Kinetic models applied to quality change and shelf-life prediction of fresh-cut pineapple in food cold chain

This study developed a predictive model of the remaining shelf-life of fresh-cut pineapple by considering microbial, chemical, and sensory indicators under storage temperatures.The effect of temperature on quality indices (Ea)was29.57-96.8 kJ/mol. The acceptable limits for vitamin C loss and weight loss for fresh-cut pineapple were 27.71 mg/100 g fresh weight and 4.32 %, respectively, in accordance with cutoffs determined on the basis of sensory changes. Key quality indicators that could predict the remaining shelf-life between 5 °C and 25 °C were the TVC and WL. Vitamin C loss was only suitable when storage temperature was above 10 °C. The remaining shelf-life in a real supply chain in terms of the TVC, vitamin C loss, and WL were 9.9, 3.5, and 4 days, respectively. Overall, the shelf-life prediction model developed using selected key indicators may help in managing temperature in the fresh-cut fruit supply chain and improving storage shelf-life.

Assessing Listeria monocytogenes growth kinetics in rice pudding at different storage temperatures

Rice pudding is a popular artisanal dairy dessert highly consumed in the main rice-producing countries, including Egypt. This study aimed to evaluate and model the growth of Listeria monocytogenes in rice pudding dessert stored at different temperatures (4-25 °C) over its shelf-life. Lab-scale rice pudding samples were prepared following a traditional Egyptian recipe and inoculated with a three-strain cocktail of L. monocytogenes (ca. 3 × 102 cfu/g). Inoculated rice pudding samples (pH = 6.67 ± 0.06 and aw = 0.99 ± 0.002) were stored at different isothermal conditions (4, 8, 12, 18, and 25 °C) and microbiologically analysed for up to 30 days for pathogen quantification by plate count methodology. Global regression analysis was used to fit the Baranyi model coupled with the Ratkowsky model to growth data, relating L. monocytogenes concentrations (N, log cfu/g) with storage temperature (°C) and times (d). Model validation was performed using published independent data. L. monocytogenes growth potential increased by increasing storage temperature. The estimated Ratkowsky model parameters were b = 0.0819 ± 0.0017 log cfu/d·°C and Tmin = -3.28 ± 0.20 °C. The indices RMSE = 0.39 and R2adj = 0.97 indicated a good agreement between the experimental data and the model predictions. The estimated maximum growth rate (μmax) values ranged between 0.355 and 5.363 log cfu/d from 4 to 25 °C. The model was successfully validated using published L. monocytogenes Scott A and California strains growth data in rice pudding samples stored at 5, 12 and 22 °C, as evidenced by the assessed statistical indices. The predictive model developed and validated in this study will aid in decision-making regarding the microbiological safety of rice pudding dessert with respect to L. monocytogenes growth, considering a wide range of storage temperatures.

Functional Genomics Identified Novel Genes Involved in Growth at Low Temperatures in Listeria monocytogenes

Listeria monocytogenes (Lm) is a foodborne pathogen that can cause severe human illness. Standard control measures for restricting bacterial growth, such as refrigeration, are often inadequate as Lm grows well at low temperatures. To identify genes involved in growth at low temperatures, a powerful functional genomics method Tn-seq was performed in this study. This genome-wide screening comprehensively identified the known and novel genetic determinants involved in low-temperature growth. A novel gene lmo1366, encoding rRNA methyltransferase, was identified to play an essential role in Lm growth at 16°C. In contrast, the inactivation of lmo2301, a gene encoding the terminase of phage A118, significantly enhanced the growth of Lm at 16°C. The deletion of lmo1366 or lmo2301 resulted in cell morphology alterations and impaired the growth rate in milk and other conditions at low temperatures. Transcriptomic analysis revealed that the Δlmo1366 and Δlmo2301 mutants exhibited altered transcriptional patterns compared to the wild-type strain at 16°C with significant differences in genes involved in ribosome structural stability and function, and membrane biogenesis, respectively. This work uncovered novel genetic determinants involved in Lm growth at 16°C, which could lead to a better understanding of how bacteria survive and multiply at low temperatures. Furthermore, these findings could potentially contribute to developing novel antibacterial strategies under low-temperature conditions.

