Isoconversional kinetic study and accurate determination of lifetime properties for thermal and thermo-oxidative degradation processes of Aronia melanocarpa

INNFOO-01392; No of Pages 12 Innovative Food Science and Emerging Technologies xxx (2015) xxx–xxx

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Isoconversional kinetic study and accurate determination of lifetime properties for thermal and thermo-oxidative degradation processes of Aronia melanocarpa Bojan Janković a,⁎, Milena Marinović-Cincović b,c, Marija Janković b,c a b c

Faculty of Physical Chemistry, Department for Dynamics and Matter Structure, University of Belgrade, Studentski trg 12-16, PO Box 137, Belgrade, RS 11001, Serbia Laboratory for Radiation Chemistry and Physics, Institute of Nuclear Sciences “Vinča,” University of Belgrade, Mike Petrovića Alasa 12-14, PO Box 522, Belgrade, RS, 11001 Serbia Institute of Nuclear Sciences “Vinča,” Radiation and Environmental Protection Department, University of Belgrade, Mike Petrovića Alasa 12-14, PO Box 522, Belgrade, RS 11001, Serbia

a r t i c l e

i n f o

Article history: Received 15 July 2015 Received in revised form 7 October 2015 Accepted 23 October 2015 Available online xxxx Keywords: Thermo-oxidative degradation Phenolic compounds Autocatalytic mechanisms Kinetic predictions Lifetime analysis Chemical compounds studied in this article: Cyanidin 3-glucoside (Chrysontemin) (PubChem CID: 197,081) Cyanidin-3-glucosylrutinoside (PubChem CID: 76,322,875) Chlorogenic acid (PubChem CID: 1,794,427) Neochlorogenic acid (PubChem CID: 5,280,633)

a b s t r a c t Isoconversional analysis and accurate determination of lifetime properties for thermal and thermo-oxidative degradation processes of Aronia melanocarpa were examined. The Šesták–Berggren (SB) autocatalytic model was found as best model to describe degradation process of A. melanocarpa in inert atmosphere. It has been found that autocatalysis may occur from inevitable presence of water probably through the hydrolysis. In the case of thermo-oxidative degradation, it was found that main mechanistic scheme can be presented with two different forms of reaction mechanism function, such as nth-order reaction model (with n N 1) and SB autocatalytic model. It was determined that neochlorogenic acid represents main compound, which has a strong hydrogen-donating activity. Based on lifetime analysis, it was found that in oxidative conditions, A. melanocarpa shows greater resistance to temperature variations, which correspond to storage conditions and where degradation mechanism greatly affects stability and physico-chemical characteristics of its constituents. Industrial relevance: Current research has a direct industrial application during the testing of “responses” of black chokeberry—A. melanocarpa fresh samples on the various thermal stresses in the inert and oxidative reaction conditions. Knowledge of the exact mechanism of degradation (referring to precisely defined reaction pathways) of A. melanocarpa in different reaction atmospheres enables us the targeting an exactly isolated chemical compounds in A. melanocarpa fresh samples, which are responsible for antioxidant protection of human tissue and plasma. The results presented in this paper can be guidelines for the application of industrial processes for precise allocations of these compounds and their further testing for the treatment of malignant diseases. The importance of this research also comes down to the fact that 25% of total polyphenols in chokeberry fruits are anthocyanins, which represent the powerful antioxidants in vitro. Also, the current work provides a specific approach in accurate determination of lifetime properties of A. melanocarpa samples, which is very important in terms of checking the behavior of tested fruit berry system on the temperature variations during storage periods. © 2015 Elsevier Ltd. All rights reserved.

1. Introduction Phenolic compounds found in plant extracts exhibit many beneficial effects on living organisms due mostly to their antioxidant properties (Banerjee, Kunwar, Mishra, & Priyadarsini, 2008; Caillet et al., 2007; Naruszewicz, Łaniewska, Millo, & Dłužniewski, 2007; Teleszko & Wojdyło, 2015; Wong, Leong, & Koh, 2006). They are excellent as free radical scavengers including those in the form of the reactive forms of oxygen (Pajk, Rezar, Levart, & Salobir, 2006). The radicals are the products of metabolic reactions within the living organism and are also formed in the external medium, e.g., by the electromagnetic radiation. A high concentration of free radicals within an organism developed as a result of faulty action of natural protective mechanisms leads to

⁎ Corresponding author. Tel./fax: +381 11 2187 133. E-mail address: [email protected] (B. Janković).

oxidative stress that result in many dysfunctions at molecular and cellular levels, which underlie many serious diseases. An exposed and very important site of attack of free radicals is the biological membrane. Oxidation of membrane lipids by free radicals causes disturbances in the structure and impairs functions of the biological membrane and leads to pathological changes within organism (Lobo, Patil, Phatak, & Chandra, 2010). The toxic effect of free radicals can be reduced or eliminated by consuming adequate amounts of phenolic compounds found in fruits and vegetables. Studies have shown that polyphenolic compounds of plant extracts posses also numerous therapeutic properties aside of the antioxidant ones (Andersen, Fossen, Torskangerpoll, Fossen, & Hauge, 2004; Da Silva, Escribano-Bailon, Alonso, Rivas-Gonzalo, & Santos-Buelga, 2007). Aronia melanocarpa (black chokeberry) belongs to the Rosaceae family and originates from North America. Nowadays, it is also cultivated around Europe. It was used in traditional medicine, but in recent years, the interest for this herb increased also due to its potential use

http://dx.doi.org/10.1016/j.ifset.2015.10.016 1466-8564/© 2015 Elsevier Ltd. All rights reserved.

Please cite this article as: Janković, B., et al., Isoconversional kinetic study and accurate determination of lifetime properties for thermal and thermo-oxidative degradation proce..., Innovative Food Science and Emerging Technologies (2015), http://dx.doi.org/10.1016/j.ifset.2015.10.016

