |
20.90 |
1 |
0.999 |
4–21 |
0.694 × 105 | ||||
Storage: capped 50 ml tubes/2–3 ml air headspace |
– |
k4 = 5.33 × 10−6 |
1.30 × 105 | |||||||
Delphinidin 3-arabinoside |
– |
k21 = 45.2 × 10−6 |
0.153 × 105 | |||||||
– |
k9 = 9.64 × 10−6 |
19.93 |
1 |
0.996 |
4–21 |
0.719 × 105 | ||||
Stored dark up to 22 wks |
– |
k4 = 5.73 × 10−6 |
1.21 × 105 | |||||||
Cyanidin 3-galactoside |
– |
k21 = 44.4 × 10−6 |
0.156 × 105 | |||||||
– |
k9 = 10.3 × 10−6 |
19.71 |
1 |
0.999 |
4–21 |
0.672 × 105 | ||||
Analysis: HPLC λ = 518 nm/MS |
– |
k4 = 5.64 × 10−6 |
1.23 × 105 | |||||||
Cyanidin 3-arabinoside |
– |
k21 = 43.5 × 10−6 |
0.159 × 105 | |||||||
– |
k9 = 10.9 × 10−6 |
19.44 |
1 |
0.999 |
4–21 |
0.635 × 105 | ||||
– |
k4 = 5.59 × 10−6 |
1.24 × 105 | ||||||||
Petunidin 3-galactoside |
– |
k21 = 40.2 × 10−6 |
0.172 × 105 |
Hellström et al. (2013) |
||||||
– |
k9 = 9.39 × 10−6 |
19.72 |
1 |
0.999 |
4–21 |
0.738 × 105 |
||||
– |
k4 = 5.09 × 10−6 |
1.36 × 105 | ||||||||
Peonidin 3-galactoside |
– |
k21 = 41.9 × 10−6 |
0.165 × 105 | |||||||
– |
k9 = 10.2 × 10−6 |
19.75 |
1 |
0.999 |
4–21 |
0.679 × 105 | ||||
– |
k4 = 5.29 × 10−6 |
1.31 × 105 | ||||||||
Peonidin 3-arabinoside |
– |
k21 = 37.4 × 10−6 |
0.1853 × 105 | |||||||
– |
k9 = 9.29 × 10−6 |
19.09 |
1 |
0.999 |
4–21 |
0.746 × 105 | ||||
– |
k4 = 5.09 × 10−6 |
1.36 × 105 | ||||||||
Malvidin 3-galactoside |
– |
k21 = 37.4 × 10−6 |
0.185 × 105 | |||||||
– |
k9 = 9.63 × 10−6 |
19.50 |
1 |
0.999 |
4–21 |
0.720 × 105 | ||||
– |
k4 = 5.21 × 10−6 |
1.33 × 105 | ||||||||
Malvidin 3-arabinoside |
– |
k21 = 40.0 × 10−6 |
0.173 × 105 | |||||||
– |
k9 = 10.3 × 10−6 |
19.01 |
1 |
0.999 |
4–21 |
0.671 × 105 | ||||
– |
k4 = 5.78 × 10−6 |
1.20 × 105 | ||||||||
Anthocyanins | ||||||||||
Blueberry |
IQF blueberries (MC = 86.5%) |
Martynenko and Chen (2016) |
||||||||
Tot. Anthocyanin: |
Lab-scale HTD processing |
0.964 |
k105 = 17.9 × 10−3 |
38.7 | ||||||
Hold times: 0–400 min |
0.945 |
k95 = 8.60 × 10−3 |
80.6 | |||||||
15 g puree/solvent extract |
0.979 |
k87.5 = 5.60 × 10−3 |
15.85 |
1 |
0.994 |
70–105 |
123.8 | |||
Analysis: Differential spectrophotometry (A520/A700) |
0.933 |
k80 =3.70 × 10−3 |
187.3 | |||||||
0.882 |
k70 =2.00 × 10−3 |
346.6 | ||||||||
PPC Formation: |
PPC = PC/CD × 100% |
0.921 |
k105 = 29.5 × 10−2 |
2.3 | ||||||
(% polymeric color) |
PC = polymeric color |
0.987 |
k95 = 16.5 × 10−2 |
4.2 | ||||||
CD = color density |
0.980 |
k87.5 = 6.20 × 10−2 |
18.95 |
0 |
0.951 |
70–105 |
11.2 | |||
0.980 |
k80 = 3.69 × 10−2 |
18.8 | ||||||||
0.978 |
k70 = 2.62 × 10−2 |
26.5 | ||||||||
Anthocyanins | ||||||||||
Cherries |
Total anthocyanins |
Ochoa et al. (2001) |
||||||||
Fresh fruit in sucrose soln./ packed in glass jars |
Pasteurized: 90°C/20 min | |||||||||
(0.073 m dia × 0.012 m h) |
Store: 10 mo | |||||||||
Sour (Prunus cerasus) |
With light |
a0.986 |
k20 = 3.194 × 10−5 |
– |
1 |
– |
20 |
2.170 × 104 | ||
No light |
0.995 |
k20 = 2.410 × 10−5 |
– |
1 |
– |
20 |
2.876 × 104 | |||
Sweet (Prunus avium) |
With light |
0.992 |
k20 = 2.500 × 10−5 |
– |
1 |
– |
20 |
2.773 × 104 | ||
No light |
0.982 |
k20 = 2.083 × 10−5 |
– |
1 |
– |
20 |
3.328 × 104 | |||
Store: 5 mo | ||||||||||
Sour (Prunus cerasus) |
With light |
0.975 |
k40 = 3.729 × 10−6 |
1.859 × 105 | ||||||
0.998 |
k20 = 1.729 × 10−6 |
8.49 |
1 |
0.998 |
4–40 |
4.009 × 105 | ||||
0.991 |
k4 = 0.764 × 10−6 |
9.073 × 105 | ||||||||
Sweet (Prunus avium) |
With light |
0.963 |
k40 = 4.826 × 10−6 |
1.436 × 105 | ||||||
0.991 |
k20 = 2.694 × 10−6 |
8.31 |
1 |
0.999 |
4–40 |
2.573 × 105 | ||||
0.957 |
k4 = 0.889 × 10−6 |
7.797 × 105 | ||||||||
Anthocyanins | ||||||||||
Cherry juice (sour) |
Cemeroglu et al. (1994) |
|||||||||
15° Brix |
Heated: 20 ml Pyrex tubes/w/minimal headspace |
0.982 |
k80 = 5.661 × 10−4 |
1.22 × 103 |
||||||
0.937 |
k70 = 2.048 × 10−4 |
3.38 × 103 | ||||||||
0.960 |
k60 = 0.875 × 10−4 |
16.37 |
1 |
0.936 |
50–80 |
7.92 × 103 | ||||
0.949 |
k50 = 0.665 × 10−4 |
10.42 × 103 | ||||||||
Max. 48 h | ||||||||||
45° Brix |
0.976 |
k80 = 9.532 × 10−4 |
0.727 × 103 | |||||||
0.982 |
k70 = 4.052 × 10−4 |
1.71 × 103 | ||||||||
0.972 |
k60 = 1.832 × 10−4 |
18.13 |
1 |
0.997 |
50–80 |
3.78 × 103 | ||||
0.916 |
k50 = 0.858 × 10−4 |
8.08 × 103 | ||||||||
71° Brix |
0.996 |
k80 = 16.192 × 10−4 |
0.428 × 103 | |||||||
0.927 |
k70 = 6.745 × 10−4 |
1.03 × 103 | ||||||||
0.931 |
k60 = 3.125 × 10−4 |
19.14 |
1 |
0.999 |
50–80 |
2.22 × 103 | ||||
0.951 |
k50 = 1.250 × 10−4 |
5.55 × 103 | ||||||||
Pasteurized/stored up to 160 days |
0.958 |
k37 = 1.281 × 10−5 |
0.541 × 105 | |||||||
45° Brix |
0.910 |
k20 = 0.367 × 10−5 |
15.58 |
1 |
0.992 |
5–37 |
1.89 × 105 | |||
0.906 |
k5 = 0.694 × 10−6 |
9.99 × 105 | ||||||||
71° Brix |
0.970 |
k37 = 1.659 × 10−5 |
0.418 × 105 | |||||||
0.904 |
k20 = 0.455 × 10−5 |
18.02 |
1 |
0.981 |
5–37 |
1.524 × 105 | ||||
0.949 |
k5 = 0.569 × 10−6 |
12.17 × 105 | ||||||||
Cherry juice model system | ||||||||||
Pelargonidin-3, 5-diglucoside |
pH 2.5 |
– |
k108 = 0.0426 |
16 |
Ioncheva and Tanchev (1974) |
|||||
– |
k98 = 0.01608 |
27.4 |
1 |
0.999 |
78–108 |
43 |
||||
– |
k88 = 0.006 |
116 | ||||||||
– |
k78 = 0.001896 |
366 | ||||||||
pH 3.5 |
– |
k108 = 0.03612 |
19 | |||||||
– |
k98 = 0.015 |
27.8 |
1 |
0.998 |
78–108 |
46 | ||||
– |
k88 = 0.004596 |
151 | ||||||||
– |
k78 = 0.00165 |
420 | ||||||||
Pelargonidin-3, 5-diglucoside |
pH 4.5 |
– |
k108 = 0.02928 |
24 |
Ioncheva and Tanchev (1974) |
|||||
– |
k98 = 0.01206 |
26.7 |
1 |
0.999 |
78–108 |
57 |
||||
– |
k88 = 0.00396 |
175 | ||||||||
– |
k78 = 0.001482 |
468 | ||||||||
Cyanidin-3, 5-diglucoside |
pH 2.5 |
– |
k108 = 0.0357 |
19 | ||||||
– |
k98 = 0.01626 |
23.5 |
1 |
0.999 |
78–108 |
43 | ||||
– |
k88 = 0.00657 |
106 | ||||||||
– |
k78 = 0.002532 |
274 | ||||||||
pH 3.5 |
– |
k108 = 0.0288 |
24 | |||||||
– |
k98 = 0.01296 |
25.4 |
1 |
0.996 |
78–108 |
53 | ||||
– |
k88 = 0.00417 |
166 | ||||||||
– |
k78 = 0.001746 |
397 | ||||||||
pH 4.5 |
– |
k108 = 0.03228 |
21 | |||||||
– |
k98 = 0.01392 |
24.2 |
1 |
0.999 |
78–108 |
50 | ||||
– |
k88 = 0.005466 |
127 | ||||||||
– |
k78 = 0.002112 |
328 | ||||||||
Peonidin-3, 5-diglucoside |
pH 2.5 |
– |
k108 = 0.03822 |
18 | ||||||
– |
k98 = 0.01566 |
27.2 |
1 |
0.998 |
78–108 |
44 | ||||
– |
k88 = 0.00495 |
140 | ||||||||
– |
k78 = 0.001842 |
376 | ||||||||
pH 3.5 |
– |
k108 = 0.03156 |
22 | |||||||
– |
k98 = 0.01338 |
24.3 |
1 |
0.934 |
78–108 |
52 | ||||
– |
k88 = 0.004548 |
152 | ||||||||
– |
k78 = 0.002136 |
325 | ||||||||
pH 4.5 |
– |
k108 = 0.02952 |
23 | |||||||
– |
k98 = 0.01161 |
24.3 |
1 |
0.999 |
78–108 |
60 | ||||
– |
k88 = 0.004986 |
139 | ||||||||
– |
k78 = 0.001848 |
375 | ||||||||
Petunidin-3, 5-diglucoside |
pH 2.5 |
– |
k108 = 0.0507 |
14 | ||||||
– |
k98 = 0.02532 |
19.4 |
1 |
0.999 |
78–108 |
27 | ||||
– |
k88 = 0.012 |
58 | ||||||||
– |
k78 = 0.00573 |
121 | ||||||||
Petunidin-3, 5-diglucoside |
pH 3.5 |