IMPORTANCEListeria monocytogenes is a Gram-positive pathogen that contributes to foodborne outbreaks due to its ability to survive at low temperatures. However, the genetic determinants of Lm involved in growth at low temperatures have not been fully defined. Here, the genetic determinants involved in the low-temperature growth of Lm were comprehensively identified on a genome-wide scale by Tn-seq. The gene lmo1366, encoding rRNA methyltransferase, was identified essential for growth under low-temperature conditions. On the other hand, the gene lmo2301, encoding terminase of phage A118, plays a negative role in bacterial growth at low temperatures. The transcriptomic analysis revealed the potential mechanisms. These findings lead to a better understanding of how bacteria survive and multiply at low temperatures and could provide unique targets for novel antibacterial strategies under low-temperature conditions.

Listeria monocytogenes - How This Pathogen Survives in Food-Production Environments?

The foodborne pathogen Listeria monocytogenes is the causative agent of human listeriosis, a severe disease, especially dangerous for the elderly, pregnant women, and newborns. Although this infection is comparatively rare, it is often associated with a significant mortality rate of 20-30% worldwide. Therefore, this microorganism has an important impact on food safety. L. monocytogenes can adapt, survive and even grow over a wide range of food production environmental stress conditions such as temperatures, low and high pH, high salt concentration, ultraviolet lights, presence of biocides and heavy metals. Furthermore, this bacterium is also able to form biofilm structures on a variety of surfaces in food production environments which makes it difficult to remove and allows it to persist for a long time. This increases the risk of contamination of food production facilities and finally foods. The present review focuses on the key issues related to the molecular mechanisms of the pathogen survival and adaptation to adverse environmental conditions. Knowledge and understanding of the L. monocytogenes adaptation approaches to environmental stress factors will have a significant influence on the development of new, efficient, and cost-effective methods of the pathogen control in the food industry, which is critical to ensure food production safety.

Short communication: Long-term -20°C survival of Listeria monocytogenes in artificially and process-contaminated ice cream involved in an outbreak of listeriosis

Listeria monocytogenes was linked to an outbreak of foodborne illness associated with in-process contaminated ice cream in the United States from 2010 to 2015 that sickened 10 individuals and led to 3 deaths. Ice cream obtained from the outbreak was used in this study to examine the population dynamics of L. monocytogenes as in-process contaminants compared with artificially inoculated cells. Because challenge studies of food products generally use artificial contamination, it is necessary to understand the differences in survival, if any, between these 2 types of contaminants. We hypothesized that laboratory-grown cultures of the pathogen that were not exposed to the environmental stresses of the manufacturing facility would show different population dynamics in an ice cream challenge study compared with in-process contaminants. In this study, half of the outbreak-associated ice cream samples were artificially inoculated with a 10 cfu/g cocktail of L. monocytogenes; the other half contained only the in-process contaminants. All samples were stored at -20°C and tested for pathogen levels (n = 10 for each contaminant type at each time point) by the most probable number method at 3-mo intervals for 36 mo. Generally, population levels between the 2 contamination states in the ice cream were not significantly different and L. monocytogenes survived for at least 36 mo, regardless of contamination state. Overall, our results suggest that the use of L. monocytogenes as an artificial contaminant in challenge studies and risk assessment of ice cream during frozen storage give results similar to those shown by in-process contaminants.

Listeria monocytogenes in Milk: Occurrence and Recent Advances in Methods for Inactivation

Milk is one of the most important food items consumed by humans worldwide. In addition to its nutritional importance, milk is an excellent culture medium for microorganisms, which may include pathogens such as Listeria monocytogenes (L. monocytogenes). Traditional processing of milk for direct consumption is based on thermal treatments that efficiently eliminate pathogens, including pasteurization or sterilization. However, the occurrence of L. monocytogenes in milk as a consequence of failures in the pasteurization process or postpasteurization contamination is still a matter of concern. In recent years, consumer demand for minimally processed milk has increased due to the perception of better sensory and nutritional qualities of the products. This review deals with the occurrence of L. monocytogenes in milk in the last 10 years, including regulatory aspects, and recent advances in technologies for the inactivation of this pathogen in milk. The results from studies on nonthermal technologies, such as high hydrostatic pressure, pulsed electric fields, ultrasounds, and ultraviolet irradiation, are discussed, considering their potential application in milk processing plants.

