Kinetic Modeling of Food Quality: A Critical Review

Formation and kinetic analysis of AGEs in Pacific white shrimp during frying

Advanced glycation end products (AGEs) are complex and heterogeneous compounds closely associated with various chronic diseases. The changes in Nε-carboxymethyllysine (CML), Nε-carboxyethyllysine (CEL), Nε-(5-hydro-5-methyl-4-imidazolon-2-yl)-ornithine (MG-H1), and fluorescent AGEs (F-AGEs) in fried shrimp during frying (170 °C, 0-210 s) were described by kinetic models. Besides,the correlations between AGEs contents and physicochemical indicators were analyzed to reveal their intrinsic relationship. Results showed that the changes of four AGEs contents followed the zero-order kinetic, and their rate constants were ranked as kCML < kCEL ≈ kMG-H1 < kF-AGEs. Oil content and lipid oxidation were critical factors that affected the AGEs levels of the surface layer. Protein content and Maillard reaction were major factors in enhancing the CML and CEL levels of the interior layer. Furthermore, the impact of temperature on the generation of CML and CEL was greater than that of MG-H1 and F-AGEs.

Simultaneous High-Performance Recovery and Extended Acid-Catalyzed Hydrolysis of Oleuropein and Flavonoid Glycosides of Olive (Olea europaea) Leaves: Hydrothermal versus Ethanol Organosolv Treatment

Olive leaves (OLLs) are an exceptional bioresource of natural polyphenols with proven antioxidant activity, yet the applicability of OLL extracts is constrained by the relatively high polarity of the major polyphenols, which occur as glycosides. To overcome this limitation, OLLs were subjected to both hydrothermal and ethanol organosolv treatments, fostered by acid catalysis to solicit in parallel increased polyphenol recovery and polyphenol modification into simpler, lower-polarity substances. After an initial screening of natural organic acids, oxalic acid (OxAc) was found to be the highest-performing catalyst. The extraction behavior using OxAc-catalyzed hydrothermal and ethanol organosolv treatments was appraised using kinetics, while treatment optimization was accomplished by deploying response-surface methodology. The comparative assessment of the composition extracts produced under optimal conditions of residence time and temperature was performed with liquid chromatography-tandem mass spectrometry and revealed that OLLs treated with 50% ethanol/1.5% HCl suffered extensive oleuropein and flavone glycoside hydrolysis, affording almost 23.4 mg hydroxytyrosol and 2 mg luteolin per g dry weight. On the other hand, hydrothermal treatment with 5% OxAc provided 20.2 and 0.12 mg of hydroxytyrosol and luteolin, respectively. Apigenin was in all cases a minor extract constituent. The study presented herein demonstrated for the first time the usefulness of using a natural, food-grade organic acid to perform such a task, yet further investigation is needed to maximize the desired effect.

Digital replica to unveil the impact of growing conditions on orange postharvest quality

The postharvest end-quality of citrus is significantly impacted by pre-harvest factors such as weather, which varies among growing regions. Despite the importance of these factors, the influence of regional weather variations, such as variations in temperature, humidity, wind, vapor pressure deficit (VPD), and solar radiation on postharvest citrus quality, is largely unknown. This study aims to quantify this impact through a physics-driven digital replica of the entire value chain of Valencia oranges, from orchards in South Africa to retail in Europe. Predicted fruit properties data at harvest and hygrothermal sensor data from orchard to retail for different production regions are coupled to a physics-based fruit model to simulate key postharvest fruit quality metrics. These metrics include mass loss, chilling injury, fruit quality index (FQI), remaining shelf life (RSL), total soluble solids (TSS), and titratable acidity (TA). Our digital fruit model reveals that regional weather variability significantly affects fruit quality evolution when comparing data from Nelspruit, Letsitele, and Sunday's River Valley (SRV). The impact of weather variations is most pronounced in the temperate oceanic climate of SRV compared to the hotter climates of Letsitele and Nelspruit. Our findings indicate that differences in weather conditions between these growing regions impact postharvest mass loss, FQI, RSL, TSS, and TA of Valencia oranges at retail. The impact is up to 10% variation in mass loss and RSL, 4% in TSS, and 1% in TA among oranges grown in different regions. We show that temperature and humidity variations in the postharvest local transport of oranges between different regions largely increase mass loss by up to twofold, FQI by up to ~ 12%, and RSL by up to ~ 15% at retail. Our research also shows that weather temperature is the most important metric during fruit growth affecting various aspects of postharvest orange quality. This study offers valuable insights into the impact of regional weather variations on the quality of oranges available to consumers. These findings could help the citrus industry enhance growing practices, postharvest logistics, retail marketing, and cold chain strategies, thereby improving product quality and consumer satisfaction.