– |
k108 = 0.03846 |
18 |
Ioncheva and Tanchev (1974) |
|||||
– |
k98 = 0.01836 |
19.6 |
1 |
0.999 |
78–108 |
38 |
||||
– |
k88 = 0.00918 |
76 | ||||||||
– |
k78 = 0.004152 |
167 | ||||||||
Petunidin-3, 5-diglucoside |
pH 4.5 |
– |
k108 = 0.0291 |
24 |
Ioncheva and Tanchev (1974) |
|||||
– |
k98 = 0.01296 |
20.4 |
1 |
0.998 |
78–108 |
53 |
||||
– |
k88 = 0.006 |
116 | ||||||||
– |
k78 = 0.002904 |
239 | ||||||||
Malvidin-3, 5-diglucoside |
pH 2.5 |
– |
k108 = 0.0513 |
14 | ||||||
– |
k98 = 0.01986 |
26.5 |
1 |
0.999 |
78–108 |
35 | ||||
– |
k88 = 0.00762 |
91 | ||||||||
– |
k78 = 0.002544 |
272 | ||||||||
pH 3.5 |
– |
k108 = 0.02628 |
26 | |||||||
– |
k98 = 0.0114 |
26.0 |
1 |
0.998 |
78–108 |
61 | ||||
– |
k88 = 0.003816 |
182 | ||||||||
– |
k78 = 0.001458 |
475 | ||||||||
pH 4.5 |
– |
k108 = 0.02244 |
31 | |||||||
– |
k98 = 0.00942 |
26.2 |
1 |
0.998 |
78–108 |
74 | ||||
– |
k88 = 0.00309 |
224 | ||||||||
– |
k78 = 0.001212 |
572 | ||||||||
Anthocyanins | ||||||||||
Cornelian cherries (Cornus mas L.) |
Moldovan and David (2014) |
|||||||||
cyanidin-3-glucoside | ||||||||||
Extract (no preservative) |
Frozen cherries crushed/extracted/w/acidified water |
0.992 |
k75 = 137.7 × 10−5 |
503 | ||||||
extract: distilled water/HCl |
0.919 |
k22 = 1.45 × 10−5 |
14.0 |
1 |
0.954 |
2–75 |
47,803 | |||
pH 3.02 |
0.963 |
k2 = 0.80 × 10−5 |
86,643 | |||||||
Extract + Na-benzoate |
0.991 |
k75 = 131.4 × 10−5 |
528 | |||||||
(0.1 g/L) |
50 ml portions, capped, kept from light |
0.974 |
k22 = 1.55 × 10−5 |
13.5 |
1 |
0.947 |
2–75 |
44,719 | ||
0.973 |
k2 = 0.95 × 10−5 |
72,963 | ||||||||
Extract + K-sorbate |
0.991 |
k75 = 128.9 × 10−5 |
538 | |||||||
(0.1 g/L) |
Analysis: UV-VIS |
0.970 |
k22 = 1.88 × 10−5 |
13.0 |
1 |
0.954 |
2–75 |
36,804 | ||
0.990 |
k2 = 1.08 × 10−5 |
63,983 | ||||||||
Anthocyanins | ||||||||||
Cranberries |
Pigment extracted and concentrated solution in pH 2.5 phos-buffer |
Attoe and von Elbe (1981) |
||||||||
Cyanidin-3-arabinoside |
No light |
– |
k55 = 0.000283 |
26.8 |
1 |
– |
40–55 |
2,450 | ||
– |
k40 = 0.000395 |
17,500 | ||||||||
With light |
– |
k55 = 0.000435 |
8.7 |
1 |
– |
40–55 |
1,590 | |||
(400 ft-c) |
– |
k40 = 0.00023 |
3,010 | |||||||
Cyanidin-3-galactoside |
No light |
– |
k55 = 0.000267 |
26.7 |
1 |
– |
40–55 |
2,600 | ||
– |
k40 = 0.0000373 |
18,600 | ||||||||
With light |
– |
k55 = 0.000363 |
7.7 |
1 |
– |
40–55 |
1,900 |
Attoe and von Elbe (1981) |
||
(400 ft-c) |
– |
k40 = 0.000207 |
3,350 |
|||||||
Peonidin-3-arabinoside |
No light |
– |
k55 = 0.000287 |
24.9 |
1 |
– |
40–55 |
2,420 | ||
– |
k40 = 0.0000458 |
15,100 | ||||||||
With light |
– |
k55 = 0.000422 |
7.6 |
1 |
– |
40–55 |
1,640 | |||
(400 ft-c) |
– |
k40 = 0.000242 |
2,860 | |||||||
Peonidin-3-galactoside |
No light |
– |
k55 = 0.000265 |
26.4 |
1 |
– |
40–55 |
2,620 | ||
– |
k40 = 0.000038 |
18,200 | ||||||||
With light |
– |
k55 = 0.000337 |
5.4 |
1 |
– |
40–55 |
2,060 | |||
(400 ft-c) |
– |
k40 = 0.0000227 |
30,500 | |||||||
Anthocyanins | ||||||||||
18 Anthocyanins (averaged) |
Tanchev (1983) |
|||||||||
Fruit juice |
– |
k108 = 0.01925 |
36 | |||||||
– |
k98 = 0.008351 |
22.2 |
1 |
0.999 |
78–108 |
83 | ||||
– |
k88 = 0.003667 |
189 | ||||||||
– |
k78 = 0.001561 |
444 | ||||||||
Citrate buffer |
– |
k108 = 0.02666 |
26 | |||||||
– |
k98 = 0.01005 |
25.1 |
1 |
0.999 |
78–108 |
69 | ||||
– |
k88 = 0.004101 |
169 | ||||||||
– |
k78 = 0.00154 |
450 | ||||||||
Anthocyanins | ||||||||||
Concord grape pigments |
Sastry and Tischer (1952) |
|||||||||
Buffer solution (McIlvaine) |
pH 3.4 |
0.674 |
k121 = 0.01879 |
37 |
||||||
0.880 |
k98.9 = 0.00743 |
13.1 |
1 |
0.999 |
76.7–121 |
93 | ||||
0.838 |
k76.7 = 0.002263 |
306 | ||||||||
Anthocyanins | ||||||||||
Grape juice |
(Total Anthocyanins) |
Ponting et al. (1960) |
||||||||
Alicante bouschet (A) |
0.991 |
k100 = 0.002822 |
– |
1 |
– |
100 |
246 |
|||
Carignane (B) |
Evelyn colorimeter (A520/A420) |
0.943 |
k100 = 0.003438 |
– |
1 |
– |
100 |
202 | ||
Zinfandel (C) |
0.913 |
k100 = 0.003443 |
– |
1 |
– |
100 |
201 | |||
Grape blend |
0.996 |
k100 = 0.002592 |
(28)a |
1 |
– |
20–120 |
267 | |||
(45A:45B:10C) | ||||||||||
Anthocyanins | ||||||||||
Concord grape pigments (V. labrusca) |
Calvi and Francis (1978) |
|||||||||
CON - | ||||||||||
(Control: 0.1M citrate-phosphate buffer) |
pH 3.2 |
0.958 |
k95 = 0.005467 |
127 | ||||||
0.990 |
k90 = 0.0036 |
18.9 |
1 |
0.991 |
85–95 |
193 | ||||
0.992 |
k85 = 0.00265 |
262 | ||||||||
GLU - | ||||||||||
(buffer + 15% glucose) |
pH 3.2 |
0.990 |
k95 = 0.005383 |
129 | ||||||
0.992 |
k90 = 0.0037 |
19.7 |
1 |
0.999 |
85–95 |
187 | ||||
0.984 |
k85 = 0.002533 |
274 | ||||||||
SUC - | ||||||||||
(buffer + 15% sucrose) |
pH 3.2 |
0.994 |
k95 = 0.008233 |
84 | ||||||
0.998 |
k90 = 0.004783 |
23.8 |
1 |
0.995 |
80–95 |
145 | ||||
0.978 |
k85 = 0.0033 |
210 | ||||||||
0.990 |
k80 = 0.002 |
347 | ||||||||
FJD - | ||||||||||
(buffer + 15% sucrose + 10% white grape juice) |
pH 3.2 |
0.994 |
k95 = 0.008783 |
79 | ||||||
0.996 |
k90 = 0.0066 |
17.9 |
1 |
0.993 |
85–95 |
105 | ||||
0.990 |
k85 = 0.004433 |
156 | ||||||||
Anthocyanins | ||||||||||
Calvi and Francis (1978) |
||||||||||
CON |
pH 2.8 |
– |
k90 = 0.0044 |
– |
1 |
– |
90 |
158 |
||
GLU |
pH 2.8 |
– |
k90 = 0.003983 |
– |
1 |
– |
90 |
174 | ||
SUC |
pH 2.8 |
– |
k90 = 0.004667 |
– |
1 |
– |
90 |
149 | ||
CON |
pH 3.6 |
– |
k90 = 0.003867 |
– |
1 |
– |
90 |
179 | ||
GLU |
pH 3.6 |
– |
k90 = 0.003517 |
– |
1 |
– |
90 |
197 | ||
SUC |
pH 3.6 |
– |
k90 = 0.005133 |
– |
1 |
– |
90 |
135 | ||
Anthocyanins | ||||||||||
Plum juice | ||||||||||
Cyanidin-3-rutinoside |
pH 2.5 |
– |
k108 = 0.02028 |
34 |
Tanchev and Joncheva (1973) |
|||||
– |
k98 = 0.00768 |
21.8 |
1 |
0.991 |
78–108 |
90 |
||||
– |
k88 = 0.00348 |
199 | ||||||||
– |
k78 = 0.0017 |
408 | ||||||||
pH 3.5 |
– |
k108 = 0.02052 |
34 | |||||||
– |
k98 = 0.00762 |
20.6 |
1 |
0.984 |
78–108 |
91 | ||||
– |
k88 = 0.0037 |
187 | ||||||||
– |
k78 = 0.00196 |
354 | ||||||||
pH 4.5 |
– |
k108 = 0.02664 |
26 | |||||||
– |
k98 = 0.00876 |
22.6 |
1 |
0.981 |
78–108 |
79 | ||||
– |
k88 = 0.00395 |
175 | ||||||||
– |
k78 = 0.00201 |
345 | ||||||||
Peonidin-3-rutinoside |
pH 2.5 |
– |
k108 = 0.02904 |
24 |
Tanchev and Joncheva (1973) |
|||||
– |
k98 = 0.01014 |
29.9 |
1 |
0.999 |
78–108 |
68 |
||||
– |
k88 = 0.00327 |
212 | ||||||||
– |
k78 = 0.000996 |
696 | ||||||||
pH 3.5 |
– |
k108 = 0.03 |
23 | |||||||
– |
k98 = 0.01254 |
23.4 |
1 |
0.997 |
78–108 |
55 | ||||
– |
k88 = 0.00477 |
145 | ||||||||
– |
k78 = 0.00219 |
317 | ||||||||
pH 4.5 |
– |
k108 = 0.02988 |
23 | |||||||
– |
k98 = 0.01428 |
22.9 |
1 |
0.995 |
78–108 |
49 | ||||
– |
k88 = 0.00509 |
136 | ||||||||
– |
k78 = 0.00239 |
290 | ||||||||
Anthocyanins | ||||||||||
Pomegranate juice |
(mostly delphinidin-3, 5-diglucoside) |
Mishkin and Saguy (1982) |
||||||||
Total anthocyanins |
– |
k92 = 0.0018 |
385 | |||||||