Current Trends in Foodborne Human Listeriosis

Human listeriosis results from the ingestion of foods contaminated with Listeria monocytogenes (Lm). About 1600 listeriosis cases are reported every year in the USA with >95% hospitalization and 15-20% death. The proportions of persons with listeriosis hospitalized and who die are very similar in Europe with slightly higher rates in Scandinavian countries. The occurrence of disease requires adaptation, survival, and usually growth of Lm in foods before consumption by members of the susceptible population. Despite concerted efforts by the food safety community, the disease incidence has not changed significantly since 2001 and remains higher than the Healthy People 2020 target of 0.2 cases per 100,000 individuals. In recent years, human listeriosis cases have been reported to involve non-typical foods, e.g. celery, cantaloupe, caramel apple, frozen vegetables and ice cream. In some outbreaks, a few infected individuals were considered outside the realm of the standard vulnerable population group. Our recent work with the outbreak associated with ice cream samples, indicated that a low-level contamination in a food that does not support growth can cause listeriosis in highly susceptible populations. Separately, using a combination of polymerase chain reaction (PCR)-based serotyping and whole genome sequencing (WGS)-based analyses; we have discovered that a genetic variant of the serotype 4b strain, called 4bV, was responsible for 3-4 recent outbreaks in the USA. Three of the four products associated with these outbreaks were grown in a small geographical region of the USA while the fourth was never linked to a specific grower, but rather a processing facility. These 4bV strains contain a 6.3kb DNA fragment normally associated with lineage II Lm strains. The significance of this DNA fragment in the serotype 4b background is currently being investigated. This article reviews current listeriosis outbreaks with an emphasis on the expansions in food niche, case demography and genotypes of Lm. The discussion raises important questions about Lm adaptation in different foods and environments and the role of certain genotypes in such adaptation and disease outcome.

Development and validation of predictive models for the effect of storage temperature and pH on the growth boundaries and kinetics of Alicyclobacillus acidoterrestris ATCC 49025 in fruit drinks

This study was undertaken to provide quantitative tools for predicting the behavior of the spoilage bacterium Alicyclobacillus acidoterrestris ATCC 49025 in fruit drinks. In the first part of the study, a growth/no growth interface model was developed, predicting the probability of growth as a function of temperature and pH. For this purpose, the growth ability of A. acidoterrestris was studied at different combinations of temperature (15-45 °C) and pH (2.02-5.05). The minimum pH and temperature where growth was observed was 2.52 (at 35 and 45 °C) and 25 °C (at pH ≥ 3.32), respectively. Then a logistic polynomial regression model was fitted to the binary data (0: no growth, 1: growth) and, based on the concordance index (98.8%) and the Hosmer-Lemeshow statistic (6.226, P = 0.622), a satisfactory goodness of fit was demonstrated. In the second part of the study, the effects of temperature (25-55 °C) and pH (3.03-5.53) on A. acidoterrestris growth rate were investigated and quantitatively described using the cardinal temperature model with inflection and the cardinal pH model, respectively. The estimated values for the cardinal parameters T_min, T_max, T_opt and pH_min, pH_max, pH_opt were 18.11, 55.68, 48.60 °C and 2.93, 5.90, 4.22, respectively. The developed models were validated against growth data of A. acidoterrestris obtained in eight commercial pasteurized fruit drinks. The validation results showed a good performance of both models. In all cases where the growth/no growth interface model predicted a probability lower than 0.5, A. acidoterrestris was, indeed, not able to grow in the tested fruit drinks; similarly, when the model predicted a probability above 0.9, growth was observed in all cases. A good agreement was also observed between growth predicted by the kinetic model and the observed kinetics of A. acidoterrestris in fruit drinks at both static and dynamic temperature conditions.