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B. Janković et al. / Innovative Food Science and Emerging Technologies xxx (2015) xxx–xxx

as a food colorant (Bridle & Timberlake, 1997) and as a source for valued phytonutrients (Slimestad, Torskangerpoll, Nateland, Johannessen, & Giske, 2005). It was found that A. melanocarpa is one of the richest herbal sources of phenolic compounds and that the content of proanthocyanidins, anthocyanins, and phenolic acids this herb is high (d'Alessandro, Kriaa, Nikov, & Dimitrov, 2012). A. melanocarpa berries are one of the richest plant sources of anthocyanins (class of flavonoids): cyanidin-3-O-galactoside, cyanidin-3-O-arabinoside, cyanidin3-O-xyloside, and cyanidin-3-O-glucoside, which are responsible for dark red, blue, and purple color of berries (Oszmiañski & Sapis, 1988). It should be noted that 25% of the total polyphenols in chokeberry fruits are anthocyanins. Of the aromatic acids, the most dominant are chlorogenic and neochlorogenic (Slimestad et al., 2005). Also, it is important to say that (−) epicatechin oligomers are dominant proanthocyanidins, which represent 66% of chokeberry fruit polyphenols (Oszmiañski & Wojdyło, 2005). Due to their strong antioxidant capacity and possible positive effect on human health, proanthocyanidins have a great potential in nutrition, medicine, and in the study of food in general. Compared to other fruit, antioxidant activity of chokeberry is significantly higher (Zheng & Wang, 2003). The positive effect of A. melanocarpa on human health was subject of numerous studies, one of which showed favorable effect of A. melanocarpa in control and prevention of diabetes mellitus type II and diabetes-associated complications (Simeonov et al., 2001). In addition, chokeberries could have positive effect on the prevention and treatment of cardiovascular diseases or on the risk factors for such diseases (Kulling & Rawel, 2008). As part of our systematic studies in kinetic analysis of A. melanocarpa degradation processes under inert and oxidative conditions, the corresponding non-isothermal thermogravimetric analysis (TGA) was conducted. Kinetic data were collected using simultaneous TG-DTA (DTA—differential thermal analysis) technique. Temperature changes cause alterations in the physical and chemical properties of food components, which influence the overall properties of the final product, e.g., taste, appearance, texture, and stability. Chemical reactions such as hydrolysis, oxidation, or reduction may be promoted, or physical changes, such as evaporation, melting, crystallization, or aggregation may occur. These phenomena can affect the overall kinetic mechanism when food is subjected to thermal stress at different reaction atmospheres. It is therefore important for food scientists to have analytical techniques to monitor the changes that occur in foods when their temperature varies and to be able to reliably track all comprehensive kinetic behavior of the studied transformations. These techniques are often grouped under the general heading of thermal analysis. Isoconversional methods deliver formal kinetic information by using a set of measurements where the heat release rate is measured at different temperatures and always at the same conversion. Once the kinetic information is known, it can be used to calculate the heat release rate and the conversion at different conditions, such as at fixed temperatures or under adiabatic conditions. Mathematical description of complex physico-chemical processes, such as thermal degradation of food system under various experimental conditions, represents the one of the main problems in food engineering and processing. Since the several degradation reactions take place, and their mechanisms are unknown, various mathematical approaches can be used to describe the process of degradation. Very often, the approaches used are isoconversional models, which presume that kinetic parameters, such as pre-exponential factor (A) and apparent activation energy (Ea), are inconstant during the process of degradation but are dependent on conversion. The main objectives of this study are the evaluation of the main mechanistic conclusions from the applied isoconversional analysis for both studied processes and also a reliable determination of all the lifetime characteristics of A. melanocarpa during its thermal stress in inert and oxidative reaction atmospheres.

2. Material and methods 2.1. Samples Fresh samples (in the form of berries—not dried) of A. melanocarpa (Aronia noir) with a vibrant navy blue were supplied by the private breeders (Republic of Serbia), with specialized plantations for the cultivation of two types of berries—Aronia noir and Goji (“wolfberry”). The berries were packed in a special pouch for disconnecting the air. All berries were transported in its full refinement without damage and non-dehydrated. The layout of the experimental samples of the tested A. melanocarpa is shown in Fig. 1. 2.2. Non-isothermal (dynamic) thermo-analytical (TA) measurements The thermal stability of the fresh samples was investigated by simultaneous non-isothermal thermogravimetric analysis (TG) and differential thermal analysis (DTA) using a SETARAM SETSYS Evolution 1750 instrument. The high purity argon (Ar) gas (99.999%) was used as the protective atmosphere, with a gas flowing of φ = 20 mL min−1. The fresh samples taken from approximately 5–10 mg were heated at three different heating rates such as β = 10, 20, and 30 °C min−1, in an argon and air atmospheres (with an airflow streaming of φ = 16 mL min−1), in the temperature range from 30 °C up to 700 °C. The duplicate non-isothermal runs were made under similar conditions, and it was found that the data overlap with each other (including the control measurement for each heating rate, with approximately the same mass of the sample), indicating the satisfactory reproducibility. Each run was duplicated in order to minimize the error. 3. Theoretical approach and calculation procedures The kinetics of thermal degradation reactions is described by various equations taking into account the special features of their mechanisms. The reaction rate can be expressed through the conversion fraction α according to the formula such as α = (mo − mT) / (mo − mf), where mo, mT, and mf are initial, current (at experimental temperature T and at the moment t), and final sample mass, respectively. Generally, the kinetic equation of the studied process under non-isothermal conditions can be written as follows (Chen et al., 2014):

β



 dα dα Ea ≡ ¼ A exp −  f ðα Þ dT dt RT

ð1Þ

Fig. 1. The layout of the experimental samples of the tested Aronia melanocarpa (Aronia noir).

Please cite this article as: Janković, B., et al., Isoconversional kinetic study and accurate determination of lifetime properties for thermal and thermo-oxidative degradation proce..., Innovative Food Science and Emerging Technologies (2015), http://dx.doi.org/10.1016/j.ifset.2015.10.016

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where β is the heating rate [°C min−1], T is the absolute temperature [K], A is the pre-exponential (frequency) factor [min−1 or s−1], Ea is the apparent (effective) activation energy [J mol− 1], R is the gas constant [8.314 J mol−1 K−1], and f(α) represents the conversion function or analytical form of the reaction mechanism function. Isoconversional methods are capable to provide same clues about the complexity of processes in terms of the variation in their apparent activation energies with conversion fraction (also called Ea–α dependency) (Vyazovkin, 1996). Isoconversional methods are based upon the isoconversional principle, which states that “at certain conversion fraction, the rate of a solid state reaction depends only upon the temperature.” These methods provide basis to calculate the values of Ea in a model free way. However, thermally stimulated solid-state processes are intrinsically multi-step with variable Ea values. Even if Ea is ostensibly constant, there is still a probability that all kinds of participating reactions have nearly similar kinetic barriers or the overall kinetics is determined by a single step despite of the fact that it includes several steps (Maciejewski, 2000). As the reaction proceeds, its state alters with conversion fraction. Therefore, the objective to treat Eq. (1) or its different integral forms under constant conditions of α is in fact, to estimate the variations in Ea at each value of α, which is one of the discriminating features of isoconversional kinetics. In the case of nonisothermal kinetics, it is usually realized by using multiple heating rate programs. Isoconversional methods can be isothermal/nonisothermal, differential/integral, and linear/non-linear. They are named so because they may be inter-convertible by certain multiples arising from numerical differentiation or the integration of temperature integral (Órfão, 2007) and therefore generate nearly similar Ea–α dependency patterns. Taking logarithm and rearranging Eq. (1) yields
ln

dα dt

 α;βi

¼ ln ½Aα  f ðα Þ−

Ea;α RT α;i

ð2Þ

where the above expression represents the basic equation in Friedman's (FR) differential isoconversional approach (Friedman, 1964). The Ea,α values can be determined by plotting ln(dα/dt)α,βi against 1/Tα,i at certain values of α and at the corresponding ith value of heating rate, βi, which inevitably demands the numerical differentiation. This method may be sensitive to the occurrence of increased background noise on the obtained rate–temperature curves so that it must be carried out their filtering through the signal processing using smoothing procedure. Given that this approach does not use any approximation for the temperature integral, the actual kinetic method is considered as quite reliable for determining Ea. The Kissinger–Akahira–Sunose (KAS) integral isoconversional method (Akahira & Sunose, 1971; Kissinger, 1957) is based on the Coats–Redfern approximation of the temperature integral (Coats & Redfern, 1964) and KAS relationship can be presented in the form

ln

βi T 2α;i

!

