Fenton-mediated oxidation in the presence and absence of oxygen

The increased use of Fenton systems for the treatment of contaminated waters and wastewaters necessitates the development of kinetic models capable of accurately simulating key species concentrations in order to optimize system performance and efficiency. In this work a reaction mechanism in which the hydroxyl radical is nominated to be the active oxidant in Fenton systems is used to describe the oxidation of formic acid (HCOOH) under a variety of experimental conditions. A kinetic model based on this reaction mechanism is shown to adequately describe results of experiments in which starting concentrations of H202 and HCOOH varied over 1 and 4 orders of magnitude, respectively, under both air-saturated and deaerated conditions. The intermediate generated during HCOOH oxidation was observed to increase oxidation efficiency, especially at high initial organic concentrations [relative to Fe(II)], by assisting in the redox cycling of iron. In the presence of oxygen, however, such improvement was attenuated through competition for the organic intermediates. While mechanistic analysis and associated kinetic modeling is invaluable in optimization of Fenton systems, a clear understanding of reaction byproducts and their reactivity toward other species in the system is critical for accurate simulations.     

Modeling Lycopene Degradation and Isomerization in the Presence of Lipids

The kinetics of thermally induced degradation and isomerization of lycopene in olive oil, fish oil, and an olive oil/tomato emulsion were studied in detail. Special attention was paid to the isomerization reactions using a multi-response modeling approach. The type of oil had a significant impact on lycopene degradation kinetics, being faster in fish oil compared with olive oil. The estimated kinetic parameters to describe lycopene degradation in olive oil were not significantly different from those in an olive oil/tomato emulsion. The overall Z-isomer formation and elimination in olive oil, fish oil, and olive oil/tomato emulsion was similar. Only the kinetic parameters for 13-Z-lycopene formation differed significantly in the two oils. Although the isomerization rate constants for the emulsion were lower than for olive oil, the isomerization reactions showed similar temperature dependency. This study shows that the kinetics of thermally induced degradation and isomerization of lycopene in oil and in an olive oil/tomato emulsion can be described using the same model. The food system, however, has an influence on the model parameters, especially on the rate constants.     

Modeling food matrix effects on chemical reactivity: Challenges and perspectives

ABSTRACT

The same chemical reaction may be different in terms of its position of the equilibrium (i.e., thermodynamics) and its kinetics when studied in different foods. The diversity in the chemical composition of food and in its structural organization at macro-, meso-, and microscopic levels, that is, the food matrix, is responsible for this difference. In this viewpoint paper, the multiple, and interconnected ways the food matrix can affect chemical reactivity are summarized. Moreover, mechanistic and empirical approaches to explain and predict the effect of food matrix on chemical reactivity are described. Mechanistic models aim to quantify the effect of food matrix based on a detailed understanding of the chemical and physical phenomena occurring in food. Their applicability is limited at the moment to very simple food systems. Empirical modeling based on machine learning combined with data-mining techniques may represent an alternative, useful option to predict the effect of the food matrix on chemical reactivity and to identify chemical and physical properties to be further tested. In such a way the mechanistic understanding of the effect of the food matrix on chemical reactions can be improved.     

Approaches to analysis and modeling texture in fresh and processed foods – A review

Texture analysis and modeling are important techniques in food and postharvest research and industrial practice. A wide range of methods have been used to evaluate instrumental results, which provide time-series data of product deformation, thereby allowing a wide range of texture attributes to be calculated from force–time or force–displacement data. Several indices of texture such as the firmness index, crunchiness index and texture index based on “vibration energy density” have been reported, but these are not widely used to quantify food texture. Some modeling and statistical approaches have been adopted to analyze food texture data, including chemical reaction kinetics and the Michaelis–Menton type decay function, mechanistic autocatalytic models based on logistic equation, and the finite element method. However, increasing demand for comprehensive approaches to texture profile analysis, generalized texture indices and fundamental texture models still remain challenges in the food research and industry.     