Listeria monocytogenes Growth Kinetics in Milkshakes Made from Naturally and Artificially Contaminated Ice Cream

This study assessed the growth of Listeria monocytogenes in milkshakes made using the process-contaminated ice cream associated with a listeriosis outbreak in comparison to milkshakes made with artificially contaminated ice cream. For all temperatures, growth kinetics including growth rates, lag phases, maximum populations, and population increases were determined for the naturally and artificially derived contaminants at 5, 10, 15, and 25°C storage for 144 h. The artificially inoculated L. monocytogenes presented lower growth rates and shorter lag phases than the naturally contaminated populations at all temperatures except for 5°C, where the reverse was observed. At 25°C, lag phases of the naturally and artificially contaminated L. monocytogenes were 11.6 and 7.8 h, respectively. The highest increase in population was observed for the artificially inoculated pathogen at 15°C after 96 h (6.16 log CFU/mL) of storage. Growth models for both contamination states in milkshakes were determined. In addition, this study evaluated the antimicrobial effectiveness of flavoring agents, including strawberry, chocolate and mint, on the growth of the pathogen in milkshakes during 10°C storage. All flavor additions resulted in decreased growth rates of L. monocytogenes for both contamination states. The addition of chocolate and mint flavoring also resulted in significantly longer lag phases for both contamination states. This study provides insight into the differences in growth between naturally and artificially contaminated L. monocytogenes in a food product.

Hygienic Shortcomings of Frozen Dessert Freezing Equipment and Fate of Listeria monocytogenes on Ice Cream-Soiled Stainless Steel

Although frozen dairy desserts have a strong record of safety, recent outbreaks of foodborne disease linked to ice creams have brought new attention to this industry. There is concern that small-scale frozen dessert equipment may not comply with or be reviewed against published comprehensive design and construction sanitation specifications (National Sanitation Foundation or 3-A sanitary standards). Equipment sanitary design issues may result in reduced efficacy of cleaning and sanitation, thus increasing the likelihood of postprocess contamination with pathogenic bacteria. In this context, and given that Listeria monocytogenes outbreaks are of great concern for the frozen dessert industry, a complementary study was conducted to evaluate the fate of L. monocytogenes in ice cream mix on a stainless steel surface. Our results showed that L. monocytogenes survived for up to 6 weeks at room temperature and 9 weeks at 4°C in contaminated ice cream on a stainless steel surface. Furthermore, chlorine- and acid-based surface sanitizers had no detrimental effect on the L. monocytogenes when used at a concentration and contact time (1 min) recommended by the manufacturer; significant reduction in CFU required 5 to 20 min of contact time.

How to Decide on Modeling Details: Risk and Benefit Assessment

Mathematical models based on thermodynamic, kinetic, heat, and mass transfer analysis are central to this chapter. Microbial growth, death, enzyme inactivation models, and the modeling of material properties, including those pertinent to conduction and convection heating, mass transfer, such as diffusion and convective mass transfer, and thermodynamic properties, such as specific heat, enthalpy, and Gibbs free energy of formation and specific chemical exergy are also needed in this task. The origins, simplifying assumptions, and uses of model equations are discussed in this chapter, together with their benefits. The simplified forms of these models are sometimes referred to as "laws," such as "the first law of thermodynamics" or "Fick's second law." Starting to modeling a study with such "laws" without considering the conditions under which they are valid runs the risk of ending up with erronous conclusions. On the other hand, models started with fundamental concepts and simplified with appropriate considerations may offer explanations for the phenomena which may not be obtained just with measurements or unprocessed experimental data. The discussion presented here is strengthened with case studies and references to the literature.

Survival of a native toxigenic isolate of Listeria monocytogenes CFR 1302 during storage of milk-based foods can be a potential cause of health risk

The ability of a native toxigenic culture of Listeria monocytogenes CFR 1302 to survive and elaborate associated toxigenic trait in ice cream and mango pulp-based lactic fermented milk was studied. The culture of L. monocytogenes inoculated at two initial levels of 4.6 and 5.6 log₁₀ CFU/ml almost remained unaltered during storage of the food products. However, in both the milk-based products, a marginal increase in viable population was observed during 2-4 d of storage as against the initial inoculum levels. The toxigenic trait, listeriolysin "O" was detected by PCR based on species-specific hlyA primers in the two products without any step of enrichment. The positive amplification in PCR was evidenced with initial population levels of 6.3, 7.3, and 8.3 log₁₀ CFU/ml of the respective products. In culture broth, PCR detection was positive with the lowest level of 2.3 log₁₀ CFU/ml. The established pathogenic strain of L. monocytogenes Scott A used as a reference culture revealed almost the same behavior to that of native culture in the food products. The findings of present study bring into focus that, irrespective of low storage temperatures, there exists the potential health hazard associated with foods initially contaminated with risk population levels of L. monocytogenes.