 ¼ ln

 Aα  R Ea;α − : Ea;α  g ðα Þ RT α;i

ð3Þ

Using TA curves recorded at the different heating rates βi, the plot of ln(βi/T2α,i) against 1/Tα,i lead to the straight lines, where the value of the apparent activation energy can be obtained from the slope of the straight lines for each α, independent of the expression of the conversion function in integral form, g(α). If the value of R2 b 0.95 for some straight lines or the change of the straight lines' slope, the implicit Ea value function of α, it can be argued that the reaction mechanism changes. In addition, after knowing Ea,α–α feature, the isoconversional approach can be used to predict isothermal kinetic conversion as a

3

function of reaction time from the arbitrary temperature programs in the light of Eq. (4) (Vyazovkin & Sbirrazzuoli, 2006): Zt α tα ¼

0

  Ea;α dt exp − RT ðt α Þ
 ; Ea;α exp − RT o

ð4Þ

where tα is the reaction time to a specific conversion fraction α, To is a fixed isothermal (operating) reaction temperature, and the other parameters involved have the same meaning as in the equations above. Specifically, for the non-isothermal process performed with a constant linear heating rate, tα can be estimated by the following equation (Vyazovkin & Sbirrazzuoli, 2006):
 Ea;α exp − dT RT o 0
 ; tα ¼ Ea;α β  exp − RT o ZT α

ð5Þ

where Tα is the temperature when a non-isothermal process progresses to conversion fraction α, with the constant heating rate, β, and at a fixed temperature, To. 3.1. Lifetime analysis From the information given by kinetic analysis, it is possible to establish the occurrence of certain changes in fruit food products during storage, when they are subject to certain temperature fluctuations that may cause changes in flavor and color. Lifetime estimations are very useful in the development of selection of food products for different applications. Lifetime is usually determined by accelerated aging, like air oven aging studies, which require long time periods. The apparent kinetic parameters in the manner described above have been used to calculate the value of lifetime for investigated A. melanocarpa samples. It can be pointed out that some importance was given to the parameters determining the stability times for fruits: storage's times at a given fraction of reaction system decomposed α, at various operating temperatures were obtained by the expression tα ¼

f ðα Þ
; Ea A exp − RT o

ð6Þ

using the mathematical expression f(α) describing the possible degradation mechanism, and α = 0.50 and small α values (such as 0.01, 0.02, 0.03, and 0.04). The important characteristics are half-life time (degradation of half-product) and shelf-life time (degradation of small pre-fixed extent of product), respectively. With the above equation, the time to equivalent damage at different fixed temperatures can be calculated. In addition, the use of a reference temperature, Tref, is recommended, corresponding to a representative value in the temperature range of the process/storage of the study. The Arrhenius equation can be mathematically transformed as follows (Labuza, 1984): 
 Ea 1 1 k ¼ kref exp −  − ; T T ref R

ð7Þ

where kref is the rate constant at the reference temperature Tref. In that case, the value of Ea is calculated from the linear regression analysis such as lnk against (1/T − 1/Tref). For Tref usually takes the value of 298.15 K for ambient temperature-stored food products. Besides giving the constant a practical physical meaning, the above transformation of the Arrhenius equation provides enhanced stability during numerical

Please cite this article as: Janković, B., et al., Isoconversional kinetic study and accurate determination of lifetime properties for thermal and thermo-oxidative degradation proce..., Innovative Food Science and Emerging Technologies (2015), http://dx.doi.org/10.1016/j.ifset.2015.10.016

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parameter estimation and integration. According to optimum scheme, an optimum number of five or six isothermal (static) temperatures are adequate to obtain a satisfactory accuracy. Non-uniform temperature within samples, as well as difficulty in recognizing a deviation from an Arrhenius behavior, should also be considered when applying non-isothermal technique. An alternative to the Arrhenius law to describe the temperature dependence of reaction rates is through the Q10 concept (Toukis, Labuza, & Saguy, 1997), a tool of practical importance to the food industry. The Q10 is the ratio of the reaction rate constants at temperatures differing by 10 °C, or equivalently, it shows the reduction of shelf-life when the food is stored at a temperature 10 °C higher, as Q 10 ¼

kðTþ10Þ : k ðT Þ

ð8Þ

Alternatively, the shelf-life time (here, generally designated as ts) can be plotted against temperature as ts(T) = ts0 ∙ exp(− b ∙ T), which leads to lnts = lnts0 − b ∙ T, where b is the slope of the shelf-life plot and ts0 is the intercept. Q10 and b are the functions of temperature and can be correlated with Ea of the studied food quality, using the following equation (Toukis et al., 1997): lnQ 10 ¼ 10b ¼

Ea 10 :  R T  ðT þ 10Þ

ð9Þ

Knowing this correlation, it is possible to establish the dependence of Q10 on temperature and Ea, which is very important for typical reaction types which may occur in the studied foods. The value of quality function (which generally describes the loss of the quality factor of investigated food, which can be presented by the loss of one or more quantifiable quality indices, where quality factor may appears through changes of chemical, physical, or sensory parameters directly correlated to the reaction mechanism of degradation) (Ramachandran & Nagarajan, 2014; Toukis et al., 1997) at time t, when the studied food is exposed at a pre-determined variable time– temperature conditions T(t), can be estimated by calculating the integral in form as Zt F q ½ f ðα Þt ¼ A 

expðb  T Þdt;