The kinetics of thermal generation of flavour

Control and optimisation of flavour is the ultimate challenge for the food and flavour industry. The major route to flavour formation during thermal processing is the Maillard reaction, which is a complex cascade of interdependent reactions initiated by the reaction between a reducing sugar and an amino compound. The complexity of the reaction means that researchers turn to kinetic modelling in order to understand the control points of the reaction and to manipulate the flavour profile. Studies of the kinetics of flavour formation have developed over the past 30 years from single‐ response empirical models of binary aqueous systems to sophisticated multi‐response models in food matrices, based on the underlying chemistry, with the power to predict the formation of some key aroma compounds. This paper discusses in detail the development of kinetic models of thermal generation of flavour and looks at the challenges involved in predicting flavour. Copyright © 2012 Society of Chemical Industry     

预测微生物学数学建模的方法构建

预测微生物学是运用微生物学、工程数学以及统计学进行数学建模,利用所建模型预测和描述处在特定食品环境下微生物的生长和死亡。预测微生物学的核心在于建立完善的数学模型。预测微生物学数学模型被分为三级:初级模型、二级模型和三级模型。初级模型描述微生物数量变化与时间的关系;二级模型描述初级模型中的参数与环境参数之间的关系;三级模型也称为专家系统,是在初级模型和二级模型的基础上,通过计算机编程制作出的友好软件,它使得非专业人士同样可以获得预测微生物学的相关信息和指导。本文介绍了预测微生物学模型的局限以及分类,并对建模方法进行了讨论。     

Multiscale modeling in food engineering

Since many years food engineers have attempted to describe physical phenomena such as heat and mass transfer that occur in food during unit operations by means of mathematical models. Foods are hierarchically structured and have features that extend from the molecular scale to the food plant scale. In order to reduce computational complexity, food features at the fine scale are usually not modeled explicitly but incorporated through averaging procedures into models that operate at the coarse scale. As a consequence, detailed insight into the processes at the microscale is lost, and the coarse scale model parameters are apparent rather than physical parameters. As it is impractical to measure these parameters for the large number of foods that exist, the use of advanced mathematical models in the food industry is still limited. A new modeling paradigm – multiscale modeling – has appeared that may alleviate these problems. Multiscale models are essentially a hierarchy of sub-models which describe the material behavior at different spatial scales in such a way that the sub-models are interconnected. In this article we will introduce the underlying physical and computational concepts. We will give an overview of applications of multiscale modeling in food engineering, and discuss future prospects.     

CONSIDERATIONS IN CALCULATING KINETIC PARAMETERS FROM EXPERIMENTAL DATA

Engineers require quantitative models to design and optimize processes. In the food industry, these process models become very complex because of the unique physical/chemical characteristics and variability of the raw material. Furthermore, frequently data describing rates of reactions and/or changes in foods are generated by food scientists who are not thoroughly familiar with reaction models. Analysis of those data to obtain parameters for reaction models thus becomes critical. In this paper, calculating kinetic parameters from experimental data is examined, and suggestions are presented for determining reaction rates and temperature dependence.     

Modeling the release of food bioactive ingredients from carriers/nanocarriers by the empirical,semiempirical, and mechanistic models

The encapsulation process has been utilized in the field of food technology to enhance the technofunctional properties of food products and the delivery of nutraceutical ingredients via food into the human body. The latter application is very similar to drug delivery systems. The inherent sophisticated nature of release mechanisms requires the utilization of mathematical equations and statistics to predict the release behavior during the time. The science of mathematical modeling of controlled release has gained a tremendous advancement in drug delivery in recent years. Many of these modeling methods could be transferred to food. In order to develop and design enhanced food controlled/targeted bioactive release systems, understanding of the underlying physiological and chemical processes, mechanisms, and principles of release and applying the knowledge gained in the pharmaceutical field to food products is a big challenge. Ideally, by using an appropriate mathematical model, the formulation parameters could be predicted to achieve a specific release behavior. So, designing new products could be optimized. Many papers are dealing with encapsulation approaches and evaluation of the impact of process and the utilized system on release characteristics of encapsulated food bioactives, but still, there is no deep insight into the mathematical release modeling of encapsulated food materials. In this study, information gained from the pharmaceutical field is collected and discussed to investigate the probable application in the food industry.     

A review of kinetic models for inactivating microorganisms and enzymes by pulsed electric field processing

As a non-thermal technology, pulsed electric field (PEF) treatment can be utilized in food processing and bioengineering for the inactivation of microorganisms and quality-degrading enzymes, as well as the retention of health-related compounds and the extension of shelf-life. Development of kinetic models that fit the degree of microbial inactivation and the loss of food quality is important to improve the efficiency of PEF treatment. The current review aims to provide an overview of the kinetic models used by PEF for microbial inactivation in liquid foods. Kinetics modeling for the destruction of microorganisms, inactivation of enzymes, retention of health-related compounds, and extension of shelf-life are discussed. Additionally, the fitting accuracy of several models, as well as issues that need further investigation, are discussed to promote further understanding and the deployment of PEF technology.     