Shelf-life prediction models for ready-to-eat fresh cut salads: Testing in real cold chain

The aim of the study was to develop and test the applicability of predictive models for shelf-life estimation of ready-to-eat (RTE) fresh cut salads in realistic distribution temperature conditions in the food supply chain. A systematic kinetic study of quality loss of RTE mixed salad (lollo rosso lettuce-40%, lollo verde lettuce-45%, rocket-15%) packed under modified atmospheres (3% O2, 10% CO2, 87% N2) was conducted. Microbial population (total viable count, Pseudomonas spp., lactic acid bacteria), vitamin C, colour and texture were the measured quality parameters. Kinetic models for these indices were developed to determine the quality loss and calculate product remaining shelf-life (SLR). Storage experiments were conducted at isothermal (2.5-15°C) and non-isothermal temperature conditions (Teff=7.8°C defined as the constant temperature that results in the same quality value as the variable temperature distribution) for validation purposes. Pseudomonas dominated spoilage, followed by browning and chemical changes. The end of shelf-life correlated with a Pseudomonas spp. level of 8 log(cfu/g), and 20% loss of the initial vitamin C content. The effect of temperature on these quality parameters was expressed by the Arrhenius equation; activation energy (Ea) value was 69.1 and 122.6kJ/mol for Pseudomonas spp. growth and vitamin C loss rates, respectively. Shelf-life prediction models were also validated in real cold chain conditions (including the stages of transport to and storage at retail distribution center, transport to and display at 7 retail stores, transport to and storage in domestic refrigerators). The quality level and SLR estimated after 2-3days of domestic storage (time of consumption) ranged between 1 and 8days at 4°C and was predicted within satisfactory statistical error by the kinetic models. Teff in the cold chain ranged between 3.7 and 8.3°C. Using the validated models, SLR of RTE fresh cut salad can be estimated at any point of the cold chain if the temperature history is known. Shelf-life models of validated applicability can serve as an effective tool for shelf-life assessment and the development of new products in the fresh produce food sector.

Prevalence and Level of Listeria monocytogenes in Ice Cream Linked to a Listeriosis Outbreak in the United States

A most-probable-number (MPN) method was used to enumerate Listeria monocytogenes in 2,320 commercial ice cream scoops manufactured on a production line that was implicated in a 2015 listeriosis outbreak in the United States. The analyzed samples were collected from seven lots produced in November 2014, December 2014, January 2015, and March 2015. L. monocytogenes was detected in 99% (2,307 of 2,320) of the tested samples (lower limit of detection, 0.03 MPN/g), 92% of which were contaminated at <20 MPN/g. The levels of L. monocytogenes in these samples had a geometric mean per lot of 0.15 to 7.1 MPN/g. The prevalence and enumeration data from an unprecedented large number of naturally contaminated ice cream products linked to a listeriosis outbreak provided a unique data set for further understanding the risk associated with L. monocytogenes contamination for highly susceptible populations.

Recovery and Growth Potential of Listeria monocytogenes in Temperature Abused Milkshakes Prepared from Naturally Contaminated Ice Cream Linked to a Listeriosis Outbreak

The recovery and growth potential of Listeria monocytogenes was evaluated in three flavors of milkshakes (vanilla, strawberry, and chocolate) that were prepared from naturally contaminated ice cream linked to a listeriosis outbreak in the U.S. in 2015, and were subsequently held at room temperature for 14 h. The average lag phase duration of L. monocytogenes was 9.05 h; the average generation time was 1.67 h; and the average population level increase per sample at 14 h was 1.14 log CFU/g. Milkshake flavors did not significantly affect these parameters. The average lag phase duration of L. monocytogenes in milkshakes with initial contamination levels ≤ 3 CFU/g (9.50 h) was significantly longer (P < 0.01) than that with initial contamination levels > 3 CFU/g (8.60 h). The results highlight the value of using samples that are contaminated with very low levels of L. monocytogenes for recovery and growth evaluations. The behavior of L. monocytogenes populations in milkshakes prepared from naturally contaminated ice cream linked to the listeriosis outbreak should be taken into account when performing risk based analysis using this outbreak as a case study.