ð10Þ

0

where A represents the overall value of pre-exponential factor, calculated for the process under study. Physically, the Fq[f(α)]t is a complex quantity so that the final calculated value actually reflects participation of various reactive compounds during degradation, inorganic catalysts, reaction inhibitors, water activity, and also participation of the experimental factors (“environmental impacts”), such as process temperature monitored under strictly defined heating modes, humidity, and partial pressures of evolved gases. All of these factors can significantly affect the current reaction mechanism of degradation or affect his “transformation” in the sense of changing the present mechanistic regimes, for example, from the kinetic (chemical reactions) into diffusion regime. The new magnitude, known as the z-value (Toukis et al., 1997), is used to describes the temperature dependence of rate quality loss. The value of z is the temperature range that causes a 10-fold change in the reaction rate constant. Similarly to the Q10 approach, the z-value depends on reference temperature and is related to the slope (b) value and Ea through the following established equation: z¼

ln10 ð ln 10Þ  RT 2 ¼ : b Ea

ð11Þ

4. Results and discussion 4.1. Thermal studies The TG–DTA curves for the degradation processes of A. melanocarpa fresh samples in an argon and air atmospheres, at the various heating rates (β = 10, 20, and 30 °C min−1) are shown in Fig. 2. Under an argon atmosphere, the three process stages were identified, while in air atmosphere, the four process stages exist (Figs. 2a– d). Thermo-analytical curves (Figs. 2a and c) in both atmospheres show a similar trend with the increase in experimental temperature, but their distinctive shapes in respective heating rates are not the same. The DTA curves recorded in argon and air also show a different behavior and significant differences in their characteristic forms (Figs. 2b and d). Table 1 provides the estimated characteristic reaction temperatures, the characteristic overall mass loss values, and mass loss values identified by the process stages, for both studied degradation features. Presented process stages in Table 1 were determined in accordance with sensitivity slope changing at thermo-analytical curves for both reaction atmospheres, where fold point is determined on the basis of two-tangent pulling approach. The entire procedure is performed with software already installed in thermogravimetric analyzer. In both cases, the first (“1” in Table 1) process stage can be attributed to dehydration mechanism pathway, where there is a sudden loss of surface water in primary stage of this process, and then to the loss of bulky water, which occurs in secondary stage of this process, and which is characterized by achieving a slightly higher temperatures, ranging beyond 100 °C (see Figs. 2a–d and Table 1). If we compare our studied system under the weight of present water, when it is subjected to thermal stress under various atmospheres, we can conclude that the fresh sample of A. melanocarpa shows higher resistance to thermooxidative degradation. Namely, compared with the behavior attached to the first process stage in inert atmosphere, in an air atmosphere, the system “expressed” a tendency that wants to keep the greatest possible amount of water, as opposed to the effect of thermal gradients within the sample. This clearly shows that water plays a more important role in the process of thermo-oxidative degradation than is the case with thermal degradation present in an inert atmosphere. This phenomenon can be confirmed also from the appearance of varying the intensity of endothermic effects for the first process stage in considered atmospheres. We can see that in the case of argon atmosphere, there is a very intense, deep and quite narrow endothermic peak at all heating rates, compared with the same effect in air atmosphere (Figs. 2b and d). In air, we have that the increase of heating rate leads to the spread of the endothermic peak, but its intensity is much lower than is the case in an inert atmosphere. Based on these results, we can conclude that in an inert atmosphere, the vaporization is a more intensive than in air atmosphere. However, it can be pointed out that water exists in foods in various forms such as free water, water droplets, water adsorbed on a surface, chemically bound water, crystal water, and composition water. Often, water is removed from processed foods as it affects keeping quality or to reduce weight and volume of the products. In most cases, however, part of this water is extremely difficult to remove so that even dehydrated food systems may contain 2–3% residual water. In addition, it is important to mention that water vapor pressure increases rapidly with temperature, especially above 150 °C, in the case of a little bit more aggressive temperature treatment for removal of chemically bonded water. In this regard, approximately up to 100 °C, the first part of dehydration can be attributed to free water, which represents the water bound with less energy to the matrix. In addition, slightly above the previously mentioned temperatures, then this case corresponds to a more slightly linked water to the matrix, which belongs to bound water, causing significant expansion of endothermic peak in a broader temperature range (Fig. 2). However, the difference between free and bound water is not straight.

Please cite this article as: Janković, B., et al., Isoconversional kinetic study and accurate determination of lifetime properties for thermal and thermo-oxidative degradation proce..., Innovative Food Science and Emerging Technologies (2015), http://dx.doi.org/10.1016/j.ifset.2015.10.016

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Fig. 2. TG (a, c)–DTA (b, d) curves for the degradation processes of Aronia melanocarpa fresh samples in an argon and air atmospheres, at the different heating rates (β = 10, 20, and 30 °C min−1).

In complex systems, such as fruits, there exist different degrees of water binding. Free water can be found far from non-aqueous components, being predominant water–water hydrogen bounds. When the sample is heated and free water is released, the equilibrium between different sorts of water changes and limit between free and the bound water become diffused. For slowest heating rate (10 °C min− 1), we can observe that exists the small visible inflection point in mass loss on both TG curves (Figs. 2a and c), but it is certainly much less noticeable in air atmosphere, immediately making a transition to the next process step, which has direct implications for distortion of DTA peak (Fig. 2d). In the latter case of actual process, the multilayer water is released slowly. When heating rate was too high (30 °C min− 1), the bound water was not accurately “measured” because at the inflection point not all the free water had been already released. This can be seen in Fig. 2d where at 30 °C min−1, we can observe the emergence of mild “shoulder” at approximately 160 °C. Therefore, the medium heating rate of 20 °C min−1 was chosen as an agreement and division between both types of water with appearance of peak temperature at 112.52 °C and 112.80 °C in argon and air atmospheres, respectively. In argon atmosphere, we distinguish two process stages after dehydration, which are prolonged in the following temperature ranges: 178.91 °C–243.97 °C (“2”) and 243.97 °C–696.31 °C (“3”) observing at 20 °C min−1 (Table 1). In inert condition, the dehydration and other decomposition stages represents three separate processes, which can be observed during thermal degradation of A. melanocarpa. In the

above-mentioned temperature ranges that correspond to the second and third reaction step, at the recorded DTA curves for all heating rates (Fig. 2b), we observe an endothermic (within “2” stage), and then one exothermic peak (within “3” stage). In air condition, it can be seen that there are three reaction steps after dehydration stage. However, it should be emphasized that the step “2” (Table 1 and Fig. 2c), which occurs in an air atmosphere, falls under the dehydration stage, bearing in mind the previous discussion regarding the behavior of water during thermal activation in various atmospheres. The stages designated by “3” and “4” (Table 1) are characterized by exothermic effects (Fig. 2d) so that there is a vigorous evolution of the heat and wherein there is a synergistic phenomenon with the increase in the heating rate of the system. Consequently, oxygen has two prominent effects during thermal decomposition at the high temperatures, namely, (i) increasing ash production and, as a result, reducing volatile production, and (ii) causing mass losses to cluster and very sharp peaks (Fig. 2d) to appear around specific temperatures. Based on these results, we can conclude that in an oxidative environment the thermal degradation reactions of A. melanocarpa are much more complex than ones in an inert environment, particularly at high temperatures. Thus, as can be seen from Figs. 2a–d, below 200 °C, the fresh samples vaporized similarly (but not identical) and exhibited smooth degradation profiles, in argon and in an air. Near 250 °C, however, the presence of oxygen caused a sharp decrease in a mass loss values, where it is much faster than is the case for argon atmosphere. This will result in emergence of