Kinetic Modeling of Food Quality: A Critical Review

ABSTRACT: This article discusses the possibilities to study relevant quality aspects of food, such as color, nutrient content, and safety, in a quantitative way via mathematical models. These quality parameters are governed by chemical, biochemical, microbial, and physical changes. It is argued that the modeling of such quality aspects is in fact kinetic modeling. Therefore, attention is paid to chemical kinetics, and its possibilities and limitations are discussed when applied to changes occurring in foods. The discussion is illustrated with examples from the literature. A major difficulty is that principles from chemical kinetics are strictly speaking only valid for simple elementary reactions, and foods are all but simple. Interactions in the food matrix and variability are 2 complicating factors. It is discussed how this difficulty can be tackled, and research priorities are suggested to come to better models in food science, and thereby to a better control of food quality.     

Reaction kinetics in food extrusion: methods and results

Extrusion cooking is a highly efficient food processing technology. During the extrusion process, there are many desirable and undesirable reactions which will determine final product quality. While being heated and sheared simultaneously, food raw materials experience a non-isothermal process and their residence time in the extruder is distributed. All these factors contribute to the difficulties in determining the kinetic parameters for those reactions. Therefore, this paper attempts to review the reaction kinetics in food extrusion. First of all, the kinetic models for the reactions are outlined. After elucidating how to determine reaction time in an extruder, the methodological approaches for determining the reaction order, rate constant, and activation energy of a reaction under isothermal or non-isothermal conditions with or without residence time distribution (RTD) are presented. Then, different models relating the rate constant to its various impact factors, with especially focusing on shear stress, are reviewed. Subsequently, how shear stress is estimated in an extruder, is illustrated. In the last part of this paper, the reported data of rate constant, reaction order, and activation energy for the reactions occurring during food extrusion are summarized, with detailed impacts of temperature, moisture content, shear stress, and determination method on these kinetic parameters. Finally, future research needs are suggested.     

Effects of organic and conventional growth systems on the content of carotenoids in carrot roots, and on intake and plasma status of carotenoids in humans

BACKGROUND: The demand for organic food products has increased during the last decades due to their probable health effects, among others. A higher content of secondary metabolites such as carotenoids in organic food products has been claimed, though not documented, to contribute to increased health effects of organic foods. The aim was to study the impact of organic and conventional agricultural systems on the content of carotenoids in carrots and human diets. In addition, a human cross‐over study was performed, measuring the plasma status of carotenoids in humans consuming diets made from crops from these agricultural systems. RESULTS: The content of carotenoids in carrot roots and human diets was not significantly affected by the agricultural production system or year, despite differences in fertilisation strategy and levels. The plasma status of carotenoids increased significantly after consumption of the organic and conventional diets, but no systematic differences between the agricultural production systems were observed. CONCLUSION: The expected higher content of presumed health‐promoting carotenoids in organic food products was not documented in this study. Copyright © 2011 Society of Chemical Industry     

Development of Associations and Kinetic Models for Microbiological Data to Be Used in Comprehensive Food Safety Prediction Software

Abstract: The objective of this study was to use an existing database of food products and their associated processes, link it with a list of the foodborne pathogenic microorganisms associated with those products and finally identify growth and inactivation kinetic parameters associated with those pathogens. The database was to be used as a part of the development of comprehensive software which could predict food safety and quality for any food product. The main issues in building such a predictive system included selection of predictive models, associations of different food types with pathogens (as determined from outbreak histories), and variability in data from different experiments. More than 1000 data sets from published literature were analyzed and grouped according to microorganisms and food types. Final grouping of data consisted of the 8 most prevalent pathogens for 14 different food groups, covering all of the foods (>7000) listed in the USDA Natl. Nutrient Database. Data for each group were analyzed in terms of 1st-order inactivation, 1st-order growth, and sigmoidal growth models, and their kinetic response for growth and inactivation as a function of temperature were reported. Means and 95% confidence intervals were calculated for prediction equations. The primary advantage in obtaining group-specific kinetic data is the ability to extend microbiological growth and death simulation to a large array of product and process possibilities, while still being reasonably accurate. Such simulation capability could provide vital ‘‘what if’’ scenarios for industry, Extension, and academia in food safety.     