Development of a predictive model for the growth kinetics of aerobic microbial population on pomegranate marinated chicken breast fillets under isothermal and dynamic temperature conditions

The aim of this study was the development of a model to describe the growth kinetics of aerobic microbial population of chicken breast fillets marinated in pomegranate juice under isothermal and dynamic temperature conditions. Moreover, the effect of pomegranate juice on the extension of the shelf life of the product was investigated. Samples (10 g) of chicken breast fillets were immersed in marinades containing pomegranate juice for 3 h at 4 °C following storage under aerobic conditions at 4, 10, and 15 °C for 10 days. Total Viable Counts (TVC), Pseudomonas spp and lactic acid bacteria (LAB) were enumerated, in parallel with sensory assessment (odor and overall appearance) of marinated and non-marinated samples. The Baranyi model was fitted to the growth data of TVC to calculate the maximum specific growth rate (μmax) that was further modeled as a function of temperature using a square root-type model. The validation of the model was conducted under dynamic temperature conditions based on two fluctuating temperature scenarios with periodic changes from 6 to 13 °C. The shelf life was determined both mathematically and with sensory assessment and its temperature dependence was modeled by an Arrhenius type equation. Results showed that the μmax of TVC of marinated samples was significantly lower compared to control samples regardless temperature, while under dynamic temperature conditions the model satisfactorily predicted the growth of TVC in both control and marinated samples. The shelf-life of marinated samples was significantly extended compared to the control (5 days extension at 4 °C). The calculated activation energies (Ea), 82 and 52 kJ/mol for control and marinated samples, respectively, indicated higher temperature dependence of the shelf life of control samples compared to marinated ones. The present results indicated that pomegranate juice could be used as an alternative ingredient in marinades to prolong the shelf life of chicken.

Modelling the effect of lactic acid bacteria from starter- and aroma culture on growth of Listeria monocytogenes in cottage cheese

Four mathematical models were developed and validated for simultaneous growth of mesophilic lactic acid bacteria from added cultures and Listeria monocytogenes, during chilled storage of cottage cheese with fresh- or cultured cream dressing. The mathematical models include the effect of temperature, pH, NaCl, lactic- and sorbic acid and the interaction between these environmental factors. Growth models were developed by combining new and existing cardinal parameter values. Subsequently, the reference growth rate parameters (μref at 25°C) were fitted to a total of 52 growth rates from cottage cheese to improve model performance. The inhibiting effect of mesophilic lactic acid bacteria from added cultures on growth of L. monocytogenes was efficiently modelled using the Jameson approach. The new models appropriately predicted the maximum population density of L. monocytogenes in cottage cheese. The developed models were successfully validated by using 25 growth rates for L. monocytogenes, 17 growth rates for lactic acid bacteria and a total of 26 growth curves for simultaneous growth of L. monocytogenes and lactic acid bacteria in cottage cheese. These data were used in combination with bias- and accuracy factors and with the concept of acceptable simulation zone. Evaluation of predicted growth rates of L. monocytogenes in cottage cheese with fresh- or cultured cream dressing resulted in bias-factors (Bf) of 1.07-1.10 with corresponding accuracy factor (Af) values of 1.11 to 1.22. Lactic acid bacteria from added starter culture were on average predicted to grow 16% faster than observed (Bf of 1.16 and Af of 1.32) and growth of the diacetyl producing aroma culture was on average predicted 9% slower than observed (Bf of 0.91 and Af of 1.17). The acceptable simulation zone method showed the new models to successfully predict maximum population density of L. monocytogenes when growing together with lactic acid bacteria in cottage cheese. 11 of 13 simulations of L. monocytogenes growth were within the acceptable simulation zone, which demonstrated good performance of the empirical inter-bacterial interaction model. The new set of models can be used to predict simultaneous growth of mesophilic lactic acid bacteria and L. monocytogenes in cottage cheese during chilled storage at constant and dynamic temperatures. The applied methodology is likely to be applicable for safety prediction of other types of fermented and unripened dairy products where inhibition by lactic acid bacteria is important for growth of pathogenic microorganisms.