Please cite this article as: Janković, B., et al., Isoconversional kinetic study and accurate determination of lifetime properties for thermal and thermo-oxidative degradation proce..., Innovative Food Science and Emerging Technologies (2015), http://dx.doi.org/10.1016/j.ifset.2015.10.016

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Table 1 The main temperature values (initial (Ti), peak (maximum) (Tp), and final (Tf) temperatures) characterizing the entire decomposition processes in an argon and air atmospheres for Aronia melanocarpa at different heating rates. Same table also shows the results attached to the final (ending) mass loss values (Δmf) and mass loss values belonging to the individual reaction stages (Δmstage). β (°C min−1)

10

20

30

β °C min−1)

10

20

30

Argon atmosphere Process stages 1 2 3 1 2 3 1 2 3

Ti (°C)

Tp (°C)

Tf (°C)

20.32 149.86 223.54 30.03 178.91 243.97 30.05 164.23 237.57

95.93 197.36 265.95 113.91 203.67 275.50 93.64 205.20 280.95

149.86 223.54 704.57 178.91 243.97 696.31 164.23 237.57 687.11

Δmf (%) 99.76

99.96

98.60

Δmstage (%) 79.60 4.89 15.27 81.40 5.34 13.22 69.21 8.05 21.34

Air atmosphere Process stages 1 2 3 4 1 2 3 4 1 2 3 4

Ti (°C)

Tp (°C)

Tf (°C)

30.00 140.61 223.35 342.75 30.03 165.86 232.54 386.90 30.03 185.94 242.36 403.61

83.93 197.11 249.71 426.15 112.80 207.10 273.91 480.42 118.11 212.08 279.78 459.75

140.61 223.35 342.75 703.74 165.86 232.54 386.90 695.83 185.94 242.36 403.41 686.59

Δmf (%)

98.22

99.90

99.10

Δmstage (%) 65.30 6.41 11.48 15.03 76.74 5.76 9.63 7.77 72.90 6.63 11.60 7.97

some differences in thermal degradation at low and high temperatures (Figs. 2c and d). However, there is no notable differences in the argon atmosphere (Figs. 2a and b). In air, above 350 °C (Fig. 2d), the DTA profiles exhibited several peaks, and some of which are overlapping in the presence of oxygen. It should be noted that the most important constituents present in A. melanocarpa are the phenolic compounds. A. melanocarpa contains the high levels of procyanidins, anthocyanins, and phenolic acids (Wangensteen et al., 2014). However, a series of the factors, such as the habitat/location, harvest date, cultivar, fertilization, and maturation of berries, can affect their content. The exclusion of oxygen may be important for anthocyanin stability. However, increased sugar content can have in general, an adverse effect to thermal degradation of anthocyanins, there are two possible mechanisms for thermal degradation of anthocyanins, such as (i) hydrolysis of the 3-glycosidic linkage to produce a more labile aglycon and (ii) hydrolytic opening of pyrylium ring to form a substituted chalcone, which degrades to an insoluble compound of the polyphenolic nature. It should be noted that the exact degradation pathway of anthocyanins in an inert atmosphere in the case of the fresh samples, only with a combination of TGA-DTA technique, is not sufficient for evaluation, but it is necessary to carry out the subsequent pigment analysis with possession of colorimetric temperature indicator (having both natural and the heat-sensitive pigment (anthocyanin—ATH)) (Maciel, Yoshida, & Franco, 2012). However, this analysis is out of the scope for this work, so it is possible to conduct this type of testing in our future research. In an air atmosphere, we can notice that there are not any endothermic effects after the first two process stages (Fig. 2d). The serious changes in thermal behavior with the presence of oxygen may be observed in the temperature range of 375 °C–575 °C. This range can be very sensitive to “external” factors such as the presence of a thermal gradient intensity and oxidative factors (the currently surface area of the sample exposed to air due to a reaction with oxygen in the surrounding air environment). The early signs of a serious oxidative stress can be

demonstrated through as changes in antioxidant enzymes such as peroxidases, catalase, or antioxidant compounds such as glutathione or ascorbic acid. In addition, at the rather high temperatures, the emergence of a large number of exothermic peaks in the DTA curves (Fig. 2d) may be due to the oxidation process of the remaining organic matter. Afterward, the rather small residual mass loss values at every considered heating rates β (Table 1) arising from the post-combustion processes. 4.2. Isoconversional kinetic analysis Figs. 3a–d shows the dependencies of apparent activation energy values and isoconversional intercept values calculated from FR and KAS methods, for degradation process of A. melanocarpa samples, in argon and air atmospheres. We can see in Fig. 3a that in argon atmosphere, the apparent activation energy (Ea) shows a rather complex nature with the change in the conversion fraction values. It may be noted that up to approximately α ≈ 0.35, the negative values of Ea were detected (Fig. 3a). Also, the negative values of Ea have been observed in some later stages of the decomposition process in conversion fraction range of 0.70 ≤ α ≤ 0.75. After α = 0.75, the value of Ea increases in positive manners with the increasing of the conversion fraction (α) values almost to the very end of the process. This increase in the apparent activation energy values may indicate on the presence of the parallel simultaneous reactions (Vyazovkin, Goryachko, & Lesnikovich, 1992). However, in conversion fraction region of 0.35 ≤ α ≤ 0.65 (if we focus on the results obtained from the Friedman's (FR) method), the Ea value has stabilized and does not show any significant variation with α, so in the mentioned α FR region, Ea can be taken as constant value, which amounts Ea,avg = KAS 13.285 ± 2.530 kJ mol−1 and Ea,avg = 30.682 ± 5.702 kJ mol−1 (Fig. 3a), where these values represent the average Ea's calculated using the Friedman (FR) and Kissinger–Akahira–Sunose (KAS) isoconversional methods, respectively. Differences in calculated average Ea values are the result of mathematical origins, which are grounds for actual methods. Much more reliable method is the Friedman's method than Kissinger–Akahira–Sunose method since FR method does not use any kind of approximation, where this is not the case for KAS method, which inevitably use approximations for solution of temperature integral. However, FR method is somewhat sensitive to occurrence of background noise, but this can be successfully overcome by using a numerical filtering of experimental rate data. Obtained Ea value (13.285 kJ mol− 1) in an inert atmosphere for decomposition process of A. melanocarpa is quite low compared to the calculated values for Ea for thermal degradation of anthocyanins in red-flesh potato (66.7 kJ mol−1), grape (75.03 kJ mol−1), and purple carrot (81.34 kJ mol−1), respectively (Reyes & Cisneros-Zevallos, 2007). However, the apparent activation energies (Ea) for anthocyanin degradation have a range from 42.00 (cyanidin-3-glucosylrutinoside) to 55.00 kJ mol−1 (cyanidin-3-glucoside), and for other phenols from 8.12 (chlorogenic acid) to 27.00 kJ mol− 1 (neochlorogenic acid) (Zorić, Dragović-Uzelac, Pedisić, Kurtanjek, & Elez Garofulić, 2014). It should be noted (taking into account above facts) that the degradation process in inert atmosphere is probably governed by degradation mechanism of chlorogenic acid. On the other hand, in the case of air atmosphere, we can see the different behavior in Ea values with an increasing of α than the one which has been identified in the case of an inert atmosphere. In the wide range of conversion fraction (0.10 ≤ α ≤ 0.60), the E a value is almost constant and does not show any significant variation FR with α, with an average values of Ea,avg = 22.714 ± 1.033 kJ mol− 1 −1 KAS and Ea,avg = 26.854 ± 1.348 kJ mol calculated by Friedman and Kissinger–Akahira–Sunose isoconversional methods, respectively (Fig. 3b). Compared with previous case, in actual case, we can notice a higher resistance of a given system under the oxidative stress