Virtualization and digital twins of the food supply chain for enhanced food safety

Meeting food safety requirements without jeopardizing quality attributes or sustainability involves adopting a holistic perspective of food products, their manufacturing processes and their storage and distribution practices. The virtualization of the food supply chain offers opportunities to evaluate, simulate, and predict challenges and mishaps potentially contributing to present and future food safety risks. Food systems virtualization poses several requirements: (1) a comprehensive framework composed of instrumental, digital, and computational methods to evaluate internal and external factors that impact food safety; (2) nondestructive and real-time sensing methods, such as spectroscopic-based techniques, to facilitate mapping and tracking food safety and quality indicators; (3) a dynamic platform supported by the Internet of Things (IoT) interconnectivity to integrate information, perform online data analysis and exchange information on product history, outbreaks, exposure to risky situations, etc.; and (4) comprehensive and complementary mathematical modeling techniques (including but not limited to chemical reactions and microbial inactivation and growth kinetics) based on extensive data sets to make realistic simulations and predictions possible. Despite current limitations in data integration and technical skills for virtualization to reach its full potential, its increasing adoption as an interactive and dynamic tool for food systems evaluation can improve resource utilization and rational design of products, processes and logistics for enhanced food safety. Virtualization offers affordable and reliable options to assist stakeholders in decision-making and personnel training. This chapter focuses on definitions and requirements for developing and applying virtual food systems, including digital twins, and their role and future trends in enhancing food safety.

Diffusion and Chemical Degradation of Vitamin B6 in Chickpeas (Cicer arietinum L.) during Hydrothermal Treatments: A Kinetic Approach

Chickpeas are more sustainable than other food systems and have high a nutritional value, especially regarding their vitamin composition. One of the main vitamins in chickpeas is vitamin B6, which is very important for several human metabolic functions. Since chickpeas are consumed after cooking, our goal was to better understand the role of leaching (diffusion) and thermal degradation of vitamin B6 in chickpeas during hydrothermal processing. Kinetics were conducted at four temperatures, ranging from 25 to 85 °C, carried out for 4 h in an excess of water for the diffusion kinetics, or in hermetic bags for the thermal degradation kinetics. Thermal degradation was modeled according to a first-order reaction, and diffusion was modeled according to a modified version of Fick's second law. Diffusivity constants varied from 4.76 × 10-14 m2/s at 25 °C to 2.07 × 10-10 m2/s at 85 °C; the temperature had an impact on both the diffusivity constant and the residual vitamin B6. The kinetic constant ranged from 9.35 × 10-6 at 25 °C to 54.9 × 10-6 s-1 at 85 °C, with a lower impact of the temperature. In conclusion, vitamin B6 is relatively stable to heat degradation; loss is mainly due to diffusion, especially during shorter treatment times.

Synergistic effect of graphene oxide/zinc oxide nanocomposites on polylactic acid-based active packaging film: Properties, release kinetics and antimicrobial efficiency

Incorporating two different nanoparticles in nanocomposite films is promising as their synergistic effects could significantly enhance polymer performance. Our previous work conferred the remarkable antimicrobial (AM) properties of the polylactic acid (PLA)-based film using optimal formulations of synergistic graphene oxide (GO)/zinc oxide (ZnO) nanocomposites. This study further explores the release profile of GO/ZnO nanocomposite and their impact on the antimicrobial properties. A fixed 1.11 wt% GO and different ZnO concentrations were well dispersed in the PLA matrix. Increasing ZnO concentrations tended to increase agglomeration, as evident in rougher surfaces. Agglomeration inhibited water penetration, leading to a significant reduction in water permeability (46.3 %), moisture content (31.6 %) but an improvement in Young's Modulus (52.6 %). The overall and specific migration of GO/ZnO nanocomposites was found to be within acceptable limits. It is inferred that the release of Zn2+ ions followed pseudo-Fickian behavior with an initial burst effect. AM film with the highest concentration of ZnO (1.25 wt%) exhibited the highest inhibition rate against Escherichia coli (68.0 %), Bacillus cereus (66.5 %), Saccharomyces cerevisiae (70.9 %). Results suggest that GO/ZnO nanocomposites with optimal ZnO concentrations have the potential to serve as promising antimicrobial food packaging materials, offering enhanced barrier, antimicrobial properties and a controlled release system.