Utilization of mathematical models to manage risk of holding cold food without temperature control

This document describes the development of a tool to manage the risk of the transportation of cold food without temperature control. The tool uses predictions from ComBase predictor and builds on the 2009 U.S. Food and Drug Administration Model Food Code and supporting scientific data in the Food Code annex. I selected Salmonella spp. and Listeria monocytogenes as the organisms for risk management. Salmonella spp. were selected because they are associated with a wide variety of foods and grow rapidly at temperatures >17°C. L. monocytogenes was selected because it is frequently present in the food processing environment, it was used in the original analysis contained in the Food Code Annex, and it grows relatively rapidly at temperatures <17°C. The suitability of a variety of growth models under changing temperature conditions is largely supported by the published literature. The ComBase predictions under static temperature conditions were validated using 148 ComBase database observations for Salmonella spp. and L. monocytogenes in real foods. The times and temperature changes encompassed by ComBase Predictor models for Salmonella spp. and L. monocytogenes are consistent with published data on consumer food transport to the home from the grocery store and on representative foods from a wholesale cash and carry food service supplier collected as part of this project. The resulting model-based tool will be a useful aid to risk managers and customers of wholesale cash and carry food service suppliers, as well as to anyone interested in assessing and managing the risks posed by holding cold foods out of temperature control in supermarkets, delis, restaurants, cafeterias, and homes.

Shelf-life extension of gilthead seabream fillets by osmotic treatment and antimicrobial agents

AIMS

The objectives of the study were to evaluate the effect of selected antimicrobial agents on the shelf life of osmotically pretreated gilthead seabream and to establish reliable kinetic equations for shelf-life determination validated in dynamic conditions.

METHODS AND RESULTS

Fresh gilthead seabream (Sparus aurata) fillets were osmotically treated with 50% high dextrose equivalent maltodextrin (HDM, DE 47) plus 5% NaCl and 0·5% carvacrol, 0·5% glucono-δ-lactone or 1% Citrox (commercial antimicrobial mix). Untreated and treated slices were aerobically packed and stored isothermally (0-15°C). Microbial growth and quality-related chemical indices were modelled as functions of temperature. Models were validated at dynamic storage conditions. Osmotic pretreatment with the use of antimicrobials led to significant shelf-life extension of fillets, in terms of microbial growth and organoleptic deterioration.

CONCLUSIONS

The shelf life was 7 days for control samples at 5°C. The osmotic pretreatment with carvacrol, glucono-δ-lactone and Citrox allowed for shelf-life extension by 8, 10 and 5 days at 5°C, respectively.

SIGNIFICANCE AND IMPACT OF THE STUDY

The results of the study show the potential of adding carvacrol, glucono-δ-lactone or Citrox in the osmotic solution to extend the shelf life and improve commercial value of chilled osmotically pretreated fish products. The developed models can be a reliable tool for predicting the shelf life of fresh or minimally processed gilthead seabream fillets in the real chill chain.

Modelling of growth, growth/no-growth interface and nonthermal inactivation areas of Listeria in foods

Growth, growth boundary and inactivation models have been extensively developed in predictive microbiology and are commonly applied in food research nowadays. Few studies though report the development of models which encompass all three areas together. A tiered modelling approach, based on the Gamma hypothesis, is proposed here to predict the behaviour of Listeria. Datasets of Listeria spp. behaviour in laboratory media, meat, dairy, seafood products and vegetables were collected from literature, unpublished sources and from the databases ComBase and Sym'Previus. The explanatory factors were temperature, pH, water activity, lactic and sorbic acids. For the growth part, 697 growth kinetic datasets were fitted. The estimated growth rates and 2021 additional growth primary datasets were used to fit the secondary growth models. In a second step, the fitted model was used to predict the growth/no-growth boundary. For the inactivation modelling phase, 535 inactivation curves were used. Gamma models with and without interactions between the explanatory factors were used for the growth and boundary models. The correct prediction percentage (predicted growth when growth is observed+predicted inactivation when inactivation is observed) varied from 62% to 81% for the models without interactions, and from 85% to 87% for the models with interactions. The median error for the predicted population size was less than 0.34 log(10)(CFU/mL) for all models. The kinetics of inactivation were fitted with modified Weibull primary models and the estimated bacterial resistance was then modelled as a function of the explanatory factors. The error for the predicted microbial population size was less than 0.71 log(10)(CFU/mL) with a median value of less than 0.21 for all foods. The model enables the quantification of the increase or decrease in the bacterial population for a given formulation or storage condition. It might also be used to optimise a food formulation or storage condition in the case of a targeted increase or decrease of the bacterial population.