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Fig. 3. The dependencies of the apparent activation energy values and isoconversional intercept values calculated from the Friedman's (FR) and Kissinger–Akahira–Sunose (KAS) methods, for degradation process of Aronia melanocarpa fresh samples, in an argon (a, c) and air (b, d) atmospheres, respectively.

conditions, where in a fairly large range of conversions, we have a very stable value of Ea. If we focus on derived value of Ea in the case of air atmosphere (22.714 kJ mol− 1 (FR) or 26.854 kJ mol− 1 (KAS) (see above)), then follows that the primary role in degradation pathways have anthocyanins, where their Ea values for degradation in air are in the range of 20.00–34.00 kJ mol−1, in the case of blackberries (Nayak, 2011). Eventually, the higher Ea value implies that a smaller temperature range could degrade a given compound more rapidly. However, it should be noted that the value of 23.80 kJ mol− 1 was reported for polyphenolic compounds entrapped in surfactant-rich phase, which increases their thermal stability (Stamatopoulos, Katsoyannos, & Chatzilazarou, 2014). The calculated value of Ea which amounts of 26.854 kJ mol− 1 is close to the value of 27.00 kJ mol− 1, which corresponds to neochlorogenic acid ((1R,3R,4S,5R)-3-{[(2E)-3-(3,4dihydroxyphenyl)prop-2-enoyl]oxy}-1,4,5trihydroxycyclohexanecarboxylic acid, which represents a natural polyphenolic compound) degradation (see above discussion). From Fig. 3b, we can notice that in later stages of the process (after α = 0.65), the quite strongly Ea variation with appearance of negative values exists with an increasing of α values. Furthermore, the isoconversional intercepts, which can be indirectly linked to behavior of pre-exponential factor (A) (not taking into account the exact analytical form of the mathematical function that cursed reaction mechanism, f(α) or g(α)) (Figs. 3c and d), show in both cases almost identically behavior as apparent activation energy values, with the change of the conversion fraction, α (Figs. 3a and b). In Fig. 3d, in the case of air atmosphere, after α = 0.65, the values of ln[A/g(α)] do not exist, and bearing in mind that for their calculation, the Ea values

(negative values) are necessary in aforementioned conversion range, then isoconversional intercepts do not have a physical meaning. 4.3. Kinetic prediction results Predictions are among the most important practical features of a kinetic study. They are widely used to evaluate the kinetic behavior of food system beyond the temperature regions of experimental measurements. For instance, thermal stability can be estimated as the time to reach a certain conversion fraction at a given operating temperature. This type of kinetic prediction might be easily accomplished using Ea dependence evaluated by isoconversional method (Eqs. (4) and (5)). Timeline has been determined for the following operating temperatures as To = 100 °C, 200 °C, 300 °C, and 400 °C, at the heating rate of β = 20 °C min−1, without knowledge of the reaction mechanism. The obtained predicted times should not be confused with those obtained from lifetime analysis, where the current analysis is conducted outside the scope of the non-isothermal (dynamic) measurements, and extrapolated to room temperatures (25 °C and 30 °C). After all the above analyzes, the time values will be compared in order to obtain the information on their real merits and applicability in practice. Figs. 4a and b show the predicted kinetic (conversion) curves at four different operating temperatures (100 °C, 200 °C, 300 °C, and 400 °C) using the heating rate of β = 20 °C min− 1 with results estimated from isoconversional analyses, in the case of thermal and thermooxidative degradation of A. melanocarpa, respectively. From obtained results in argon atmosphere (Fig. 4a), we can see that parameters (Eq. (5)) predict a later reaction to the half conversion in

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Fig. 4. The predicted kinetic (conversion) curves at four different operating temperatures (To = 100 °C, 200 °C, 300 °C, and 400 °C) using the heating rate of β = 20 °C min−1, with results estimated from isoconversional analyses, in the case of thermal (argon) and thermo-oxidative (air) degradation of Aronia melanocarpa, respectively.

comparison with a reaction described by predicted curves (the sooner reaction) in an air atmosphere (Fig. 4b), at all operating temperatures. Obvious differences can be observed in the reaction times at a given operating temperatures in different atmospheres. Much shorter times can be observed at all operating temperatures (except at 400 °C) in a thermal degradation than in the case of thermo-oxidative degradation. However, as “finger-print” prediction curve in both considered cases, we should consider properly the curve at To = 400 °C. In the same time intervals, for all marked conversion fraction values, the predicted curve in air atmosphere much more quickly enters into the saturation portion, than is the case with a predicted curve in an argon atmosphere.

Faster increase in the value of the conversion fraction at very low time values for thermo-oxidative degradation than in the case of the process in an inert conditions is a direct result of different reaction mechanisms, which have been explained in detail in previous subsection. The key element here represents the shape of predicted curves (Figs. 4a and b). From detailed examination of the curves, we can observe that in inert atmosphere, at the low time values (Fig. 4a), the prediction shows that curves exhibit some sigmoid shaped level, but that is not so pronounced, and which is characteristic for the self-accelerating processes. On the other hand, in an air atmosphere, all predicted curves

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(Fig. 4b) exhibit a clear deceleratory behavior. The consequences of this analysis indicate that probably different reaction pathways exist in inert and oxidative atmospheres.