Assessment of the stability of compounds belonging to neglected phenolic classes and flavonoid sub-classes using reaction kinetic modeling

Phenolic compounds are known to degrade and/or undergo changes during food production and storage. Reaction kinetic modeling is generally used to define kinetic parameters of a food system and predict changes during thermal processing and storage. Data for phenolic acids and flavonoids, such as anthocyanins and flavan-3-ols, have been reviewed in detail, but the flavonoid sub-classes, dihydrochalcones and flavanones, have been mostly neglected. Other neglected phenolic classes are xanthones and benzophenones. The stability of these types of compounds is important as they are present in fruits and exposed to heat when processed into juice and jam. Other sources of the compounds are herbal teas, which are also subjected to thermal processing, either during the primary processing of the plant material, or the production of extracts for use as food ingredients. The theoretical background is given to understand the review of literature on these classes/sub-classes. Results of research on kinetic modeling are discussed in detail, while research on compound stability without the application of reaction kinetic modeling is briefly mentioned to provide context. The studies discussed included those focusing on heating during the processing and storage of model solutions, liquid foods, plant material, dried extracts, and extracts formulated with other food ingredients.

Reaction kinetics of aspalathin degradation and flavanone isomer formation in aqueous model solutions: Effect of temperature, pH and metal chelators

The poor stability of aspalathin in aqueous solutions is a major challenge in delivering a shelf-stable ready-to-drink (RTD) green rooibos iced tea. The kinetics of aspalathin degradation and the formation of eriodictyol glucoside isomers [(S/R)-6-β-D-glucopyranosyleriodictyol and (S/R)-8-β-D-glucopyranosyleriodictyol] in aqueous buffers were modeled to understand and predict aspalathin losses during heat processing. The effects of temperature and pH on the rate constants of aspalathin degradation and eriodictyol glucoside isomer formation were determined in a 0.1 M phosphate buffer with 5.7 mM citric acid. The zero-order model best described the reaction kinetics of aspalathin degradation and eriodictyol glucoside isomer formation. Increasing the temperature and pH increased the reaction rate constants. The activation energies of the reactions were much lower at pH 6 than at pH 4, indicating that pH affected the temperature dependence of the reactions. The 8-C-glucosyl eriodictyol derivatives (RE8G and SE8G) formed at much lower rates than the 6-C-glucosyl eriodictyol derivatives (RE6G and SE6G). The metal chelators, citric acid, citrate and EDTA, drastically reduced the reaction rate constants, indicating the catalytic role of metal ions in aspalathin autoxidation. The results of the study could assist manufacturers to improve the shelf life of rooibos RTD beverages by changing the formulation and adjusting heat processing conditions.

Investigation of cryoprotectants-treated surimi protein deterioration during chilled and frozen storage: Functional properties and kinetic modeling

The relative cryoprotective effects of flaxseed protein hydrolysate and pectin in comparison with conventional cryoprotectant (sucrose + sorbitol + sodium tripolyphosphates) on stabilization of proteins in surimi of Capoor (Cyprinus carpio) were investigated during freezing (-20°C for 4 months) and chilling storage (4°C for 10 days). Although pectin caused to improve water-holding capacity (27.8%; 4°C and 21.5%; -20°C) on account of highly more inhibitory impact on the ice crystals growth, the protein denaturation may have occurred. It can be related to higher reduction in the amount of salt extractable protein (%) and the immeasurable value of thiol group in surimi formulation containing pectin compared with other cryoprotectants. The results of modeling surimi samples showed that salt extractable protein and sulfhydryl content were in good agreement with the first-order reaction model at -20°C and second-order kinetic model at 4°C. In comparison with other samples, samples treated with flaxseed protein showed the lowest reaction rate constant during chilled and frozen storage. The results confirmed that flaxseed protein with no sweetness and considerable caloric value had a cryoprotective effect similar to sucrose + sorbitol + polyphosphate and even better.

Integrating the latest biological advances in the key steps of a food packaging life cycle

This literature review provides a focus on the potential of integrating the latest scientific and technological advances in the biological field to improve the status of the key steps of a food packaging life cycle: production, usage, post-usage, and long-term fate. A case study of such multi-biological food packaging is demonstrated based on the use of PHAs (polyhydroxyalkanoates) polymer, a microbiologically produced polymer from non-food renewable resources, activated by the use of bioactive components to enhance its usage benefits by reducing food loss and waste, displaying potential for reusability, compostability as post-usage, and finally, being ultimately biodegradable in most common natural conditions to considerably reduce the negative impact that persistent plastics have on the environment. We discuss how designing safe and efficient multi "bio" food packaging implies finding a compromise between sometimes contradictory functional properties. For example, active antimicrobials help preserve food but can hamper the ultimate biodegradation rate of the polymer. This review presents such antagonisms as well as techniques (e.g., coatings, nanoencapsulation) and tools (e.g., release kinetic) that can help design optimized, safe, and efficient active food packaging.