– |
k90 = 0.00088 |
25.0 |
1 |
0.945 |
70–92 |
788 | ||||
– |
k80 = 0.00054 |
1,284 | ||||||||
– |
k70 = 0.00015 |
4,621 | ||||||||
Raspberries |
Total anthocyanins |
Ochoa et al. (2001) |
||||||||
Fresh fruit in sucrose soln./ packed in glass jars |
Pasteurized: 90°C/20 min | |||||||||
(0.073 m dia × 0.012 m h) |
Store: 10 mo | |||||||||
With light |
a0.975 |
k20 = 3.819 × 10−5 |
– |
1 |
– |
20 |
1.815 × 104 | |||
No light |
0.995 |
k20 = 1.528 × 10−5 |
– |
1 |
– |
20 |
4.537 × 104 | |||
Store: 5 mo | ||||||||||
With light |
0.975 |
k40 = 4.931 × 10−6 |
1.406 × 105 | |||||||
0.998 |
k20 = 2.347 × 10−6 |
6.24 |
1 |
0.998 |
4–40 |
2.953 × 105 | ||||
0.991 |
k4 = 1.389 × 10−6 |
4.990 × 105 | ||||||||
Anthocyanins | ||||||||||
Raspberry juice |
Tanchev (1972) |
|||||||||
Total anthocyanins | ||||||||||
Malling Promise |
pH 3.2 |
– |
k108 = 0.01986 |
35 | ||||||
– |
k98 = 0.00852 |
22.0 |
1 |
0.999 |
78–108 |
81 | ||||
– |
k88 = 0.00396 |
175 | ||||||||
– |
k78 = 0.00162 |
428 | ||||||||
New Burg |
pH 3.4 |
– |
k108 = 0.01638 |
42 | ||||||
– |
k98 = 0.0064 8 |
24.1 |
1 |
0.999 |
78–108 |
107 | ||||
– |
k88 = 0.002874 |
241 | ||||||||
– |
k78 = 0.00105 |
660 | ||||||||
Bulgarian ruby |
pH 3.3 |
– |
k108 = 0.0204 |
34 |
Tanchev (1972) |
|||||
– |
k98 = 0.00894 |
21.2 |
1 |
0.998 |
78–108 |
78 | ||||
– |
k88 = 0.00351 |
197 | ||||||||
– |
k78 = 0.00195 |
355 | ||||||||
Raspberry juice |
Tanchev (1972) |
|||||||||
(with added sugar) | ||||||||||
Malling Promise |
pH 3.2 |
– |
k108 = 0.0171 |
41 | ||||||
– |
k98 = 0.00615 |
23.0 |
1 |
0.988 |
78–108 |
113 | ||||
– |
k88 = 0.00345 |
201 | ||||||||
– |
k78 = 0.001164 |
595 | ||||||||
New Burg |
pH 3.4 |
– |
k108 = 0.01416 |
49 | ||||||
– |
k98 = 0.00618 |
23.6 |
1 |
0.999 |
78–108 |
112 | ||||
– |
k88 = 0.002652 |
261 | ||||||||
– |
k78 = 0.000972 |
713 | ||||||||
Bulgarian ruby |
pH 3.3 |
– |
k108 = 0.02052 |
34 | ||||||
– |
k98 = 0.00867 |
23.6 |
1 |
0.999 |
78–108 |
80 | ||||
– |
k88 = 0.00348 |
199 | ||||||||
– |
k78 = 0.001434 |
483 | ||||||||
Anthocyanins | ||||||||||
Raspberry pulp (Rubus idaeus L.) |
Summen and Erge (2014) |
|||||||||
Anthocyanin |
Fresh fruit/homogenized |
0.96 |
k90 = 36.5 × 10−4 |
189.9 |
||||||
(total monomeric) |
Heat: water bath/20 ml test tubes, 2 cm ID (8pts) |
0.94 |
k80 = 19.0 × 10−4 |
11.9 |
1 |
0.985 |
60–90 |
364.8 | ||
0.91 |
k70 = 13.2 × 10−4 |
526.4 | ||||||||
Time up to 7 hrs |
0.94 |
k60 = 7.83 × 10−4 |
884.9 | |||||||
L-ascorbic acid |
Extract 1 g pulp/w/MeOH + 0.1% HCl/centrifuge/supernatant evap. × 2 |
0.94 |
k90 = 7.00 × 10−4 |
990.2 | ||||||
0.90 |
k80 = 6.00 × 10−4 |
1155.2 | ||||||||
0.90 |
k70 = 4.67 × 10−4 |
3.8 |
1 |
0.928 |
60–90 |
1485.3 | ||||
Analyses: UV-VIS |
0.92 |
k60 = 4.50 × 10−4 |
1540.3 | |||||||
a-value |
Anthocyanins: A700/A527 |
0.99 |
k90 = 10.8 × 10−4 |
644.8 | ||||||
Ascorbic acid: A500 |
0.98 |
k80 = 4.10 × 10−4 |
1690.6 | |||||||
0.97 |
k70 = 2.48 × 10−4 |
18.4 |
1 |
0.986 |
60–90 |
2791.2 | ||||
Color: Hunterlab |
0.94 |
k60 = 0.983 × 10−4 |
7049.0 | |||||||
b-value |
0.77 |
k90 = 12.3 × 10−4 |
565.8 | |||||||
0.95 |
k80 = 10.6 × 10−4 |
651.9 | ||||||||
0.94 |
k70 = 6.75 × 10−4 |
12.0 |
1 |
0.909 |
60–90 |
1026.9 | ||||
0.84 |
k60 = 2.73 × 10−4 |
2535.9 | ||||||||
Anthocyanins | ||||||||||
Summen and Erge (2014) |
||||||||||
Chroma |
0.97 |
k90 = 10.9 × 10−4 |
634.0 |
|||||||
0.98 |
k80 = 5.03 × 10−4 |
1377.1 | ||||||||
0.93 |
k70 = 3.07 × 10−4 |
16.3 |
1 |
0.992 |
60–90 |
2260.3 | ||||
0.94 |
k60 = 1.35 × 10−4 |
5134.4 | ||||||||
Anthocyanins | ||||||||||
Strawberry juice | ||||||||||
In oxygen |
pH 3.05 |
– |
k45 = 5.95 × 10−4 |
– |
1 |
– |
45 |
1,165 |
Lukton et al. (1956) |
|
pH 3.55 |
– |
k45 = 10.83 × 10−4 |
– |
1 |
– |
45 |
640 |
|||
pH 4.30 |
– |
k45 = 15.33 × 10−4 |
– |
1 |
– |
45 |
452 | |||
In nitrogen |
pH 3.05 |
– |
k45 = 0.85 × 10−4 |
– |
1 |
– |
45 |
8,155 | ||
pH 3.55 |
– |
k45 = 1.00 × 10−4 |
– |
1 |
– |
45 |
6,966 | |||
pH 4.30 |
– |
k45 = 1.24 × 10−4 |
– |
1 |
– |
45 |
5,590 | |||
Anthocyanins | ||||||||||
Strawberry juice |
Spectrophotometer |
Ponting et al. (1960) |
||||||||
(A490/A420) |
– |
– |
(19)a |
1 |
– |
20–120 |
– |
|||
Anthocyanins | ||||||||||
Wine grapes |
Peron et al. (2017) |
|||||||||
Juçara grapes |
Extraction |
0.96 |
k90 = 12.5 × 10−4 |
0.555 × 103 | ||||||
(Euterpe edulis Martius) |
Filtration |
0.91 |
k80 = 6.48 × 10−4 |
1.07 × 103 | ||||||
pH adjust 2.5 |
0.95 |
k70 = 4.26 × 10−4 |
23.3 |
1 |
0.955 |
50–90 |
1.63 × 103 | |||
malvidin-3-O-glu predominates |
0.97 |
k60 = 1.01 × 10−4 |
6.86 × 103 | |||||||
0.97 |
k50 = 0.220 × 10−4 |
31.5 × 103 | ||||||||
Italia grapes |
Analysis: |
0.97 |
k90 = 54.5 × 10−4 |
0.127 × 103 | ||||||
(Evitus vinifera L.) |
UV/VIS – A528 |
0.97 |
k80 = 28.3 × 10−4 |
0.245 × 103 | ||||||
0.97 |
k70 = 15.3 × 10−4 |
22.0 |
1 |
0.980 |
50–90 |
0.453 × 103 | ||||
0.99 |
k60 = 4.57 × 10−4 |
1.52 × 103 | ||||||||
0.99 |
k50 = 1.23 × 10−4 |
5.64 × 103 | ||||||||
Anthocyanins | ||||||||||
Wine model systems |
Baranowski and Nagle (1983) |
|||||||||
Malvidin-3-glucoside |
Glass tubes, |
– |
k52 = 6.60 × 10−5 |
1.05 × 104 |
||||||
(M-3-G) |
O2-free atmos., |
– |
k42 = 9.60 × 10−4 |
16.9 |
1 |
0.778 |
22–52 |
0.0722 × 104 | ||
HPLC |
– |
k32 = 4.08 × 10−6 |
(28)a |
16.99 × 104 | ||||||
– |
k22 = 4.38 × 10−6 |
15.83 × 104 | ||||||||
M-3-G + d-catechin |
– |
k52 = 3.24 × 10−5 |
2.14 × 104 | |||||||
– |
k42 = 1.98 × 10−5 |
12.0 |
1 |
0.971 |
22–52 |
3.50 × 104 | ||||
– |
k32 = 1.26 × 10−5 |
(11)a |
5.50 × 104 | |||||||
– |
k22 = 4.68 × 10−6 |
14.81 × 104 | ||||||||
M-3-G + d-catechin + equimolar acetaldehyde |
– |
k52 = 2.94 × 10−5 |
2.36 × 104 | |||||||
– |
k42 = 2.04 × 10−5 |
13.0 |
1 |
0.832 |
22–52 |
3.40 × 104 | ||||
– |
k32 = 1.68 × 10−5 |
(10)a |
4.13 × 104 | |||||||
– |
k22 = 3.30 × 10−6 |
21.00 × 104 | ||||||||
M-3-G + d-catechin + XS acetaldehyde |
– |
k52 = 9 .60 × 10−5 |
0.722 × 104 |
Baranowski and Nagle (1983) |
||||||
– |
k42 = 5.94 × 10−5 |
12.7 |
1 |
0.994 |
22–52 |
1.17 × 104 |
||||
– |
k32 = 2.88 × 10−5 |
(13)a |
2.41 × 104 | |||||||
– |
k22 = 1.32 × 10−5 |
5.25 × 104 | ||||||||
Wine model systems | ||||||||||
(grape skin pigments in potassium hydrogen tartrate, pH 3.5) |
Storage: |
Romero and Bakker (2000) |
||||||||
50 ml vials/air/dark/up to 140 days | ||||||||||
HPLC | ||||||||||
PA/TA Ratio | ||||||||||
Malvidin-3-glucoside |
0 |
0.984 |
k32 = 59.03 × 10−6 |
1.17 × 10−4 | ||||||
0.984 |
k20 = 29.17 × 10−6 |
0.32 |
1 |
– |
10–32 |
2.38 × 10−4 | ||||
PA = pyruvic acid |
0.963 |
k15 = 5.56 × 10−6 |
12.48 × 10−4 | |||||||
TA = total anthocyanins |
0.975 |
k10 = 4.86 × 10−6 |
14.26 × 10−4 | |||||||
300 |
0.975 |
k32 = 39.58 × 10−6 |
1.75 × 10−4 | |||||||
0.981 |
k20 = 20.14 × 10−6 |
0.24 |
1 |
– |
10–32 |
3.44 × 10−4 | ||||
0.987 |
k15 = 8.33 × 10−6 |
8.32 × 10−4 | ||||||||
0.986 |
k10 = 4.86 × 10−6 |
14.26 × 10−4 | ||||||||
Malvidin-3-acetylglucoside |
