Mathematical modeling of Salmonella typhimurium inactivation under high hydrostatic pressure at different temperatures

Role of Pascalization in Milk Processing and Preservation: A Potential Alternative towards Sustainable Food Processing

Renewed technology has created a demand for foods which are natural in taste, minimally processed, and safe for consumption. Although thermal processing, such as pasteurization and sterilization, effectively limits pathogenic bacteria, it alters the aroma, flavor, and structural properties of milk and milk products. Nonthermal technologies have been used as an alternative to traditional thermal processing technology and have the ability to provide safe and healthy dairy products without affecting their nutritional composition and organoleptic properties. Other than nonthermal technologies, infrared spectroscopy is a nondestructive technique and may also be used for predicting the shelf life and microbial loads in milk. This review explains the role of pascalization or nonthermal techniques such as high-pressure processing (HPP), pulsed electric field (PEF), ultrasound (US), ultraviolet (UV), cold plasma treatment, membrane filtration, micro fluidization, and infrared spectroscopy in milk processing and preservation.

Microbial inactivation by high pressure processing: principle, mechanism and factors responsible

High-pressure processing (HPP) is a novel technology for the production of minimally processed food products with better retention of the natural aroma, fresh-like taste, additive-free, stable, convenient to use. In this regard safety of products by microbial inactivation is likely to become an important focus for food technologists from the research and industrial field. High pressure induces conformational changes in the cell membranes, cell morphology. It perturbs biochemical reactions, as well as the genetic mechanism of the microorganisms, thus ensures the reduction in the microbial count. Keeping in view the commercial demand of HPP products, the scientific literature available on the mechanism of inactivation by high pressure and intrinsic and extrinsic factors affecting the efficiency of HPP are systematically and critically analyzed in this review to develop a clear understanding of these issues. Modeling applied to study the microbial inactivation kinetics by HPP is also discussed for the benefit of interested readers.

High hydrostatic pressure inactivation of microorganisms: A probabilistic model for target log-reductions

A probabilistic model based on logistic regression was developed for a target log reduction of microorganisms inactivated by high hydrostatic pressure. Published inactivation data of Salmonella Typhimurium in broth for 4 and 5 log reductions, and Escherichia coli in buffer and carrot juice for 5 log reduction were used. The probabilities of achieving 4 or 5 log reductions for S. Typhimurium in broth and 5 log reduction for E. coli in buffer and carrot juice could be calculated at different pressure, temperature and time levels. The fitted interfaces of achieving/not achieving the target log reduction were consistent with the experimental data. Although the reliability of the predictions of the developed models could be questioned due to strain variation and different food matrix, a validation study has demonstrated that the developed models could be used to predict the target log reduction of these microorganisms at different pressure, temperature and time levels. This study has indicated that the probabilistic modeling for target log reductions can be useful tool for HHP inactivation of microorganisms, but further studies could be performed with several other factors such as pH and water activity of the food, concentration of certain additives as well as initial number of bacteria present in the food.

Inactivation of Listeria monocytogenes, Staphylococcus aureus, and Salmonella enterica under High Hydrostatic Pressure: A Quantitative Analysis of Existing Literature Data

High hydrostatic pressure processing (HPP) is a mild preservation technique, and its use for processing foods has been widely documented in the literature. However, very few quantitative synthesis studies have been conducted to gather and analyze bacterial inactivation data to identify the mechanisms of HPP-induced bacterial inactivation. The purpose of this study was to conduct a quantitative analysis of three-decimal reduction times (t_3δ) from a large set of existing studies to determine the main influencing factors of HPP-induced inactivation of three foodborne pathogens (Listeria monocytogenes, Staphylococcus aureus, and Salmonella enterica) in various foods. Inactivation kinetics data sets from 1995 to 2017 were selected, and t_3δ values were first estimated by using the nonlinear Weibull model. Bayesian inference was then used within a metaregression analysis to build and test several models and submodels. The best model (lowest error and most parsimonious) was a hierarchical mixed-effects model including pressure intensity, temperature, study, pH, species, and strain as explicative variables and significant factors. Values for t_3δ and Z_P associated with inactivation under HPP were estimated for each bacterial pathogen, with their associated variability. Interstudy variability explained most of the variability in t_3δ values. Strain variability was also important and exceeded interstudy variability for S. aureus, which prevented the development of an overall model for this pathogen. Meta-analysis is not often used in food microbiology but was a valuable quantitative tool for modeling inactivation of L. monocytogenes and Salmonella in response to HPP treatment. Results of this study could be useful for refining quantitative assessment of the effects of HPP on vegetative foodborne pathogens or for more precisely designing costly and labor-intensive experiments with foodborne pathogens.