Application of Dispersive Liquid-Liquid Aerosol Phase Extraction to the Analysis of Total and Individual Phenolic Compounds in Fried Extra Virgin Olive Oils

Seventeen extra virgin olive oil samples from Valencian Community (Spain) were submitted to a domestic-frying process (180 °C) during different degradation times (5, 10, 30, 60, 120 min). A dispersive liquid-liquid aerosol phase extraction by using a methanol/water (50:50) extracting solution was used to isolate the polyphenol fraction. Total phenolic content (TPC) was determined, whereas the determination of seven individual target polyphenolic compounds (hydroxytyrosol, tyrosol, oleuropein, vanillic acid, p-coumaric acid, ferulic acid, and vanillin) was carried out by using ultrahigh-performance liquid chromatography coupled to a tandem mass spectrometer. Statistically significant differences in the TPC values were found for Blanqueta and Manzanilla samples from different harvesting years. The domestic-frying process impacted the TPC and the individual phenolic compounds content. Thermal treatment for 2 h gave rise to a 94% decrease in the TPC. A first-order kinetic model was suitable to accurately describe the degradation of the individual phenolic compounds.

Inactivation kinetics of a surrogate yield conservative predictions of foodborne pathogen reductions from low water activity foods of varying size and composition during low-temperature steam processing

There is a growing interest in using models to predict foodborne pathogen inactivation as a way to validate or verify preventive controls. Unlike liquid foods, solid, low water activity foods (LWAF) are heterogenous in composition and structure and do not transfer heat uniformly. Using models constructed from one food to predict pathogen inactivation on another LWAF is complex and may not always be possible, even if the foods have similar composition. Using models constructed from inactivation kinetics of three foodborne pathogens and a surrogate from vacuum-steam-pasteurized (72 and 82 °C) whole macadamia nuts and dried apricot halves, 3-log reductions were predicted for the same pathogens and foods of reduced size. Model fits (First-order, Weibull, and Gompertz) were significantly impacted by the food type regardless of particle size. Despite the foods being identical in composition with particle size as the only altered characteristic, best-fit models accurately predicted the 3-log reductions only 50% of the time, but the surrogate inactivation models provided conservative predictions for pathogen reductions, highlighting that a surrogate's model may be a suitable tool for predicting pathogen reduction on LWAFs.

The volatile profile of pasteurized leek (Allium ampeloprasum var. porrum) and Brussels sprouts (Brassica oleracea var. gemmifera) (products), as a witness to (bio)chemical reactivity, influenced by pretreatment and successive refrigerated storage

Processing can affect (bio)chemical conversions in vegetables and can act on their volatile properties accordingly. In this study, the integrated effect of pretreatment and pasteurization on the volatile profile of leek and Brussels sprouts and the change of this profile upon refrigerated storage were investigated. Pretreatments were specifically selected to steer biochemical reactivities to different extents. Volatile profiles were analyzed by headspace-solid phase microextraction-gas chromatography-mass spectrometry. For both vegetables, it was observed that different pretreatments prior to a pasteurization step led to diverse volatile profiles. The differences in volatile profiles observed in the different samples were presumably attributed to the different degrees of enzymatic conversions, further conversions of enzymatically formed products and thermally induced reactivities. Interestingly, the observed initial relative differences between volatile profiles of differently pretreated pasteurized samples were still observed after a refrigerated storage of 4 weeks at 4 °C. In conclusion, refrigerated storage only limitedly affected the resulting volatile profile.

Black Tea Extracts/Polyvinyl Alcohol Active Nanofibers Electrospun Mats with Sustained Release of Polyphenols for Food Packaging Applications

The efficiency in the capabilities to store and release antioxidants depends on the film morphology and its manufacturing process, as well as on the type and methodology used to obtain the polyphenol extracts. Here, hydroalcoholic extracts of black tea polyphenols (BT) were obtained and dropped onto different polyvinyl alcohol (PVA) aqueous solutions (water or BT aqueous extract with and without citric acid, CA) to obtain three unusual PVA electrospun mats containing polyphenol nanoparticles within their nanofibers. It was shown that the mat obtained through the nanoparticles precipitated in BT aqueous extract PVA solution presented the highest total polyphenol content and antioxidant activity, and that the addition of CA as an esterifier or PVA crosslinker interfered with the polyphenols. The release kinetics in different food simulants (hydrophilic, lipophilic and acidic) were fitted using Fick's diffusion law and Peppas' and Weibull's models, showing that polymer chain relaxation is the main mechanism in all food simulants except for the acidic, which presented an abrupt release by Fick's diffusion mechanism of about 60% before being controlled. This research provides a strategy for the development of promising controlled-release materials for active food packaging, mainly for hydrophilic and acidic food products.