0 |
0.933 |
k32 = 54.86 × 10−6 |
1.17 × 10−4 |
Romero and Bakker (2000) |
|||||
0.994 |
k20 = 34.03 × 10−6 |
0.31 |
1 |
– |
10–32 |
2.38 × 10−4 |
||||
0.919 |
k15 = 5.56 × 10−6 |
12.48 × 10−4 | ||||||||
0.973 |
k10 = 4.86 × 10−6 |
14.26 × 10−4 | ||||||||
300 |
0.927 |
k32 = 41.67 × 10−6 |
1.66 × 10−4 | |||||||
0.921 |
k20 = 18.06 × 10−6 |
0.23 |
1 |
– |
10–32 |
3.84 × 10−4 | ||||
0.933 |
k15 = 11.81 × 10−6 |
5.87 × 10−4 | ||||||||
0.875 |
k10 = 5.56 × 10−6 |
12.48 × 10−4 | ||||||||
Malvidin-3p-coumaryl-glucoside |
0 |
0.984 |
k32 = 104.9 × 10−6 |
0.661 × 10−4 | ||||||
0.997 |
k20 = 53.47 × 10−6 |
0.37 |
1 |
– |
10–32 |
1.30 × 10−4 | ||||
0.933 |
k15 = 8.33 × 10−6 |
8.32 × 10−4 | ||||||||
0.906 |
k10 = 5.56 × 10−6 |
12.48 × 10−4 | ||||||||
300 |
0.963 |
k32 = 67.36 × 10−6 |
1.03 × 10−4 | |||||||
0.927 |
k20 = 26.39 × 10−6 |
0.30 |
1 |
– |
10–32 |
2.63 × 10−4 | ||||
0.938 |
k15 = 10.42 × 10−6 |
6.65 × 10−4 | ||||||||
0.925 |
k10 = 5.56 × 10−6 |
12.48 × 10−4 | ||||||||
Anthocyanins |
||||||||||
Black rice (Oryza sativa L.) Extract |
Loypimai et al. (2016) |
|||||||||
pH 2.0 |
0.901 |
k100 = 1.16 × 10−3 |
598 |
|||||||
Cyanidin-3-O-glucoside |
0.875 |
k80 = 0.520 × 10−3 |
6.05 |
1 |
0.866 |
60–100 |
1326 | |||
3 g extract/1 L 2.0M acetate buffer/pH adjust 0.952 |
0.931 |
k60 = 0.43 × 10−3 |
1614 | |||||||
k100 = 2.42 × 10−3 |
286 | |||||||||
Cyanidin-3-O-rutinoside |
0.931 |
k80 = 0.99 × 10−3 |
6.98 |
1 |
0.885 |
60–100 |
696 | |||
Heat: waterbath/capped 15 ml brown glass vials 0–120 min (7 pts) |
0.936 |
k60 = 0.77 × 10−3 |
900 | |||||||
0.936 |
k100 = 4.36 × 10−3 |
159 | ||||||||
Delphinidin |
0.969 |
k80 = 1.79 × 10−3 |
9.43 |
1 |
0.984 |
60–100 |
387 | |||
0.958 |
k60 = 0.94 × 10−3 |
738 | ||||||||
Analysis: HPLC |
0.895 |
k100 = 3.78 × 10−3 |
184 |
Loypimai et al. (2016) |
||||||
Cyanidin |
0.923 |
k80 = 1.03 × 10−3 |
9.07 |
1 |
0.820 |
60–100 |
672 |
|||
0.964 |
k60 = 0.85 × 10−3 |
816 | ||||||||
0.957 |
k100 = 3.96 × 10−3 |
175 | ||||||||
Pelargonidin |
0.971 |
k80 = 1.68 × 10−3 |
10.42 |
1 |
0.998 |
60–100 |
413 | |||
0.973 |
k60 = 0.73 × 10−3 |
954 | ||||||||
0.955 |
k100 = 3.81 × 10−3 |
182 | ||||||||
Total |
0.880 |
k80 = 1.04 × 10−3 |
11.41 |
1 |
0.936 |
60–100 |
666 | |||
0.928 |
k60 = 0.59 × 10−3 |
1176 | ||||||||
pH 33.0 |
0.931 |
k100 = 1.83 × 10−3 |
374 | |||||||
Cyanidin-3-O-glucoside |
0.931 |
k80 = 1.19 × 10−3 |
3.89 |
1 |
0.937 |
60–100 |
583 | |||
0.965 |
k60 = 0.98 × 10−3 |
714 | ||||||||
0.895 |
k100 = 3.61 × 10−3 |
192 | ||||||||
Cyanidin-3-O-rutinoside |
0.953 |
k80 = 1.71 × 10−3 |
9.06 |
1 |
0.998 |
60–100 |
406 | |||
0.971 |
k60 = 0.83 × 10−3 |
834 | ||||||||
0.904 |
k100 = 6.32 × 10−3 |
110 | ||||||||
Delphinidin |
0.925 |
k80 = 2.44 × 10−3 |
7.91 |
1 |
0.914 |
60–100 |
284 | |||
0.902 |
k60 = 1.73 × 10−3 |
401 | ||||||||
0.923 |
k100 = 5.93 × 10−3 |
117 | ||||||||
Cyanidin |
0.913 |
k80 = 2.17 × 10−3 |
7.12 |
1 |
0.829 |
60–100 |
319 | |||
0.901 |
k60 = 1.84 × 10−3 |
377 | ||||||||
0.927 |
k100 = 7.18 × 10−3 |
97 | ||||||||
Pelargonidin |
0.929 |
k80 = 3.46 × 10−3 |
5.59 |
1 |
0.874 |
60–100 |
200 | |||
0.903 |
k60 = 2.87 × 10−3 |
242 | ||||||||
0.886 |
k100 = 4.12 × 10−3 |
168 | ||||||||
Total |
0.907 |
k80 = 1.26 × 10−3 |
10.77 |
1 |
0.948 |
60–100 |
550 | |||
0.963 |
k60 = 0.71 × 10−3 |
978 | ||||||||
pH 4.0 |
0.948 |
k100 = 3.16 × 10−3 |
219 | |||||||
Cyanidin-3-O-glucoside |
0.894 |
k80 = 2.47 × 10−3 |
5.47 |
1 |
0.954 |
60–100 |
281 | |||
0.943 |
k60 = 1.31 × 10−3 |
529 | ||||||||
0.925 |
k100 = 4.84 × 10−3 |
143 | ||||||||
Cyanidin-3-O-rutinoside |
0.925 |
k80 = 2.82 × 10−3 |
8.58 |
1 |
0.991 |
60–100 |
246 | |||
0.953 |
k60 = 1.21 × 10−3 |
573 | ||||||||
0.902 |
k100 = 9.71 × 10−3 |
71 |
Loypimai et al. (2016) |
|||||||
Delphinidin |
0.941 |
k80 = 4.75 × 10−3 |
8.46 |
1 |
0.997 |
60–100 |
146 |
|||
0.924 |
k60 = 2.46 × 10−3 |
282 | ||||||||
0.899 |
k100 = 7.26 × 10−3 |
95 | ||||||||
Cyanidin |
0.929 |
k80 = 3.12 × 10−3 |
6.09 |
1 |
0.840 |
60–100 |
222 | |||
0.914 |
k60 = 2.67 × 10−3 |
260 | ||||||||
0.933 |
k100 = 9.45 × 10−3 |
73 | ||||||||
Pelargonidin |
0.900 |
k80 = 7.76 × 10−3 |
6.26 |
1 |
0.910 |
60–100 |
89 | |||
0.865 |
k60 = 3.46 × 10−3 |
200 | ||||||||
0.876 |
k100 = 4.87 × 10−3 |
142 | ||||||||
Total |
0.951 |
k80 = 3.67 × 10−3 |
5.04 |
1 |
0.980 |
60–100 |
189 | |||
0.951 |
k60 = 2.16 × 10−3 |
321 | ||||||||
pH 5.0 |
0.897 |
k100 = 4.73 × 10−3 |
147 | |||||||
Cyanidin-3-O-glucoside |
0.885 |
k80 = 3.85 × 10−3 |
7.55 |
1 |
0.894 |
60–100 |
180 | |||
0.922 |
k60 = 1.41 × 10−3 |
492 | ||||||||
0.884 |
k100 = 7.33 × 10−3 |
95 | ||||||||
Cyanidin-3-O-rutinoside |
0.921 |
k80 = 5.18 × 10−3 |
6.83 |
1 |
0.969 |
60–100 |
134 | |||
0.930 |
k60 = 2.44 × 10−3 |
284 | ||||||||
0.918 |
k100 = 18.8 × 10−3 |
37 | ||||||||
Delphinidin |
0.944 |
k80 = 7.51 × 10−3 |
6.98 |
1 |
0.871 |
60–100 |
92 | |||
0.922 |
k60 = 5.98 × 10−3 |
116 | ||||||||
0.921 |
k100 = 15.2 × 10−3 |
46 | ||||||||
Cyanidin |
0.894 |
k80 = 5.87 × 10−3 |
7.61 |
1 |
0.896 |
60–100 |
118 | |||
0.903 |
k60 = 4.37 × 10−3 |
159 | ||||||||
0.887 |
k100 = 16.1 × 10−3 |
43 | ||||||||
Pelargonidin |
0.911 |
k80 = 10.4 × 10−3 |
5.38 |
1 |
0.999 |
60–100 |
67 | |||
0.904 |
k60 = 6.73 × 10−3 |
103 | ||||||||
0.989 |
k100 = 1.23 × 10−3 |
56 |
Loypimai et al. (2016) |
|||||||
Total |
0.908 |
k80 = 8.59 × 10−3 |
5.16 |
1 |
0.998 |
60–100 |
81 |
|||
0.925 |
k60 = 5.34 × 10−3 |
130 | ||||||||
pH 2.0 |
0.950 |
k100 = 4.30 × 10−3 |
161 | |||||||
Δ L |
3 g extract/1 L 2.0M acetate buffer/pH adjust |
0.980 |
k80 = 3.27 × 10−3 |
6.43 |
1 |
0.947 |
60–100 |
212 | ||
0.967 |
k60 = 1.53 × 10−3 |
453 | ||||||||
0.989 |
k100 = 7.12 × 10−3 |
97 | ||||||||
Δ C |
Heat: waterbath/capped 15 ml brown glass vials 0–120 min (7 pts) |
0.960 |
k80 = 5.55 × 10−3 |
5.52 |
1 |
0.954 |
60–100 |
125 | ||
0.975 |
k60 = 2.93 × 10−3 |
237 | ||||||||
0.980 |
k100 = 1.79 × 10−3 |
387 | ||||||||
Δ h |
0.973 |
k80 = 1.51 × 10−3 |
3.55 |
1 |
0.962 |
60–100 |
459 | |||
0.936 |
k60 = 1.01 × 10−3 |
686 | ||||||||
pH 3.0 |
0.920 |
k100 = 6.64 × 10−3 |
104 | |||||||
Δ L |
0.919 |
k80 = 5.54 × 10−3 |
4.93 |
1 |
0.929 |
60–100 |
125 | |||
0.944 |
k60 = 3.01 × 10−3 |
230 | ||||||||
0.968 |
k100 = 16.1 × 10−3 |
43 | ||||||||
Δ C |
0.986 |
k80 = 9.82 × 10−3 |
9.34 |
1 |
0.974 |
60–100 |
71 | |||
Analysis: Hunterlab CIELAB |
0.913 |
k60 = 3.57 × 10−3 |
194 | |||||||
0.978 |
k100 = 3.74 × 10−3 |
185 | ||||||||
Δ h |
0.977 |
k80 = 2.37 × 10−3 |
6.11 |
1 |
1.000 |
60–100 |
292 | |||
0.968 |
k60 = 1.39 × 10−3 |
499 | ||||||||
pH 4.0 |
0.963 |
k100 = 8.65 × 10−3 |
80 | |||||||
Δ L |
L = lightness |
0.982 |
k80 = 7.73 × 10−3 |
3.76 |
1 |
0.904 |
60–100 |
90 | ||
0.909 |
k60 = 4.73 × 10−3 |
147 | ||||||||
0.922 |
k100 = 17.1 × 10−3 |
41 | ||||||||
Δ C |
C = chroma |
0.913 |
k80 = 11.3 × 10−3 |
4.99 |
1 |
0.998 |
60–100 |
61 | ||
0.925 |
k60 = 7.61 × 10−3 |
91 | ||||||||
0.957 |
k100 = 2.38 × 10−3 |