4.4. Results of lifetime analysis The half-life and shelf-life values for the investigated berry fruit system in the case of thermal and thermo-oxidative degradation processes have been calculated using Eq. (6). All calculations were performed in accordance with the reaction mechanism functions, which best describe the processes under study. In an inert atmosphere, it was found that the two-parameter Šesták– Berggren (SB) autocatalytic model (Šesták & Berggren, 1971) best describes the kinetics of the investigated process (the conversion function in the form of f(α)inert = αm(1-α)n, with the kinetic exponents m = 1.381 and n = 2.477). On the other hand, in an oxidative conditions, the “composite” conversion function exists in a form of f(α)ox. = f1(α) + f2(α) = (1α)n + αm(1-α)n, where f(α)ox. represents the mixture kinetic model, including the nth order (with n N 1) (n = 1.656) (in dynamic modes, this corresponds to the lower heating rate with β = 10 °C min−1) and the SB autocatalytic reaction mechanisms (with m = 0.871 and n = 1.861, where in the dynamic modes these values correspond to the higher heating rates at β = 20 and 30 °C min−1). The following values of the kinetic parameters were used in the calculation procedure such as Ea = 14.839 kJ mol− 1 and A = 6.690 × 102 min−1 (inert atmosphere), Ea = 39.600 kJ mol− 1 and A = 2.042 × 105 min−1 for nth order reaction model, and Ea = 23.617 kJ mol−1 and A = 1.353 × 103 min− 1 for the SB reaction model (air atmosphere). All calculations were performed at the operating temperatures outside of the active degradation temperature range. The corresponding results are shown in Table 2. From the obtained values (Table 2), it can be observed that tα values at 25 °C and 30 °C in thermal degradation (argon) are lower, and especially the half-life values, in comparison with same magnitudes in the case of thermo-oxidative process. Under oxidative conditions, A. melanocarpa sample shows greater resistance to the temperature variations, which correspond to the storage conditions, than in an inert atmosphere, and this also means

9

that the degradation mechanism greatly affects the stability and physico-chemical characteristics of its constituents. It can be noted that both half-life and shelf-life values, for the considered experimental conditions at the monitored temperatures, seem to be realistic in comparison with the time axes in isoconversional prediction analysis at much higher temperatures (Figs. 4a and b). Figs. 5 and 6 show the temperature dependence of degradation rate constant expressed through the modified Arrhenius model (Eq. (7)) at six different isothermal (static) temperatures (30 °C, 35 °C, 40 °C, 45 °C, 50 °C, and 55 °C) for the investigated processes in an argon and air atmospheres, respectively. It can be seen from Fig. 5 that in an argon atmosphere, we have a typical non-Arrhenius behavior, with a schedule of points that form a concave up-ward curve in respect to the possible linear progression that is presented with a colored dashed arrow. The current curve is manifested with a negative deviation from the Arrhenius dependence because the negative value of Ea was obtained. This behavior is an indication of the presence of a complex process that cannot be explained by the simple Arrhenius model expressed through elementary kinetic steps, but with a complex transformation with a large dispersion of the apparent activation energies, which is officially approved in above-mentioned consideration (namely, the complex autocatalytic mechanism with appropriate analysis attached to the kinetic predictions (Fig. 4a)). On the other hand, in Fig. 6, we have a different behavior. Namely, in current situation, with an increasing of temperature, the points form the Arrhenius-like behavior after 35 °C, with the increase of the linear regression to yield at the same time a positive value of Ea. Thus, up to 35 °C, we have a negative value of Ea, and after 35 °C, the value of Ea becomes positive, indicating a declension in the kinetic nature of the process, which means that studied system is extremely sensitive to temperature variations in oxidative conditions. The temperature variations obviously influenced the change in the mechanism of degradation, as evidenced in the previous discussions, at the beginning of this subsection. In addition, the degradation parameters such as Q10, z, and b were determined for all considered atmospheres. Also, the corresponding Ea values (Eq. (9)) at various isothermal temperatures were calculated. Table 3 summarizes the values of calculated degradation parameters (Q10, z, and b), as well as the values of Ea in an argon and air atmospheres, respectively. It should be noted that in Table 3, the values of the factor D are listed, which represents the decimal reduction time

Table 2 The half-life and shelf-life values tα at fixed operating temperatures, which are outside of the active degradation temperature range, for the thermal and thermo-oxidative degradation processes of Aronia melanocarpa fresh samples. Argon atmosphere (Eq. (6)) a tα (min) t0.01 t0.02 t0.03 t0.04 t0.10 t0.50

Operating temperature, To 25 °C

30 °C −3

1.57 × 10 4.00 × 10−3 6.82 × 10−3 9.89 × 10−3 2.99 × 10−2 6.43 × 10−2

1.44 × 10−3 3.66 × 10−3 6.24 × 10−3 9.05 × 10−3 2.73 × 10−2 5.89 × 10−2

Air atmosphere (Eq. (6)) a tα (min) t0.01 t0.02 t0.03 t0.04 t0.10 t0.50 a

Operating temperature, To 25 °C

30 °C

5.51 × 10−2 9.88 × 10−2 1.38 × 10−1 1.74 × 10−1 3.43 × 10−1 4.66 × 10−1

4.73 × 10−2 8.50 × 10−2 1.19 × 10−1 1.50 × 10−1 2.95 × 10−1 4.01 × 10−1

For the estimated kinetic triplets [Ea, A, f(α)].

Fig. 5. The temperature dependence of degradation rate constant expressed through the modified Arrhenius model at six different isothermal (static) temperatures (30 °C, 35 °C, 40 °C, 45 °C, 50 °C, and 55 °C), for degradation process in an argon atmosphere.

Please cite this article as: Janković, B., et al., Isoconversional kinetic study and accurate determination of lifetime properties for thermal and thermo-oxidative degradation proce..., Innovative Food Science and Emerging Technologies (2015), http://dx.doi.org/10.1016/j.ifset.2015.10.016

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Fig. 6. The temperature dependence of degradation rate constant expressed through the modified Arrhenius model at six different isothermal (static) temperatures (30 °C, 35 °C, 40 °C, 45 °C, 50 °C, and 55 °C), for thermo-oxidative degradation. In the same figure, the trend of increasing temperature is indicated.