Computer-aided food engineering

Computer-aided food engineering (CAFE) can reduce resource use in product, process and equipment development, improve time-to-market performance, and drive high-level innovation in food safety and quality. Yet, CAFE is challenged by the complexity and variability of food composition and structure, by the transformations food undergoes during processing and the limited availability of comprehensive mechanistic frameworks describing those transformations. Here we introduce frameworks to model food processes and predict physiochemical properties that will accelerate CAFE. We review how investments in open access, such as code sharing, and capacity-building through specialized courses could facilitate the use of CAFE in the transformation already underway in digital food systems.

Production of Marinated Chinese Lotus Root Slices Using High-Pressure Processing as an Alternative to Traditional Thermal-and-Soaking Procedure

Marinated vegetables are traditional cold dishes with a long history and special flavor in the Chinese deli market. However, the traditional thermal-and-soaking (TS) procedure often results in unreproducible flavor quality properties of marinated vegetables and waste of brine and time in production. A novel green and sustainable technique, high-pressure processing (HPP), has caught the attention of the food industry. In this study, the effects of HPP and TS treatment on the visual, flavor, textural, and microbiological qualities of Chinese marinated lotus root slices were investigated. Compared to the TS products, lighter color, more varieties of volatile compounds, and crunchier texture were detected in the HPP products. Throughout the 4 °C, 25 °C, and 45 °C shelf life challenges, the HPP products retained their original color and crunchiness better than the TS ones, whereas no significant differences were found in total viable counts (TVCs) in the first half of the shelf lives. The Arrhenius model under the first-order reaction of TVC deterioration showed a good fit to the shelf life of the HPP marinated lotus root slices. This study demonstrates that HPP may assist in making the best use of brine in a more time-efficient manner to improve the visual, flavor, and textural quality of traditional Chinese marinated lotus root slices.

Monitoring the Shelf Life of Refined Vegetable Oils under Market Storage Conditions-A Kinetic Chemofoodmetric Approach

Most physicochemical and sensory properties of edible vegetable oils are not stable over time. One of the main causes of quality depletion of vegetable oils is oxidation, which influences sensory acceptability and nutritional value, and could even lead to toxic compounds. That negative influence affects international refined oil prices and the variety of its culinary applications. Modelling quality depletion of vegetable oils and establishing the shelf life, generally accepted as the time until rancidity becomes evident, already remains a challenge for the industry. Hence, this paper will show a promising chemofoodmetric methodology, as an easy and straightforward tool to estimate the current shelf-life of refined vegetable oils, based on a comprehensive characterisation of quality depletion-related changes over storage time under real market conditions. The methodology for building a multivariate kinetic ageing-based model is described, taking into account all time-related physicochemical parameters and chemometric processing tools. From a particular ageing state, multiparametric models are able to reliably infer the expected storage time for each vegetable oil so that it remains consistent with acceptability requirements. The results of the study pointed out the accuracy of multivariate shelf-life modelling with regard to univariate modelling. Discrepancies were found in the oxidation rates of oils extracted from different plant seeds.

Modelling of the nutritional behaviour of cowpea seeds during soaking, germination and cooking process

Two modelling approaches previously developed and describing separately the diffusion-reaction of folates and alpha-galactosides during cowpea seed soaking, germination and cooking processes were combined here to simulate the effect of some key processing parameters on the nutritional value of cowpea seeds. The simulator was upgraded, considering thermal-pH dependency of both diffusivities and reactivities of folates and alpha-galactosides together with water-to-seed ratio and starch gelatinization. The simulations showed that soaking and cooking processes were deleterious for folates whereas germination promoted the production of folates while reducing alpha-galactosides concentration. This study suggests that a long germination (96 h), followed by a short cooking seems to be optimal both in terms of nutritional value and degree of cooking.

Digital Food Twins Combining Data Science and Food Science: System Model, Applications, and Challenges

The production of food is highly complex due to the various chemo-physical and biological processes that must be controlled for transforming ingredients into final products. Further, production processes must be adapted to the variability of the ingredients, e.g., due to seasonal fluctuations of raw material quality. Digital twins are known from Industry 4.0 as a method to model, simulate, and optimize processes. In this vision paper, we describe the concept of a digital food twin. Due to the variability of the raw materials, such a digital twin has to take into account not only the processing steps but also the chemical, physical, or microbiological properties that change the food independently from the processing. We propose a hybrid modeling approach, which integrates the traditional approach of food process modeling and simulation of the bio-chemical and physical properties with a data-driven approach based on the application of machine learning. This work presents a conceptual framework for our digital twin concept based on explainable artificial intelligence and wearable technology. We discuss the potential in four case studies and derive open research challenges.