291 | ||||||||
Δ h |
h = hue angle |
0.984 |
k80 = 2.20 × 10−3 |
1.56 |
1 |
0.968 |
60–100 |
315 | ||
0.973 |
k60 = 1.85 × 10−3 |
375 | ||||||||
pH 5.0 |
0.894 |
k100 = 9.28 × 10−3 |
75 | |||||||
Δ L |
0.926 |
k80 = 9.15 × 10−3 |
0.37 |
1 |
0.934 |
60–100 |
76 | |||
0.903 |
k60 = 8.75 × 10−3 |
79 | ||||||||
0.908 |
k100 = 24.8 × 10−3 |
28 | ||||||||
Δ C |
0.955 |
k80 = 15.2 × 10−3 |
6.73 |
1 |
0.999 |
60–100 |
46 | |||
0.930 |
k60 = 8.34 × 10−3 |
83 | ||||||||
0.913 |
k100 = 4.43 × 10−3 |
156 |
Loypimai et al. (2016) |
|||||||
Δ h |
0.972 |
k80 = 2.81 × 10−3 |
3.24 |
1 |
0.833 |
60–100 |
247 |
|||
0.940 |
k60 = 2.60 × 10−3 |
267 | ||||||||
Anthocyanins |
Luna-Vital et al., 2017 |
|||||||||
Purple corn |
pH |
ASE 300 Extraction: | ||||||||
PCW |
2.0 |
50C/5 min° |
– |
k22 = 2.62 × 10−5 |
2.65 × 10−4 | |||||
(purple corn water extraction) |
2.5 |
Cell pressure: |
– |
k22 = 1.92 × 10−5 |
3.61 × 10−4 | |||||
3.0 |
1500 psi |
– |
k22 = 1.24 × 10−5 |
5.60 × 10−4 | ||||||
3.5 |
N2 purge/resin filtra-tion/vacuum eva-poration/freeze dried |
– |
k22 = 1.06 × 10−5 |
– |
1 |
– |
22 |
6.54 × 10−4 | ||
4.0 |
– |
k22 = 0.752 × 10−5 |
9.22 × 10−4 | |||||||
5.0 |
– |
k22 = 0.451 × 10−5 |
15.4 × 10−4 | |||||||
6.0 |
– |
k22 = 0.157 × 10−5 |
44.2 × 10−4 | |||||||
EA |
2.0 |
EA |
– |
k22 = 0.124 × 10−5 |
55.9 × 10−4 | |||||
(purple corn prepurified – water extract) |
2.5 |
Further partition/w/water, ethyl acetate |
– |
k22 = 0.203 × 10−5 |
34.1 × 10−4 | |||||
3.0 |
– |
k22 = 0.330 × 10−5 |
21.0 × 10−4 | |||||||
3.5 |
– |
k22 = 0.578 × 10−5 |
– |
1 |
– |
22 |
12.0 × 10−4 | |||
4.0 |
– |
k22 = 0.692 × 10−5 |
10.0 × 10−4 | |||||||
5.0 |
– |
k22 = 1.12 × 10−5 |
6.22 × 10−4 | |||||||
6.0 |
– |
k22 = 2.33 × 10−5 |
2.98 × 10−4 | |||||||
F1 |
2.0 |
F1/F2 |
– |
k22 = 0.159 × 10−5 |
43.4 × 10−4 | |||||
(purple corn extract/w/condensed forms) |
2.5 |
Ethyl acetate phase |
– |
k22 = 0.259 × 10−5 |
26.8 × 10−4 | |||||
3.0 |
– |
k22 = 0.555 × 10−5 |
12.5 × 10−4 | |||||||
3.5 |
– |
k22 = 1.01 × 10−5 |
– |
1 |
– |
22 |
6.84 × 10−4 | |||
4.0 |
– |
k22 = 2.48 × 10−5 |
2.79 × 10−4 | |||||||
5.0 |
– |
k22 = 2.09 × 10−5 |
3.32 × 10−4 | |||||||
6.0 |
– |
k22 = 5.52 × 10−5 |
1.26 × 10−4 | |||||||
F2 |
2.0 |
– |
k22 = 0.137 × 10−5 |
50.6 × 10−4 |
Luna-Vital et al. (2017) |
|||||
(purple corn extract w/o condensed forms) |
2.5 |
Assay: |
– |
k22 = 1.22 × 10−5 |
5.66 × 10−4 |
|||||
3.0 |
– |
k22 = 0.431 × 10−5 |
16.1 × 10−4 | |||||||
3.5 |
– |
k22 = 0.581 × 10−5 |
– |
1 |
– |
22 |
11.9 × 10−4 | |||
4.0 |
– |
k22 = 0.819 × 10−5 |
8.46 × 10−4 | |||||||
5.0 |
– |
k22 = 1.44 × 10−5 |
4.82 × 10−4 | |||||||
6.0 |
– |
k22 = 5.63 × 10−5 |
1.23 × 10−4 | |||||||
Anthocyanins |
||||||||||
Purple sweet potato (Ipomoea batatas) extract in soft drink model |
Li et al. (2014) |
|||||||||
Ascorbic acid: |
50 mg/L in 0.1M citric-sodium citric buffer (pH3) |
0.996 |
k90 = 14.4 × 10−4 |
481 | ||||||
0.996 |
k85 = 12.1 × 10−4 |
574 | ||||||||
0 mg/L |
Beverage model: |
0.996 |
k80 = 11.3 × 10−4 |
5.8 |
1 |
0.983 |
70–90 |
613 | ||
0.993 |
k75 = 10.0 × 10−4 |
692 | ||||||||
Per 1000 ml – 86 g sugar, |
0.999 |
k70 = 8.78 × 10−4 |
789 | |||||||
0.14 g Na-benzoate, 0.18 g |
0.997 |
k90 = 13.8 × 10−4 |
500 | |||||||
K-sorbate, 1.52 g citric acid, ascorbic acid |
0.997 |
k85 = 12.3 × 10−4 |
563 | |||||||
40 mg/L |
Heat: waterbath/capped 7 ml tubes/N2 headspace flush/wrapped/w/aluminum foil |
0.994 |
k80 = 10.3 × 10−4 |
7.5 |
1 |
0.997 |
70–90 |
672 | ||
0.999 |
k75 = 8.82 × 10−4 |
786 | ||||||||
0.994 |
k70 = 7.68 × 10−4 |
902 | ||||||||
0.986 |
k90 = 12.5 × 10−4 |
557 |
Li et al. (2014) |
|||||||
Cooled in ice bath to 25°C |
0.979 |
k85 = 11.0 × 10−4 |
633 | |||||||
120 mg/L |
0.971 |
k80 = 9.67 × 10−4 |
6.6 |
1 |
0.999 |
70–90 |
717 | |||
0.989 |
k75 = 8.47 × 10−4 |
819 | ||||||||
Assay: UV-VIS Absorbance at 527 nm |
0.986 |
k70 = 7.25 × 10−4 |
956 | |||||||
0.998 |
k90 = 15.7 × 10−4 |
441 | ||||||||
0.996 |
k85 = 14.3 × 10−4 |
485 | ||||||||
360 mg/L |
0.980 |
k80 = 13.1 × 10−4 |
6.1 |
1 |
0.968 |
70–90 |
530 | |||
0.994 |
k75 = 11.6 × 10−4 |
597 | ||||||||
0.988 |
k70 = 9.42 × 10−4 |
736 | ||||||||
Purple sweet potato (commercial pigment extract) |
Li et al. (2014) |
|||||||||
In: pH 3.0 Buffer | ||||||||||
50 mg/L in 0.1M citric-sodium citric buffer (pH3) |
0.997 |
k90 = 5.33 × 10−4 |
1.30 × 103 | |||||||
0.996 |
k85 = 4.87 × 10−4 |
1.42 × 103 | ||||||||
0.997 |
k80 = 4.37 × 10−4 |
3.9 |
1 |
0.961 |
70–90 |
1.59 × 103 | ||||
0.994 |
k75 = 4.05 × 10−4 |
1.71 × 103 | ||||||||
0.994 |
k70 = 3.93 × 10−4 |
1.76 × 103 | ||||||||
Purple sweet potato extract in soft drink model |
Li et al. (2014) |
|||||||||
Ascorbic acid (mg/L): | ||||||||||
0 |
50 mg/L in 0.1M citric-sodium citric buffer (pH3) |
0.998 |
k25 = 1.60 × 10−5 |
– |
1 |
– |
25 |
43.2 × 105 | ||
40 |
0.994 |
k25 = 1.85 × 10−5 |
– |
1 |
– |
25 |
37.5 × 105 | |||
120 |
0.998 |
k25 = 2.02 × 10−5 |
– |
1 |
– |
25 |
34.3 × 105 | |||
360 |
Beverage model: |
0.997 |
k25 = 2.62 × 10−5 |
– |
1 |
– |
25 |
26.5 × 105 | ||
(mg/L∙min) | ||||||||||
0 |
Per 1000 ml – 86 g sugar, 0.14 g Na-benzoate, 0.18 g K-sorbate, 1.52 g citric acid, ascorbic acid |
0.998 |
k4 = 2.63 × 10−4 |
– |
0 |
– |
4 |
1.90 × 105 | ||
40 |
0.999 |
k4 = 2.77 × 10−4 |
– |
0 |
– |
4 |
1.81 × 105 | |||
120 |
0.999 |
k4 = 2.85 × 10−4 |
– |
0 |
– |
4 |
1.76 × 105 | |||
360 |
0.999 |
k4 = 2.81 × 10−4 |
– |
0 |
– |
4 |
1.78 × 105 | |||
Anthocyanins |
Fernandez-Lopez et al. (2013) |
|||||||||
(commercial red pigment extracts) | ||||||||||
Elderberry |
Heat: waterbath/capped 100 × 14 mm id tubes 0–6 hr (8 pts) |
0.97 |
k90 = 10.0 × 10−4 |
693 | ||||||
(Sambucus nigra L.) |
0.99 |
k70 = 6.67 × 10−4 |
10.5 |
1 |
0.928 |
50–90 |
1040 | |||
0.99 |
k50 = 1.67 × 10−4 |
(3.7)a |
4159 | |||||||
Red cabbage |
500 mg/50 ml in 100 mM pH 5.5 cit-phos buffer |
0.98 |
k90 = 16.67 × 10−4 |
416 | ||||||
(Brassica oleracea L.) |
0.98 |
k70 = 10.0 × 10−4 |
7.0 |
1 |
0.997 |
50–90 |
693 | |||
0.99 |
k50 = 5.00 × 10−4 |
(6.3)a |
1386 | |||||||
Hibiscus |
Assay: UV-VIS Absorbance at 535 nm |
0.94 |
k90 = 43.3 × 10−4 |
160 | ||||||
(Hibiscus sabdariffa L.) |
0.97 |
k70 = 15.0 × 10−4 |
9.5 |
1 |
0.961 |
50–90 |
462 | |||
0.97 |
k50 = 8.33 × 10−4 |
(9.1)a |
832 | |||||||
Anthocyanins |
||||||||||
Chinese red radish (Oraphanus sativus L.) extract |
Liu et al. (2014) |
|||||||||
In: Apple juice |
0.822 |
k90 = 8.30 × 10−4 |
835 | |||||||
Conc: 0.1 g RRA/1 liter juice beverage |
0.868 |
k80 = 5.60 × 10−4 |
11.42 |
1 |
0.995 |
70–90 |
1238 | |||
0.927 |
k70 = 3.30 × 10−4 |
2100 | ||||||||
Grape juice |
(RRA = red radish anthocyanins) |
0.971 |
k90 = 11.5 × 10−4 |
603 | ||||||
0.926 |
k80 = 7.90 × 10−4 |
7.23 |
1 |
0.969 |
70–90 |
877 | ||||
0.872 |
k70 = 6.40 × 10−4 |
1083 | ||||||||
Peach juice |
6 ml plastic tubes capped/N2 flush/wrapped in aluminum foil |
0.952 |
k90 = 13.3 × 10−4 |
521 |
Liu et al. (2014) |