(“D-value”), i.e., the heating time required to reduce the anthocyanins concentration by 90% (where D = ln(10)/k (values of k from Figs. 5 and 6); the values of k were calculated in accordance with established kinetic models as k = [dα/dt]/f(α), where dα/dt is the rate of the considered process, while f(α) represents the appropriate conversion function (see above)). Based on the results shown in Table 3, we can see that there is quite different stability between A. melanocarpa samples in various reaction atmospheres, as can be seen from the accompanying Ea values. In an argon atmosphere, at all considered temperatures, the negative Ea values exist, while in air atmosphere, there is a change in sign of Ea, in the transition temperature interval of ΔT = 35 °C–40 °C, from the extremely negative to positive values. These results are in complete agreement with the results presented in Figs. 5 and 6. Observing the reaction system in a given reaction atmospheres and only in the temperature range of ΔT = 30 °C–35 °C (lower temperatures), we can notice that the higher Ea and lower z-values in an air atmosphere, in comparison with same magnitudes in an argon atmosphere, are associated to increased temperature dependence of the anthocyanins degradation rate (Mollov, Mihalev, Shikov, Yoncheva, & Karagyozov, 2007; Rogez, Pompeu, Akwie, & Larondelle, 2011; Yang, Han, Gu, Fan,

& Chen, 2008). This can be easily noticed and from the values of Q10, which in the observed temperature range provide interesting results. Namely, in the observed temperature range, in both atmospheres, the values of Q10 are comparable, but, in an air atmosphere, after T = 40 °C, the values of Q10 are much larger than those in an argon atmosphere (Table 3). At a given value of temperature, in an air atmosphere, the z-value becomes a positive (Table 3). After 40 °C, in thermooxidative conditions, the z-value is changes drastically with an increasing tendency, as compared to the same magnitude in an argon atmosphere (Table 3). At the higher temperatures (T ≥ 40 °C), the z-value remains higher than at lower temperatures, and Ea turns to positive values, in accordance with the trend in Fig. 6. These results show enhanced stability of antioxidants in thermal stressed fruit berry system, whereby they clearly play a key role in blocking of free radicals operations and their harmful effects in reactions that take place at elevated temperatures. This assumption is confirmed by the values of D factors shown in Table 3. The D values are much higher in air atmosphere, than those in an argon atmosphere, wherein in thermo-oxidative conditions for ΔT = 30 °C–40 °C, there is an increase in D value, and after 40 °C, a decrease in D value occurs. Finally, Fig. 7 shows the forms of derived quality functions in respect to the fixed values of temperature within selected time intervals, in the case of thermal and thermo-oxidative degradation of A. melanocarpa fresh samples, respectively. From Fig. 7, we can see that the values of the quality function at the observed temperatures in air atmosphere are incomparably higher than those present in an argon atmosphere. Also, the Fq[f(α)]t value functionally increases more correctly with the temperature in air atmosphere, than those in an argon atmosphere. In an argon atmosphere, during the thermal degradation of studied system, the significant loss of quality as well as the strong influence of various factors (such as gases composition, water activity, etc.) can be seen only after 50 °C (sudden jump in the value of Fq[f(α)]t function). On the other hand, in the case of thermooxidative degradation, the appreciable increase in the values of Fq[f(α)]t function can be observed after 40 °C, but this increase is gradual, with the constant maintenance of the high values of Fq[f(α)]t function. In this sense, we can conclude that after 40 °C, the Arrhenius behavior exists (Fig. 6) as the degradation rate increases with the temperature toward the exponential manners. However, based on the results presented in Fig. 6, as well as the trend of the quality function in thermo-oxidative process, we obviously can detect that many factors affect on the chemical reactions responsible for the loss of quality, and which have a significant impact on the change in the rate-controlling mechanism.

Table 3 The values of degradation parameters (Q10, z, b, and D), as well as the values of Ea (Eq. (9)) in an argon and air atmospheres, for the tested Aronia melanocarpa fresh samples. Argon atmosphere Temperature (°C) Parameters Q10 z (°C) b (°C−1) D (min) Ea (kJ mol−1)

30

35

40

45

50

55

0.07391 −281.989 −0.00361 0.00751 −205.643

0.25449 −289.976 −0.00357 0.04603 −111.569

0.37712 −296.761 −0.00353 0.10159 −82.057

0.49602 −305.991 −0.00348 0.18087 −60.859

0.57185 −314.350 −0.00344 0.27229 −50.059

0.62890 −322.798 −0.00339 0.36463 −42.781

Air atmosphere Temperature (°C) Parameters Q10 z (°C) b (°C−1) D (min) Ea (kJ mol−1)

30

35

40

45

50

55

0.18941 −286.989 −0.00358 1.74797 −131.355

0.89193 −474.471 −0.00275 8.12871 −9.327

1.06318 102.677 −0.00939 9.22837 5.156

1.12385 −75.943 −0.00527 9.11364 10.137

1.16315 −120.793 −0.00484 8.68001 13.529

1.19096 −141.394 −0.00460 8.10939 16.124

Please cite this article as: Janković, B., et al., Isoconversional kinetic study and accurate determination of lifetime properties for thermal and thermo-oxidative degradation proce..., Innovative Food Science and Emerging Technologies (2015), http://dx.doi.org/10.1016/j.ifset.2015.10.016

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Fig. 7. The derived quality functions in respect to the fixed values of temperature within the selected time intervals, in the case of thermal and thermo-oxidative degradation of Aronia melanocarpa fresh samples, respectively.

5. Conclusions Isoconversional analysis and accurate determination of lifetime properties for thermal and thermo-oxidative degradation processes of A. melanocarpa were examined in this study. Based on the presented results, the real mechanistic schemes of both processes have been proposed, with special emphasis on the effect of antioxidative characteristics of studied food system. Also, proper study related to the quality control analysis was conducted. The Šesták–Berggren (SB) autocatalytic model was found as best model to describe the degradation process of A. melanocarpa in an inert atmosphere. It has been found that the autocatalysis may occur from inevitable presence of water probably through the hydrolysis. In the case of thermo-oxidative degradation, it was found that main mechanistic scheme can be presented with two different forms of reaction mechanism function, such as the nth order reaction model (with n N 1) and SB autocatalytic model. Using isoconversional analysis, it was determined that neochlorogenic acid represents the main compound which has a strong hydrogen-donating activity. Based on lifetime analysis, it was found that under oxidative conditions, A. melanocarpa shows greater resistance to the temperature variations that correspond to the storage conditions, than in an inert atmosphere, and this also means that the degradation mechanism greatly affects the stability and physico-chemical characteristics of its constituents. From calculated degradation parameters in an air atmosphere, the increased temperature dependence of anthocyanins degradation rate in A. melanocarpa sample have been identified. It was established that many factors affect on the chemical reactions responsible for the loss of quality.

Acknowledgments Authors would like to acknowledge the financial support of the Ministry of Education, Science and Technological Development of the Republic of Serbia (under project nos. 172015, 45020, and III43009).

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Please cite this article as: Janković, B., et al., Isoconversional kinetic study and accurate determination of lifetime properties for thermal and thermo-oxidative degradation proce..., Innovative Food Science and Emerging Technologies (2015), http://dx.doi.org/10.1016/j.ifset.2015.10.016