Effects of the Frying and Drying Conditions on the Furan Formation in Instant-Noodle Manufacturing

In this study, furan analysis was conducted in instant fried and dried noodles manufactured under various frying and drying conditions, respectively. Instant fried noodles were manufactured via five different frying durations (30-150 s). The levels of furan formed in the fried noodles during the manufacturing process ranged from 4.26 to 41.8 ng/g. The instant dried noodles were manufactured at four different temperatures (80-130 °C). The levels of furan formed in the dried noodles ranged from 3.99 to 4.11 ng/g. The black-bean paste, which is the main ingredient of the black-bean sauce, had the highest furan level (16.5-2484 ng/g) in instant noodles. Our results showed that the furan formation increased with the frying temperature and duration of the black-bean paste (p < 0.05). The activation energy (E_a) in the black-bean paste was estimated at 58.627 kJ/mol by using the Arrhenius formula. The calculated E_a was similar to the E_a of the general chemical reaction. The results of this study might be useful to minimize the furan formation in the manufacture of instant noodles.

Kinetic Modeling of Quality Changes and Shelf Life Prediction of Dried Coconut Chips

The color, texture and rancidity of dried fruit are critical parameters to control for consumer acceptance. The goal of this research was to investigate the kinetics of color parameter changes and texture in terms of the crispness and peroxide value (PV) of dried coconut chips by using zero-, first- and second-order kinetic reactions during storage at different temperatures, as well as shelf life prediction using the accelerated method. The outcomes demonstrated that the zero-order kinetic reaction was appropriate to describe the change in color, crispness and PV of dried coconut chips during storage (R2 = 0.9690–0.9899). The rancidity had a higher correlation than the texture and color changes used to assign the quality essence. The activation energy (Ea) for the PV change was 11.83 kJ/mol. Therefore, the shelf life expectancy of the dried coconut chips was estimated to be 144, 128 and 115 days at 35, 45 and 55 °C, respectively. Meanwhile, the shelf life of products stored at ambient temperature was 159 days, and those products were stored in the refrigerator for 194 days. The findings provide retailers and consumers the ability to choose the ideal temperature and storage time for dried coconut chips in order to ensure the product’s quality.

Shelf-Life Prediction and Critical Value of Quality Index of Sichuan Sauerkraut Based on Kinetic Model and Principal Component Analysis

Kinetic models and accelerated shelf-life testing were employed to estimate the shelf-life of Sichuan sauerkraut. The texture, color, total acid, microbe, near-infrared analysis, volatile components, taste, and sensory evaluation of Sichuan sauerkraut stored at 25, 35, and 45 °C were determined. Principal component analysis (PCA) and Fisher discriminant analysis (FDA) were used to analyze the e-tongue data. According to the above analysis, Sichuan sauerkraut with different storage times can be divided into three types: completely acceptable period, acceptable period, and unacceptable period. The model was found to be useful to determine the critical values of various quality indicators. Furthermore, the zero-order kinetic reaction model (R², 0.8699-0.9895) was fitted better than the first-order kinetic reaction model. The Arrhenius model (E_a value was 47.23-72.09 kJ/mol, k_ref value was 1.076 × 10⁶-9.220 × 10¹⁰ d^-1) exhibited a higher fitting degree than the Eyring model. Based on the analysis of physical properties, the shelf-life of Sichuan sauerkraut was more accurately predicted by the combination of the zero-order kinetic reaction model and the Arrhenius model, while the error back propagation artificial neural network (BP-ANN) model could better predict the chemical properties. It is a better choice for dealers and consumers to judge the shelf life and edibility of food by shelf-life model.

Digital twins enable the quantification of the trade-offs in maintaining citrus quality and marketability in the refrigerated supply chain

Supply chains of fresh fruit must maintain a very narrow window of hygrothermal conditions after harvest. Any excursions outside this range can markedly lower the consumer acceptability of the fruit. However, the loss in fruit quality and marketability largely remains invisible to stakeholders throughout the supply chain. Here we developed a physics-based digital twin of citrus fruit to pinpoint when, why and to what extent fruit quality and marketability are reduced. Sensor data on 47 commercial shipments are thereby translated into actionable metrics for supply chain stakeholders by mapping the variability using principal component analysis. We unveiled a large spread (between 3% and 60%) in the shipments for different metrics of quality and marketability. Half of the shipments currently lie outside the ideal trade-off range between maintaining quality, killing fruit fly larvae and avoiding chilling injury. The digital twin technology opens the possibility to obtain the real-time coupling with sensor data to monitor food quality and marketability.