|||||
0.940 |
k80 = 10.2 × 10−4 |
6.60 |
1 |
1.000 |
70–90 |
680 | ||||
0.862 |
k70 = 7.80 × 10−4 |
889 | ||||||||
Pear juice |
0.989 |
k90 = 8.30 × 10−4 |
835 | |||||||
0.959 |
k80 = 6.70 × 10−4 |
10.38 |
1 |
0.935 |
70–90 |
1035 | ||||
0.967 |
k70 = 3.60 × 10−4 |
1925 | ||||||||
Pomegranate juice |
0.908 |
k90 = 12.7 × 10−4 |
546 | |||||||
0.942 |
k80 = 8.60 × 10−4 |
8.27 |
1 |
0.988 |
70–90 |
806 | ||||
0.928 |
k70 = 6.50 × 10−4 |
1066 | ||||||||
Lemon juice |
0.913 |
k90 = 11.5 × 10−4 |
603 | |||||||
0.946 |
k80 = 7.80 × 10−4 |
7.82 |
1 |
0.979 |
70–90 |
889 | ||||
0.912 |
k70 = 6.10 × 10−4 |
1136 | ||||||||
Chinese red radish (Oraphanus sativus L.) Extract | ||||||||||
In: Apple juice |
200 ml juice beverage in capped glass vials/N2 flush/aluminum foil wrapped |
0.992 |
k25 = 5.76 × 10−6 |
– |
1 |
– |
25 |
1.21 × 105 |
Liu et al. (2014) |
|
Grape juice |
0.999 |
k25 = 6.39 × 10−6 |
– |
1 |
– |
25 |
1.09 × 105 | |||
Peach juice |
0.998 |
k25 = 5.90 × 10−6 |
– |
1 |
– |
25 |
1.17 × 105 | |||
Pear juice |
0.972 |
k25 = 11.6 × 10−6 |
– |
1 |
– |
25 |
59.8 × 105 | |||
Pomegranate juice |
0.984 |
k25 = 5.76 × 10−6 |
– |
1 |
– |
25 |
1.20 × 105 | |||
Lemon juice |
Vials pasteurized 85°C/15 min/cooled/stored 4 weeks |
0.999 |
k25 = 6.25 × 10−6 |
– |
1 |
– |
25 |
1.11 × 105 | ||
mg/L∙min | ||||||||||
Apple juice |
0.997 |
k4 = 1.69 × 10−4 |
– |
0 |
– |
4 |
2.96 × 105 | |||
Grape juice |
0.999 |
k4 = 2.13 × 10−4 |
– |
0 |
– |
4 |
2.35 × 105 | |||
Peach juice |
Analysis: UV-VIS |
0.997 |
k4 = 2.65 × 10−4 |
– |
0 |
– |
4 |
1.88 × 105 | ||
Pear juice |
Absorbance: 520 nm |
0.997 |
k4 = 2.38 × 10−4 |
– |
0 |
– |
4 |
2.10 × 105 | ||
Pomegranate juice |
0.997 |
k4 = 1.09 × 10−4 |
– |
0 |
– |
4 |
4.59 × 105 | |||
Lemon juice |
0.997 |
k4 = 1.34 × 10−4 |
– |
0 |
– |
4 |
3.73 × 105 | |||
Strawberry Color | ||||||||||
Strawberry color – pH 3.7 |
– |
k140 = 7.32 |
0.0947 |
Rodrigo et al. (2007) |
||||||
L*∙a*/b* |
Wash, cut, homogenize, filter (nat. pH = 3.7) |
– |
k130 = 3.75 |
0.1848 |
||||||
– |
k120 = 2.55 |
16.2 |
1 |
0.991 |
100–140 |
0.2718 | ||||
Heat: 0–120 min |
– |
k110 = 1.55 |
0.4472 | |||||||
Inox tubes (5 mm ID × 100 mm) |
– |
k105 = 1.01 |
0.6863 | |||||||
– |
k100 = 0.857 |
0.8088 | ||||||||
Strawberry Color cont. - | ||||||||||
Strawberry color – pH 2.5 |
Rodrigo et al. (2007) |
|||||||||
L*∙a*/b* |
pH adjust/w/1.5M citric acid |
– |
k140 = 7.78 |
0.0891 |
||||||
– |
k130 = 3.26 |
0.2126 | ||||||||
– |
k120 = 1.63 |
20.7 |
1 |
0.977 |
100–140 |
0.4252 | ||||
– |
k110 = 0.781 |
0.8875 | ||||||||
– |
k100 = 0.536 |
1.2932 | ||||||||
Strawberry color – pH 5.0 |
– |
k140 = 9.91 |
0.0699 | |||||||
L*∙a*/b* |
pH adjust/w/1.0M Na-phosphate buffer |
– |
k120 = 5.57 |
12.9 |
1 |
0.966 |
100–140 |
0.1244 | ||
– |
k110 = 2.63 |
0.2636 | ||||||||
– |
k100 = 1.98 |
0.3501 | ||||||||
Betalains |
||||||||||
Beets |
Von Elbe et al. (1974) |
|||||||||
Beet puree |
Natural pH |
0.995 |
ak116 = 0.01419 |
a8.7 |
49 |
|||||
(Betanine) |
(electrophoretic separation) |
0.996 |
ak110 = 0.01219 |
(10 + 2)a |
1 |
0.996 |
102–116 |
57 | ||
0.950 |
ak102 = 0.009333 |
74 | ||||||||
Beet juice | ||||||||||
(Betanine) |
pH 3.0 |
– |
k100 = 0.079 |
– |
1 |
– |
100 |
8.8 | ||
pH 5.0 |
– |
k100 = 0.024 |
– |
1 |
– |
100 |
29.0 | |||
pH 7.0 |
– |
k100 = 0.135 |
– |
1 |
– |
100 |
5.1 | |||
Betanine solution |
pH 3.0 |
– |
k100 = 0.094 |
– |
1 |
– |
100 |
7.4 | ||
(citric-phosphate buffer) |
pH 4.0 |
– |
k100 = 0.051 |
– |
1 |
– |
100 |
13.6 | ||
pH 5.0 |
– |
k100 = 0.048 |
– |
1 |
– |
– |
14.4 | |||
pH 5.0 |
– |
k75 = 0.0078 |
a12.6 |
1 |
0.976 |
25–100 |
89.0 | |||
pH 5.0 |
– |
k50 = 0.0022 |
10.5 |
1 |
0.998 |
25–75 |
315 | |||
pH 5.0 |
– |
k25 = 0.00061 |
14.7 |
1 |
0.979 |
50–100 |
1136 | |||
pH 6.0 |
– |
k100 = 0.079 |
– |
1 |
– |
100 |
8.8 | |||
pH 7.0 |
– |
k100 = 0.118 |
– |
1 |
– |
– |
5.9 | |||
pH 7.0 |
– |
k75 = 0.035 |
a8.5 |
1 |
0.974 |
25–100 |
20.0 | |||
pH 7.0 |
– |
k50 = 0.0138 |
7.1 |
1 |
0.992 |
25–75 |
50.0 | |||
pH 7.0 |
– |
k25 = 0.0062 |
10.1 |
1 |
0.986 |
50–100 |
112 | |||
Beet powder |
Kopelman and Saguy (1977) |
|||||||||
Betanine |
Drum-dried |
– |
k45 = 3.04 × 10−6 |
2.28 × 105 |
||||||
Dry powders sealed in glass vials: |
(4% MC) |
– |
k40 = 2.65 × 10−6 |
2.62 × 105 | ||||||
– |
k35 = 2.37 × 10−6 |
5.9 |
1 |
0.992 |
25–45 |
2.92 × 105 | ||||
– |
k31 = 1.99 × 10−6 |
3.48 × 105 | ||||||||
– |
k25 = 1.63 × 10−6 |
4.25 × 105 | ||||||||
Air-dried |
– |
k45 = 3.49 × 10−6 |
1.99 × 105 | |||||||
(4% MC) |
– |
k40 = 3.28 × 10−6 |
2.11 × 105 | |||||||
– |
k35 = 2.79 × 10−6 |
6.6 |
1 |
0.949 |
25–45 |
2.48 × 105 | ||||
– |
k31 = 2.10 × 10−6 |
3.30 × 105 | ||||||||
– |
k25 = 1.84 × 10−6 |
3.77 × 105 | ||||||||
Vulgaxanthin |
Drum-dried |
– |
k45 = 3.01 × 10−6 |
2.30 × 105 |
Kopelman and Saguy (1977) |
|||||
(4% MC) |
– |
k40 = 2.68 × 10−6 |
2.59 × 105 |
|||||||
– |
k35 = 2.19 × 10−6 |
5.6 |
1 |
0.935 |
25–45 |
3.17 × 105 | ||||
– |
k31 = 1.80 × 10−6 |
3.85 × 105 | ||||||||
– |
k25 = 1.75 × 10−6 |
3.96 × 105 | ||||||||
Vulgaxanthin cont. – |
Air-dried |
– |
k45 = 3.23 × 10−6 |
2.15 × 105 | ||||||
(4% MC) |
– |
k40 = 2.90 × 10−6 |
2.39 × 105 | |||||||
– |
k35 = 2.38 × 10−6 |
6.5 |
1 |
0.986 |
25–45 |
2.91 × 105 | ||||
– |
k31 = 1.96 × 10−6 |
3.54 × 105 | ||||||||
– |
k25 = 1.67 × 10−6 |
4.15 × 105 | ||||||||
Beet powder |
Freeze-dried/ground/rehumidified to 0.75 aw |
Cohen and Saguy (1983) |
||||||||
Betanine |
g H2O/100 g solids | |||||||||
No additives: |
25.8 |
0.982 |
k35 = 5.80 × 10−5 |
– |
1 |
– |
35 |
1.20 × 104 | ||
Beet:CMC (3:1) |
20.1 |
0.984 |
k35 = 5.35 × 10−5 |
– |
1 |
– |
35 |
1.30 × 104 | ||
Beet:CMC (1:1) |
14.9 |
0.984 |
k35 = 2.92 × 10−5 |
– |
1 |
– |
35 |
2.37 × 104 | ||
Beet:pectin (1:1) |
13.6 |
0.992 |
k35 = 3.01 × 10−5 |
– |
1 |
– |
35 |
2.30 × 104 | ||
Vulgaxanthin-I |
g H2O/100 g solids | |||||||||
No additives: |
25.8 |
0.986 |
k35 = 4.47 × 10−5 |
– |
1 |
– |
35 |
1.55 × 104 | ||
Beet:CMC (3:1) |
20.1 |
0.972 |
k35 = 4.04 × 10−5 |
– |
1 |
– |
35 |
1.72 × 104 | ||
Beet:CMC (1:1) |
14.9 |
0.992 |
k35 = 2.45 × 10−5 |
– |
1 |
– |
35 |
2.83 × 104 | ||
Beet:pectin (1:1) |
13.6 |
0.460 |
k35 = 0.150 × 10−5 |
– |
1 |
– |
35 |
13.86 × 104 | ||
Betalains | ||||||||||
Beet juice |
Saguy (1979) |
|||||||||
Betanine |
pH 4.8 |
– |
k100 = 0.113 |
6.2 | ||||||
– |
k85.5 = 0.0405 |
18.2 |
1 |
0.991 |
61.5–100 |
17.0 | ||||
– |
k75.5 = 0.0243 |
29.0 | ||||||||
– |
k61.5 = 0.0063 |
110 | ||||||||
pH 5.2 |
– |
k100 = 0.098 |
7.1 | |||||||
– |
k85.5 = 0.0374 |
18.6 |
1 |
0.999 |
61.5–100 |
19.0 | ||||
– |
k75.5 = 0.0165 |
42.0 | ||||||||
– |
k61.5 = 0.0056 |
124 | ||||||||
pH 5.8 |
– |
k100 = 0.0946 |
7.3 | |||||||
– |
k85.5 = 0.032 |
19.6 |
1 |
0.999 |
61.5–100 |
22.0 | ||||
– |
k75.5 = 0.0146 |
47.0 | ||||||||
– |
k61.5 = 0.0045 |
154 | ||||||||
pH 6.2 |
– |
k100 = 0.1177 |
5.9 | |||||||
– |
k85.5 = 0.0405 |
19.9 |
1 |
0.999 |
61.5–100 |