Mechanistically Inspired Kinetic Approach to Describe Interactions During Co‐Culture Growth of Carnobacterium maltaromaticum and Listeria monocytogenes

Lactic acid bacteria and Listeria monocytogenes are psychotropic organisms that can grow and compete in food such as lightly preserved fishery products. Predictive microbiology is nowadays one of the leading tools to assess the behavior of bacteria in food and to predict food spoilage. Mathematical models can be used to predict the growth, inactivation or growth probability of bacteria. Currently, the efforts in microbial modeling are oriented towards extrapolation of results beyond experiments in order to predict the growth of interacting microorganisms and develop new food preservation processes. In the present work, a model combining both heterogeneous population and quasi‐chemical approaches to describe the different phases of the bacterial growth curve is presented. The model was applied to both monoculture and co‐culture cases of lactic acid bacteria, Carnobacterium maltaromaticum H‐17, and two Listeria monocytogenes strains in a raw fish extract. It is a highlight that our model includes novel inhibition reactions due to the accumulation of metabolites, and a general equation to take into account the effect of chemical compounds during the lag or physiological adaptation phase of the cells. Our results show that the proposed model can accurately describe the experimental data when the curve shape is a sigmoid, and when it presents a maximum. Besides, the parameters have biological interpretability since the model is mechanistically inspired.     

Plenary lecture: innovative modeling approaches applicable to risk assessments

Proper identification of safe and unsafe food at the processing plant is important for maximizing the public health benefit of food by ensuring both its consumption and safety. Risk assessment is a holistic approach to food safety that consists of four steps: 1) hazard identification; 2) exposure assessment; 3) hazard characterization; and 4) risk characterization. Risk assessments are modeled by mapping the risk pathway as a series of unit operations and associated pathogen events and then using probability distributions and a random sampling method to simulate the rare, random, variable and uncertain nature of pathogen events in the risk pathway. To model pathogen events, a rare event modeling approach is used that links a discrete distribution for incidence of the pathogen event with a continuous distribution for extent of the pathogen event. When applied to risk assessment, rare event modeling leads to the conclusion that the most highly contaminated food at the processing plant does not necessarily pose the highest risk to public health because of differences in post-processing risk factors among distribution channels and consumer populations. Predictive microbiology models for individual pathogen events can be integrated with risk assessment models using the rare event modeling method.     

Acrylamide kinetic in plantain during heating process: Precursors and effect of water activity

Almost two thirds of plantain world production is processed by means of deep frying which place it in the same occurrence as potatoes-based food in some tropical regions (Latin America, Central Africa and Southeast Asia). Asparagine content and effect of water activity on acrylamide kinetic in a plantain matrix was surprisingly investigated for the first time. Asparagine content was analyzed in ten edible Musa L., and “Cooking bananas” were found (maximum of 70 mg/100 g db) to be less concentrated than “dessert bananas” (maximum of 321 mg/100 g db). Moreover, asparagine content decreased by 75% after 11 days of post-harvest ripening. Acrylamide formation/elimination kinetics were determined in plantain paste at three different initial water activity values (0.972, 0.904, and 0.430) measured at 25 °C and heated at high temperatures (140-200 °C) in a closed reactor. Acrylamide in plantain was formed at the same magnitude as for potatoes, rye and wheat-based products (max ~ 0.9 ppm, wb). Kinetic parameter estimation was performed using a single response modeling. The reaction kinetic and the estimated kinetic parameters revealed an increase in acrylamide formation and elimination reaction rates with decreasing water activity. The corresponding activation energies of the rate constants remained unaffected.     

Use of Multi-response Modelling to Investigate Mechanisms of β-Carotene Degradation in Dried Orange-Fleshed Sweet Potato During Storage: from Carotenoids to Aroma Compounds

In order to give insight into β-carotene degradation mechanism during the storage of dried orange-fleshed sweet potato, and particularly into the role of isomers and norisoprenoids formation, multi-response kinetic modelling was applied. Determination of degradation compounds were carried out by HPLD-DAD and SPME-GC-MS as a function of time between 10 and 40 °C and at four water activities from 0.13 to 0.76. Kinetic modelling was developed assuming first-order reactions and by using mass balance. Eight compounds, namely, two isomers (9-cis- and 13-cis-β-carotene), two β-carotene epoxides (β-carotene 5,6 and 5,8 epoxide) and four volatile compounds (β-cyclocitral, β-ionone, 5,6-epoxy-β-ionone and dihydroactinidiolide), were integrated into two theoretical reaction schemes. The different models were discriminated according to goodness of fit to experimental data. This work showed that: (1) the formation of cis-isomers from β-carotene preceded oxidation, (2) β-cyclocitral arose directly from β-carotene scission while the other norisoprenoids resulted from β-carotene epoxide degradation, (3) cis-isomers were high reactive compounds. Temperature had a major influence on reaction rates k while water activities only impacted k at values under 0.51. Therefore, multi-response modelling is not only a tool to predict β-carotene degradation but a interesting way to select the appropriate degradation scheme based on the different options presented in literature.