Modeling of Chilled/Supercooled Pork Storage Quality Based on the Entropy Weight Method

Simple Summary

The quality of chilled meat is difficult to predict because many quality indexes need to be considered. The waste of meat resources caused by improper storage has caused huge economic losses in the meat industry. The entropy weight method (EWM) was widely used as an effective method of infusion of multiple attributes into a single index of food quality. In this study, the model based on the entropy weight method was used to predict and comprehensively evaluate the quality changes in chilled pork, and the relative error range between the measured and predicted shelf life was lower than 11%. The modeling based on EWM integrates the information from each quality index and provides accurate quality prediction, which will enable the food industry to enhance accurate judging of the shelf life and safety of meat.

Abstract

The entropy weight method (EWM) was developed and used to integrate multiple quality indexes of pork to generate a comprehensive measure of quality. The Arrhenius equation and chemical kinetic reaction were used to fit and generate the shelf life prediction model. The pork was stored at the temperatures of 7 °C, 4 °C, 1 °C and −1 °C. Quality indexes, such as drip loss, color, shear force, pH, TAC, TVB-N and TBARS were measured. The results show that low temperatures effectively delay microbial growth and lipid oxidation. The regression coefficients (R²) for the comprehensive scores at each temperature were greater than 0.973 and the activation energy Ea was 9.7354 × 104 kJ mol⁻¹. The predicted shelf life of pork stored at 7 °C, 4 °C, 1 °C and −1 °C was 4.35 d, 6.85 d, 10.88 d and 14.90 d, respectively. In conclusion, EWM is an effective method to predict the shelf life of chilled/supercooled pork.

Modelling Virgin Olive Oil Potential Shelf-Life from Antioxidants and Lipid Oxidation Progress

The development of effective shelf-life prediction models is extremely important for the olive oil industry. This research is the continuation of a previous accelerated shelf-life test at mild temperature (40–60 °C), applied in this case to evaluate the oxidation effect of temperature on minor components (phenols, tocopherol, pigments) to properly complete a shelf-life predictive model. The kinetic behaviour of phenolic compounds, α-tocopherol and pigments during storage of different virgin olive oil samples at different temperatures (25–60 °C) is reported. Hydroxytyrosol, tyrosol and α-tocopherol fitted to pseudo-zero-order kinetics, whereas secoiridoid derivatives of hydroxytyrosol and tyrosol, o-diphenols and total phenols apparently followed pseudo-first-order kinetics. The temperature-dependent kinetic of phenolic compounds and α-tocopherol were well described by the linear Arrhenius model. The apparent activation energy was calculated. Principal component analysis was used to transform the considered compositional and degradation variables into fewer uncorrelated principal components resulting in 4: “no oxidizable substrate”, “initial oxidation state and conditions”, “free simple phenols”, and “degradation rates”. In addition, multivariate linear regression was used to yield several modelling equations for shelf-life prediction, considering initial composition and experimental variables easily determined in accelerated storage.

Kinetic study on peroxidase inactivation and anthocyanin degradation of black cherry tomatoes (Solanum lycopersicum cv. OG) during blanching

Introduction

Blanching is a necessary treatment stage in processing of tomato products to inactivate enzymes. However, it may cause the degradation of nutrients.

Objective

In this study, the kinetics of thermal peroxidase inactivation and anthocyanin degradation in black cherry tomatoes (cv. OG) were determined to predict the quality changes during the blanching.

Methods

Tomatoes were blanched at five levels of temperature (75–95oC) for five time periods (30–150 s).

Results

It was found that as the blanching temperature increased and the blanching time is prolonged, more peroxidase was inactivated and the greater number of anthocyanins was lost. The thermal peroxidase inactivation and anthocyanin degradation showed an apparent first-order reaction with the activation energy of 129.96 kJ/mol and 65.99 kJ/mol, respectively. Peroxidase and anthocyanin in black cherry tomatoes were found to be heat-sensitive.

Conclusion

These kinetic parameters were necessary to select and design appropriate blanching conditions for black cherry tomatoes on larger scale processing.

Advances in the control of lipid peroxidation in oil-in-water emulsions: kinetic approaches†

Large efforts have been, and still are, devoted to minimize the harmful effects of lipid peroxidation. Much of the early work focused in understanding both the lipid oxidation mechanisms and the action of antioxidants in bulk solution. However, food-grade oils are mostly present in the form of oil-in-water emulsions, bringing up an increasing complexity because of the three-dimensional interfacial region. This review presents an overview of the kinetic approaches employed in controlling the oxidative stability of edible oil-in-water emulsions and of the main outcomes, with particular emphasis on the role of antioxidants and on the kinetics of the inhibition reaction. Application of physical-organic chemistry methods, such as the pseudophase models to investigate antioxidant partitioning, constitute a remarkable example on how kinetic methodologies contribute to model chemical reactivity in multiphasic systems and to rationalize the role of interfaces, opening new opportunities for designing novel antioxidants with tailored properties and new prospects for modulating environmental conditions in attempting to optimize their efficiency. Here we will summarize the main kinetic features of the inhibition reaction and will discuss on the main factors affecting its rate, including the determination of antioxidant efficiencies from kinetic profiles, structure-reactivity relationships, partitioning of antioxidants and concentration effects.