A 2D analysis of correlations between the parameters of the Gompertz-Makeham model (or law?) of relationships between aging, mortality, and longevity

When mortality (μ), aging rate (γ) and age (t) are treated according to the Gompertz model μ(t) = μ₀e^γt (GM), any mean age corresponds to a manifold of paired reciprocally changing μ₀ and γ. Therefore, any noisiness of data used to derive GM parameters makes them negatively correlated. Besides this artifactual factor of the Strehler-Mildvan correlation (SMC), other factors emerge when the age-independent mortality C modifies survival according to the Gompertz-Makeham model μ(t) = C+μ₀e^γt (GMM), or body resources are partitioned between survival and protection from aging [the compensation effect of mortality (CEM)]. Theoretical curves in (γ, logμ₀) coordinates show how μ₀ decreases when γ increases upon a constant mean age. Within a species-specific range of γ, such "isoage" curves look as nearly parallel straight lines. The slopes of lines constructed by applying GM to survival curves modeled according to GMM upon changes in C are greater than the isoage slopes. When CEM is modeled, the slopes are still greater. Based on these observations, CEM is shown to contribute to SMC associated with sex differences in lifespan, with the effects of several life-extending drugs, and with recent trends in survival/mortality patterns in high-life-expectancy countries; whereas changes in C underlie differences between even high-life-expectancy countries, not only between high- and low-life-expectancy countries. Such interpretations make sense only if GM is not merely a statistical model, but rather reflects biological realities. Therefore, GM is discussed as derivable by applying certain constraints to a natural law termed the generalized Gompertz-Makeham law.

Modeling the pressure inactivation of Escherichia coli and Salmonella typhimurium in sapote mamey ( Pouteria sapota (Jacq.) H.E. Moore & Stearn) pulp

High hydrostatic pressure inactivation kinetics of Escherichia coli ATCC 25922 and Salmonella enterica subsp. enterica serovar Typhimurium ATCC 14028 ( S. typhimurium) in a low acid mamey pulp at four pressure levels (300, 350, 400, and 450 MPa), different exposure times (0-8 min), and temperature of 25 ± 2℃ were obtained. Survival curves showed deviations from linearity in the form of a tail (upward concavity). The primary models tested were the Weibull model, the modified Gompertz equation, and the biphasic model. The Weibull model gave the best goodness of fit ( R²_adj > 0.956, root mean square error < 0.290) in the modeling and the lowest Akaike information criterion value. Exponential-logistic and exponential decay models, and Bigelow-type and an empirical models for b'( P) and n( P) parameters, respectively, were tested as alternative secondary models. The process validation considered the two- and one-step nonlinear regressions for making predictions of the survival fraction; both regression types provided an adequate goodness of fit and the one-step nonlinear regression clearly reduced fitting errors. The best candidate model according to the Akaike theory information, with better accuracy and more reliable predictions was the Weibull model integrated by the exponential-logistic and exponential decay secondary models as a function of time and pressure (two-step procedure) or incorporated as one equation (one-step procedure). Both mathematical expressions were used to determine the t_d parameter, where the desired reductions ( 5D) (considering d = 5 ( t₅) as the criterion of 5 Log₁₀ reduction (5 D)) in both microorganisms are attainable at 400 MPa for 5.487 ± 0.488 or 5.950 ± 0.329 min, respectively, for the one- or two-step nonlinear procedure.

Bioconverted products of essential fatty acids as potential antimicrobial agents

This review deals with the recent findings on the microbial conversion of essential fatty acids (EFAs) through Pseudomonas aeruginosa PR3 NRRL-B-18602, and the antimicrobial properties of bioconverted EFAs, with particular emphasis on n-3 or n-6 fatty acids. The first section deals with the most recent and some background literature on which have been the latest developments with respect to bioconverted EFAs as potential antibacterial agents, in particular the inhibition of severe foodborne and food spoilage bacteria causing deleterious effects in food and human beings. The second section of the review deals with the inhibition of certain important plant pathogenic fungi through the bioconverted EFAs which cause drastic losses to food and agriculture industries. Also we have given emphasis through the literature on the importance of microbial bioconversion of EFAs along with their possible applications in various beneficial fields.