17.0 | ||||
– |
k75.5 = 0.0168 |
41.0 | ||||||||
– |
k61.5 = 0.0 055 |
126 | ||||||||
Vulgaxanthin-I |
pH 4.8 |
– |
k100 = 0.1337 |
5.2 | ||||||
– |
k85.5 = 0.056 |
15.4 |
1 |
0.997 |
61.5–100 |
12.0 | ||||
– |
k75.5 = 0.0341 |
20.0 | ||||||||
– |
k61.5 = 0.0119 |
58.0 | ||||||||
pH 5.2 |
– |
k100 = 0.1204 |
5.8 | |||||||
– |
k85.5 = 0.0497 |
16.4 |
1 |
0.999 |
61.5–100 |
14.0 | ||||
– |
k75.5 = 0.0251 |
28.0 | ||||||||
– |
k61.5 = 0.0095 |
73.0 | ||||||||
pH 5.8 |
– |
k100 = 0.1146 |
6.0 | |||||||
– |
k85.5 = 0.0456 |
16.5 |
1 |
0.999 |
61.5–100 |
15.0 | ||||
– |
k75.5 = 0.0234 |
30.0 | ||||||||
– |
k61.5 = 0.0088 |
79.0 | ||||||||
Vulgaxanthin-I |
pH 6.2 |
– |
k100 = 0.1239 |
5.6 |
Saguy (1979) |
|||||
– |
k85.5 = 0.0493 |
16.9 |
1 |
0.999 |
61.5–100 |
14.0 | ||||
– |
k75.5 = 0.0234 |
30.0 | ||||||||
– |
k61.5 = 0.0091 |
76.0 | ||||||||
Beet slices |
Partially freeze-dried/rehumidified |
Saguy et al. (1980) |
||||||||
Betanine | ||||||||||
Moisture: |
g H2O/100 g solids | |||||||||
0.03 |
0.99 |
k90 = 0.00297 |
233 | |||||||
0.98 |
k80 = 0.00214 |
9.1 |
1 |
0.99 |
70–90 |
324 | ||||
0.98 |
k70 = 0.00142 |
(13.1)a |
488 | |||||||
0.41 |
0.99 |
k90 = 0.00397 |
175 | |||||||
0.98 |
k80 = 0.00283 |
10.4 |
1 |
0.99 |
70–90 |
245 | ||||
0.99 |
k70 = 0.00172 |
(14.9)a |
403 | |||||||
0.56 |
0.99 |
k90 = 0.00733 |
95 | |||||||
0.99 |
k80 = 0.00546 |
10.8 |
1 |
0.97 |
70–90 |
127 | ||||
0.98 |
k70 = 0.00306 |
(15.5)a |
227 | |||||||
4.26 |
0.99 |
k90 = 0.00872 |
79 | |||||||
0.98 |
k80 = 0.00659 |
11.3 |
1 |
0.96 |
70–90 |
105 | ||||
0.99 |
k70 = 0.0035 |
(16.2)a |
198 | |||||||
6.67 |
0.97 |
k90 = 0.00984 |
70 | |||||||
0.98 |
k80 = 0.0069 |
12.0 |
1 |
0.98 |
70–90 |
100 | ||||
0.98 |
k70 = 0.0037 |
(17.4)a |
187 | |||||||
Moisture: |
g H2O/100 g solids | |||||||||
Vulgaxanthin-I |
0.03 |
0.99 |
k90 = 0.00081 |
856 | ||||||
0.99 |
k80 = 0.00069 |
5.3 |
1 |
0.98 |
70–90 |
1005 | ||||
0.98 |
k70 = 0.00053 |
(7.3)a |
1308 | |||||||
0.41 |
0.99 |
k90 = 0.00194 |
357 | |||||||
0.98 |
k80 = 0.00096 |
10.4 |
1 |
0.86 |
70–90 |
722 | ||||
0.99 |
k70 = 0.00083 |
(15.0)a |
835 | |||||||
0.56 |
0.99 |
k90 = 0.00456 |
152 | |||||||
0.98 |
k80 = 0.00292 |
13.0 |
1 |
0.99 |
70–90 |
237 | ||||
0.99 |
k70 = 0.00159 |
(16.7)a |
436 | |||||||
Vulgaxanthin-I |
4.26 |
0.95 |
k90 = 0.00598 |
116 |
Saguy et al. (1980) |
|||||
0.97 |
k80 = 0.00336 |
13.4 |
1 |
0.99 |
70–90 |
206 | ||||
0.99 |
k70 = 0.00207 |
(18.8)a |
335 | |||||||
6.67 |
0.99 |
k90 = 0.00718 |
97 | |||||||
0.99 |
k80 = 0.00403 |
13.4 |
1 |
0.99 |
70–90 |
172 | ||||
0.98 |
k70 = 0.00243 |
(19.2)a |
285 | |||||||
Betalains | ||||||||||
Betanine → Betalamic acid |
pH 5.5/spectro-photometric |
– |
k86 = 0.0461 |
15 |
Saguy et al. (1978c) |
|||||
k81 = 0.0296 |
20.4 |
1 |
0.999 |
60–86 |
23 |
|||||
Amax = 535 nm |
– |
k75 = 0.0175 |
(20.4)a |
40 | ||||||
– |
k60 = 0.0049 |
141 | ||||||||
Betalamic acid → Betalamic acid brown compounds |
– |
k86 = 0.00341 |
203 | |||||||
– |
k81 = 0.00261 |
20.3 |
1 |
0.909 |
60–86 |
266 | ||||
pH 5.5 |
– |
k75 = 0.00081 |
(20.7)a |
856 | ||||||
Amax = 430 nm |
– |
k60 = 0.0039 |
178 | |||||||
Betanine |
0.1M citrate-phosphate buffer: pH 5.0 |
Huang and von Elbe (1985) |
||||||||
Forward reaction: |
2-ml glass vials, in N2 atmos. |
– |
ak90 = 6.3 + 0.3 |
0.11 |
||||||
– |
k85 = 4.5 + 0.2 |
17.9 |
1 |
0.999 |
65–90 |
0.15 | ||||
– |
k75 = 2.1 + 0.1 |
(17.3)a |
0.33 | |||||||
– |
k65 = 1.01 + 0.05 |
0.69 | ||||||||
Reverse reaction: |
– |
k90 = 86.7 |
0.0080 | |||||||
– |
k85 = 85.6 |
0.66 |
1 |
0.999 |
65–90 |
0.0081 | ||||
– |
k75 = 83.3 |
(0.64)a |
0.0083 | |||||||
– |
k65 = 81 |
0.0086 | ||||||||
Betalamic acid |
– |
k90 = 1.6 + 0.2 |
0.43 | |||||||
– |
k85 = 1.1 + 0.1 |
17.7 |
1 |
0.999 |
65–90 |
0.63 | ||||
– |
k75 = 0.53 + 0.06 |
(18.2)a |
1.30 | |||||||
– |
k65 = 0.26 + 0.02 |
2.70 | ||||||||
Cyclodopa-5-0-glycoside |
– |
k90 = 0.22 + 0.03 |
3.20 | |||||||
– |
k85 = 0.15 + 0.02 |
25.4 |
1 |
0.998 |
65–90 |
4.60 | ||||
– |
k75 = 0.048 + 0.005 |
(29)a |
14.00 | |||||||
– |
k65 = 0.017 + 0.002 |
41.00 | ||||||||
Betacyanins |
Fernandez-Lopez et al. (2013) |
|||||||||
Red beet |
0.91 |
k90 = 5.33 × 10−3 |
130 |
|||||||
(Beta vulgaris L.) |
0.91 |
k70 = 3.17 × 10−3 |
8.1 |
1 |
0.988 |
50–90 |
219 | |||
0.94 |
k50 = 1.33 × 10−3 |
(8.5)a |
520 | |||||||
Opuntia fruits (Prickly Pear) |
0.89 |
k90 = 15.2 × 10−3 |
46 | |||||||
(Opuntia stricta) |
0.90 |
k70 = 5.83 × 10−3 |
12.9 |
1 |
0.998 |
50–90 |
119 | |||
0.90 |
k50 = 1.67 × 10−3 |
(12.8)a |
416 | |||||||
Betalains |
Pigment extracted and concentrated solution in pH 5.0 phosphate buffer |
Attoe and von Elbe (1981) |
||||||||
Cranberries | ||||||||||
Betanine |
No light |
– |
k55 = 0.00368 |
188 | ||||||
– |
k40 = 0.000642 |
25.1 |
1 |
0.999 |
25–55 |
1,080 | ||||
– |
k25 = 0.0000765 |
9,060 | ||||||||
With light |
– |
k55 = 0.00468 |
148 | |||||||
(400 ft-c) |
– |
k40 = 0.00117 |
19.3 |
1 |
0.999 |
25–55 |
592 | |||
– |
k25 = 0.000238 |
2,910 | ||||||||
Prickly pear fruit |
10-ml aqueous solution of extracted pigment |
Merin et al. (1987) |
||||||||
Betacyanine | ||||||||||
Dilute |
– |
k90 = 0.05711 |
15.7 |
pseudo-1 |
0.973 |
50–90 |
12.1 | |||
– |
k70 = 0.01076 |
(7.7)a |
64.4 | |||||||
– |
k50 = 0.0038 |
182.4 | ||||||||
Concentrated |
– |
k90 = 0.0299 |
21.9 |
pseudo-1 |
0.992 |
50–90 |
23.2 | |||
(× 10) |
– |
k70 = 0.0069 |
(10.7)a |
100.4 | ||||||
– |
k50 = 0.0007 |
990.0 | ||||||||
Carotenoids (as pigment) | ||||||||||
Blue crab |
Himelbloom et al. (1983) |
|||||||||
Astaxanthin |
XS-water cook color measured by a-value (colorimeter) |
– |
k100 = 3.47 |
0.20 |
||||||
– |
k93.9 = 2.853 |
0.24 | ||||||||
– |
k87.8 = 1.051 |
22.5 |
1 |
0.941 |
76.6–100 |
0.66 | ||||
– |
k82.2 = 0.7674 |
0.90 | ||||||||
– |
k76.6 = 0.5377 |
1.29 | ||||||||
Paprika |
Ramakrishnan and Francis (1973) |
|||||||||
(Total carotenoids) |
0.998 |
k125 = 0.003786 |
– |
1 |
– |
125–150 |
183 |
|||
Carotenoids (as pigment) | ||||||||||
Salmon |
Freeze-dried/rehydrated |
Martinez and Labuza (1968) |
||||||||
Astacene |
aw = 0 |
– |
k37 = 1.83 × 10−5 |
3.79 × 104 |
||||||
aw = 0.11 |
– |
k37 = 1.67 × 10−5 |
– |
1 |
– |
37 |
4.15 × 104 | |||
aw = 0.32 |
– |
k37 = 0.83 × 10−5 |
8.35 × 104 | |||||||
aw = 0.40 |
– |
k37 = 0.17 × 10−5 |
40.77 × 104 | |||||||
Tomato juice |
Heat: 0–7 min |
0.896 |
k130 = 0.024105 |
28.8 |
Miki & Akatsu (1970) (from Shi & LeMaguer (2000a)) |
|||||
Lycopene loss |
0.885 |
k127 = 0.020146 |
34.4 |
|||||||
0.884 |
k124 = 0.017068 |
40.6 |
||||||||
0.882 |
k121 = 0.014357 |
48.3 | ||||||||
0.683 |
k118 = 0.01068 |
21.2 |
1 |
0.977 |
90–130 |
64.9 | ||||
0.917 |
k115 = 0.009462 |
73.3 | ||||||||
0.822 |
k110 = 0.005581 |
124.2 | ||||||||
0.756 |
k100 = 0.002107 |
329.0 | ||||||||
0.855 |
k90 = 0.001647 |
420.9 | ||||||||
Tomato paste |
Barreiro et al. (1997) |
|||||||||
Overall color change |
Color measure: | |||||||||