Oleogelation of extra virgin olive oil by different oleogelators affects the physical properties and the stability of bioactive compounds

Extra virgin olive oil (EVOO) was gelled with 10% monoglycerides, (MG), rice wax (RW), γ-oryzanol, and β-sitosterol (PS), or ethylcellulose (EC). The oleogel structure and the stability of bioactive compounds were investigated during storage up to 120 days at 20, 30, and 40 °C. All samples were self-standing but presented different structures. PS produced the firmest gel, whereas EC caused the lowest firmness and rheological values. Structural properties did not change during storage, except for EC oleogel. Structuring triggered a depletion in phenolic content and α-tocopherol, which was more pronounced when a higher temperature was required for oleogel preparation (MG ~ RW < PS < EC). However, during storage phenolics and α-tocopherol decreased following zero-order kinetics with a higher susceptibility in unstructured oil, suggesting in all cases a protective effect of the gel network.

Application of multivariate data analysis for food quality investigations: An example-based review

These days, large multivariate data sets are common in the food research area. This is not surprising as food quality, which is important for consumers, and its changes are the result of a complex interplay of multiple compounds and reactions. In order to comprehensively extract information from these data sets, proper data analysis tools should be applied. The application of multivariate data analysis (MVDA) is therefore highly recommended. However, at present the use of MVDA for food quality investigations is not yet fully explored. This paper focusses on a number of MVDA methods (PCA (Principal Component Analysis), PLS (Partial Least Squares Regression), PARAFAC (Parallel Factor Analysis) and ASCA (ANOVA Simultaneous Component Analysis)) useful for food quality investigations. The terminology, main steps and the theoretical basis of each method will be explained. As this is an example-based review, each method was applied on the same experimental data set to give the reader an idea about each selected MVDA method and to make a comparison between the outcomes. Numerous MVDA methods are available in literature. Which method to select depends on the data set and objective. PCA should be the first choice for data exploration of two-dimensional data. For predictive purposes, PLS is the most appropriate method. Given an underlying experimental design, ASCA takes into account both the relation between the different variables and the design factors. In case of a multi-way data set, PARAFAC can be used for data exploration. While these methods have already proven their value in research, there is a need to further explore their potential to investigate the complex interplay of compounds and reactions contributing to food quality. With this work we would like to encourage food scientists with no or limited knowledge of MVDA to get some first insights into the selected methods.

Pecan color change during storage: Kinetics and Modeling of the Processes

Postharvest changes in pecan nutmeat color are affected by many factors, both internal and external. The temperature, relative humidity (RH) of the surrounding environment, and storage time are major factors contributing to color deterioration of the nutmeats. Kinetic models have long been employed to provide insights into the physical and chemical changes in food systems; however, no kinetic model has been developed describing the color changes of pecan nutmeats during storage. The objective of this research was to determine the effect of temperature, RH and storage time on pecan nutmeat color change. Pecan nutmeats of three commercially important cultivars (Stuart, Pawnee and Desirable) were subjected to different temperatures (20, 30 and 40 °C) and RH conditions (30, 50, 75% and 80%) for up to 450 days in simulated storage. The observed color changes of the pecan nutmeats were measured as lightness, chroma and hue (LCh). Additionally, the USDA pecan color rating scale was digitized to encourage its use among researchers. It was observed that the change in hue followed a zero-order decay whereas change in lightness and chroma followed a first-order decay. The value of the reaction constants ranged from 0.010 to 1.315 day⁻¹. An Arrhenius model was used to estimate the activation energy (E_a) corresponding to different storage conditions. The values revealed significant effects of temperature, RH and storage days on color degradation. The breakdown of flavonoids and reaction products from Maillard browning could be responsible for the formation of the reddish-brown color observed in degraded nutmeats. The kinetic parameters and models were used to develop a user-friendly online interface for predicting color change depending on selected parameters, with illustrations of the resulting pecan color (https://tinyurl.com/uspecans). The results of this study will aid pecan growers, processors and researchers to predict and visualize changes in color of pecan nutmeats during storage under various conditions of temperature and RH, and duration of storage. Although the study used cultivars Stuart, Pawnee and Desirable, the results likely have more general applicability to other cultivars too.

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A systematic investigation of the kinetics associated with pecan color change during storage was conducted.

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Temperature and relative humidity (RH) affected rate constants (k) and activation energy (E_a) of pecan color.

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A digital version of the USDA pecan color scale was developed.

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An online model was built for pecan color prediction (https://tinyurl.com/uspecans).