(Lycopene) |
Gardner XL-23 | |||||||||
∆E |
0.992 |
k100 = 0.458 |
10.20 |
0 |
0.977 |
70–100 |
1.51 | |||
9 ml glass vials/70, 80, 90, 100°C/5–90 min |
0.991 |
k70 = 0.122 |
5.68 | |||||||
L-value: phase 1 |
0.986 |
k100 = 0.015 |
11.50 |
1 |
0.996 |
70–100 |
46.20 | |||
0.988 |
k70 = 0.0036 |
192.54 | ||||||||
Effect of color parameter on determination of reaction order and Ea |
L-value: phase 2 |
0.960 |
k100 = 0.00146 |
5.73 |
1 |
0.979 |
70–100 |
474.76 | ||
0.968 |
k70 = 0.000762 |
909.64 | ||||||||
a-value |
0.996 |
k100 = 0.0172 |
9.79 |
apparent 1 |
0.983 |
70–100 |
40.30 | |||
0.979 |
k70 = 0.005 |
138.63 | ||||||||
b-value |
0.958 |
k100 = 0.00321 |
20.50 |
apparent 1 |
0.952 |
70–100 |
215.93 | |||
0.902 |
k70 = 0.00024 |
2888.11 | ||||||||
Tomato paste |
a/b |
0.964 |
k100 = 0.011 |
6.86 |
apparent 1 |
0.986 |
70–100 |
69.31 |
Barreiro et al. (1997) |
|
0.962 |
k70 = 0.0046 |
150.68 |
||||||||
hue angle |
0.960 |
k100 = 0.00924 |
7.57 |
apparent 1 |
0.993 |
70–100 |
75.02 | |||
0.966 |
k70 = 0.00384 |
180.51 | ||||||||
SI |
0.998 |
k100 = 0.0144 |
10.10 |
apparent 1 |
0.989 |
70–100 |
48.14 | |||
0.986 |
k70 = 0.00406 |
170.73 | ||||||||
Carotenoids | ||||||||||
Tomato peel |
Kaur et al. (2006) |
|||||||||
Lycopene |
Peel air-dried |
0.9985 |
k100 = 10.4 × 10−4 |
666 | ||||||
25 g samples in petri dishes |
0.9967 |
k90 = 8.52 × 10−4 |
813 | |||||||
Heat: up to 10 hrs. |
0.9976 |
k80 = 7.30 × 10−4 |
4.4 |
1 |
0.995 |
50–100 |
949 | |||
0.9988 |
k70 = 5.92 × 10−4 |
1172 | ||||||||
0.9972 |
k60 = 5.20 × 10−4 |
1333 | ||||||||
Extraction: |
0.9985 |
k50 = 4.06 × 10−4 |
1706 | |||||||
Color (a × b) |
hexane:acetone:alcohol |
0.9962 |
k100 = 5.75 × 10−4 |
1205 | ||||||
(2:1:1) |
0.9954 |
k90 = 4.62 × 10−4 |
1502 | |||||||
Analysis: UV-VIS |
0.9952 |
k80 = 3.54 × 10−4 |
6.9 |
1 |
0.993 |
50–100 |
1957 | |||
A503 |
0.9942 |
k70 = 2.84 × 10−4 |
2438 | |||||||
Hunterlab |
0.9915 |
k60 = 1.84 × 10−4 |
Lycopene-Color rate constant correlation: |
3760 | ||||||
0.9949 |
k50 = 1.38 × 10−4 |
0.984 |
5041 | |||||||
Carotenoids | ||||||||||
Tomato pomace |
Aw |
Raw pomace |
Lavelli et al. (2011) |
|||||||
Lycopene |
0.17 |
Washed, cut, screw extractor, dispersed in 1% citric acid, seeds separated, freeze dried |
– |
k30 = 11.8 × 10−6 |
0.587 × 10−5 |
|||||
0.22 |
– |
k30 = 6.94 × 10−6 |
0.998 × 10−5 | |||||||
0.32 |
– |
k30 = 4.86 × 10−6 |
– |
1 |
– |
30 |
1.43 × 10−5 | |||
0.56 |
– |
k30 = 4.17 × 10−6 |
1.66 × 10−5 | |||||||
0.75 |
– |
k30 = 3.47 × 10−6 |
2.00 × 10−5 | |||||||
Tomato pomace |
Aw |
Raw pomace | ||||||||
β-carotene |
0.17 |
– |
k30 = 11.1 × 10−6 |
0.624 × 10−5 | ||||||
0.22 |
– |
k30 = 10.4 × 10−6 |
0.665 × 10−5 | |||||||
0.32 |
Analysis: HPLC |
– |
k30 = 10.4 × 10−6 |
– |
1 |
– |
30 |
0.665 × 10−5 | ||
0.56 |
– |
k30 = 15.3 × 10−6 |
0.454 × 10−5 | |||||||
0.75 |
– |
k30 = 11.8 × 10−6 |
0.587 × 10−5 | |||||||
Rutin |
0.75 |
Raw pomace |
– |
k30 = 4.58 × 10−6 |
1.51 × 10−5 | |||||
Chlorogenic acid |
0.75 |
– |
k30 = 1.94 × 10−6 |
3.56 × 10−5 | ||||||
Carotenoids | ||||||||||
Tomato pomace |
Aw |
Heated pomace |
Lavelli et al. (2011) |
|||||||
Lycopene |
0.17 |
Washed, cut, heat (3 h/100°C), screw extractor, dispersed in 1% citric acid, seeds separated, freeze dried. |
– |
k30 = 13.2 × 10−6 |
0.525 × 10−5 |
|||||
0.22 |
– |
k30 = 6.94 × 10−6 |
0.998 × 10−5 | |||||||
0.32 |
– |
k30 = 6.25 × 10−6 |
– |
1 |
– |
30 |
1.11 × 10−5 | |||
0.56 |
– |
k30 = 3.47 × 10−6 |
2.00 × 10−5 | |||||||
0.75 |
– |
k30 = 3.47 × 10−6 |
2.00 × 10−5 | |||||||
Tomato pomace |
Aw |
Heated pomace |
Lavelli et al. (2011) |
|||||||
β-carotene |
0.17 |
– |
k30 = 9.03 × 10−6 |
0.768 × 10−5 |
||||||
0.22 |
– |
k30 = 9.72 × 10−6 |
0.713 × 10−5 | |||||||
0.32 |
Analysis: HPLC |
– |
k30 = 8.33 × 10−6 |
– |
1 |
– |
30 |
0.832 × 10−5 | ||
0.56 |
– |
k30 = 6.25 × 10−6 |
1.11 × 10−5 | |||||||
0.75 |
– |
k30 = 6.94 × 10−6 |
0.998 × 10−5 | |||||||
Heated pomace | ||||||||||
Rutin |
0.75 |
– |
k30 = 1.18 × 10−6 |
5.87 × 10−5 | ||||||
Chlorogenic acid |
0.75 |
– |
k30 = 0.556 × 10−6 |
12.5 × 10−5 | ||||||
Tomato pulp |
Heat: 0–3 hr |
Cole & Kapur (1957b) (from Shi & LeMaguer (2000b) |
||||||||
Lycopene loss |
Dark/CO2 |
0.633 |
k100 = 0.0002635 |
– |
1 |
– |
100 |
2631.0 |
||
Dark/O2 |
0.986 |
k100 = 0.00198997 |
– |
1 |
– |
100 |
348.3 |
|||
Light/CO2 |
0.978 |
k100 = 0.00065683 |
– |
1 |
– |
100 |
1055.0 |
|||
Light/O2 |
0.990 |
k100 = 0.00223662 |
– |
1 |
– |
100 |
309.9 | |||
Lycopene model |
Cole & Kapur (1957a) (from Shi & LeMaguer (2000)) |
|||||||||
(Hexane/light petroleum solution) |
Lycopene |
0.956 |
k100 = 0.00234117 |
– |
1 |
– |
100 |
296.1 |
||
0.950 |
k65 = 0.0016133 |
– |
1 |
– |
65 |
429.6 |
||||
Lycopene + Cu-stearate |
0.985 |
k100 = 0.0129717 |
– |
1 |
– |
100 |
53.4 |
|||
0.999 |
k65 = 0.0050983 |
– |
1 |
– |
65 |
136.0 | ||||
Carotenoids (color only) | ||||||||||
Tomato color |
Wash, cut, homogenize, filter, concentrated from 4 to 20Brix under vacuum |
– |
k140 = 8.63 |
0.0803 |
Rodrigo et al. (2007) |
|||||
L*∙a*/b* |
– |
k130 = 3.27 |
0.2120 | |||||||
– |
k125 = 1.87 |
0.3707 | ||||||||
Heat: 0–120 min |
– |
k120 = 1.29 |
30.1 |
1 |
0.990 |
100–140 |
0.5373 | |||
Inox tubes (5 mm ID × 100 mm)– |
– |
k115 = 0.784 |
0.8841 | |||||||
– |
k110 = 0.344 |
2.0150 | ||||||||
(Pressure experiments showed little change in color (0–700 MPa/65°C/60 min) |
– |
k105 = 0.268 |
2.5864 | |||||||
– |
k100 = 0.189 |
3.6674 | ||||||||
Carotenoids | ||||||||||
Tomato puree (fresh) |
Heat: |
Shi et al. (2003) |
||||||||
Lycopene |
90–150°C, up to 6 hr | |||||||||
all-trans-lycopene → mono & poly-cis isomers |
– |
k150 = 0.0146383 |
47.4 | |||||||
– |
k120 = 0.0071483 |
7.98 |
1 |
0.959 |
90–150 |
97.0 | ||||
– |
k110 = 0.00425 |
a(0.982) |
163.1 | |||||||
– |
k90 = 0.0032233 |
215.1 | ||||||||
cis isomers → oxidized by-products |
– |
k150 = 0.014455 |
48.0 | |||||||
– |
k120 = 0.005965 |
11.80 |
1 |
0.967 |
90–150 |
116.2 | ||||
– |
k110 = 0.00263333 |
a(0.891) |
263.2 | |||||||
– |
k90 = 0.001521667 |
455.5 | ||||||||
Carotenoids |
Shi et al. (2003) |
|||||||||
Tomato puree cont. – |
– |
k150 = 0.0257833 |
26.9 | |||||||
all-trans-lycopene → oxidized by-products |
– |
k120 = 0.01461667 |
7.00 |
1 |
0.996 |
90–150 |
47.4 | |||
– |
k110 = 0.0113833 |
a(1.507) |
60.9 | |||||||
– |
k90 = 0.0064833 |
106.9 | ||||||||
Tomato puree (fresh) |
Storage: | |||||||||
25°C/1–6 days | ||||||||||
Light: 400 µmol/m−2 s−1 | ||||||||||
all-trans-lycopene → mono & poly-cis isomers |
– |
k25 = 0.000057639 |
– |
1 |
– |
25 |
12025.7 | |||
cis isomers → oxidized by-products |
– |
k25 = 0.0027076 |
– |
1 |
– |
25 |
256.0 | |||
all-trans-lycopene → oxidized by-products |
– |
k25 = 0.00282639 |
– |
1 |
– |
25 |
245.2 | |||
Light: 500 µmol/m−2 s−1 | ||||||||||
all-trans-lycopene → mono & poly-cis isomers |
– |
k25 = 0.000083333 |
– |
1 |
– |
25 |
8317.8 | |||
cis isomers → oxidized by-pr |