Modeling germination of fungal spores at constant and fluctuating temperature conditions

The germination of Penicillium expansum and Aspergillus niger spores was monitored microscopically on malt extract agar at isothermal conditions ranging from 0 to 33°C and 5 to 41.5°C, respectively. The obtained germination data, expressed as percentage of germination (% P) versus time, were fitted to the modified Gompertz equation for the estimation of the germination kinetic parameters (lag time, λ(g), and germination rate, μ(g)), which were further modeled as a function of temperature via the use of Cardinal Models with Inflection (CMI). The effect of temperature on these parameters was similar with that previously reported for mycelium growth kinetics of the tested isolates. The germination of spores was also studied at various dynamic time-temperature conditions including single or sequential temperature shifts. The germination of spores at fluctuating temperatures was predicted using the modified Gompertz equation in conjunction with the CMI models for λ(g) and μ(g) and based on the assumptions that i) a temperature shift does not result in any additional λ(g) and, thus, the total lag can be calculated by adding relative parts of the lag time, and ii) after a temperature shift the germination rate μ(g) adapts instantaneously to the new temperature. The comparison between predicted and observed data showed that the germination of spores is strongly affected by the extent of the temperature shift, the percentage of germinated spores at the time of the shift and the fungal species. Apart from the scientific interest in understanding the dynamics of spores' germination, the models developed in this study can be used as tools in effective quality management systems for fungi control in foods.

Modeling microbial spoilage and quality of gilthead seabream fillets: combined effect of osmotic pretreatment, modified atmosphere packaging, and nisin on shelf life

The objective of the study was the kinetic modeling of the effect of storage temperature on the quality and shelf life of chilled fish, modified atmosphere-packed (MAP), and osmotically pretreated with the addition of nisin as antimicrobial agent. Fresh gilthead seabream (Sparus aurata) fillets were osmotically treated with 50% high dextrose equivalent maltodextrin (DE 47) plus 5% NaCl. Water loss, solid gain, salt content, and water activity were monitored throughout treatment and treatment conditions were selected for the shelf life study. Untreated and osmotically pretreated slices with and without nisin (2 x 10(4) IU/100 g osmotic solution), packed in air or modified atmosphere (50% CO(2)-50% air), and stored at controlled isothermal conditions (0, 5, 10, and 15 degrees C) were studied. Quality assessment and modeling were based on growth of several microbial indices, total volatile nitrogen, trimethylamine nitrogen, lipid oxidation (TBARS), and sensory scoring. Temperature dependence of quality loss rates was modeled by the Arrhenius equation, validated under dynamic conditions. Pretreated samples showed improved quality stability during subsequent refrigerated storage, in terms of microbial growth, chemical changes, and organoleptic degradation. Osmotic pretreatment with the addition of nisin in combination with MAP was the most effective treatment resulting in significant shelf life extension of gilthead seabream fillets (48 days compared to 10 days for the control at 0 degrees C).

Dynamic modeling of Listeria monocytogenes growth in pasteurized vanilla cream after postprocessing contamination

A product-specific model was developed and validated under dynamic temperature conditions for predicting the growth of Listeria monocytogenes in pasteurized vanilla cream, a traditional milk-based product. Model performance was also compared with Growth Predictor and Sym'Previus predictive microbiology software packages. Commercially prepared vanilla cream samples were artificially inoculated with a five-strain cocktail of L. monocytogenes, with an initial concentration of 102 CFU g(-1), and stored at 3, 5, 10, and 15 degrees C for 36 days. The growth kinetic parameters at each temperature were determined by the primary model of Baranyi and Roberts. The maximum specific growth rate (mu(max)) was further modeled as a function of temperature by means of a square root-type model. The performance of the model in predicting the growth of the pathogen under dynamic temperature conditions was based on two different temperature scenarios with periodic changes from 4 to 15 degrees C. Growth prediction for dynamic temperature profiles was based on the square root model and the differential equations of the Baranyi and Roberts model, which were numerically integrated with respect to time. Model performance was based on the bias factor (B(f)), the accuracy factor (A(f)), the goodness-of-fit index (GoF), and the percent relative errors between observed and predicted growth. The product-specific model developed in the present study accurately predicted the growth of L. monocytogenes under dynamic temperature conditions. The average values for the performance indices were 1.038, 1.068, and 0.397 for B(f), A(f), and GoF, respectively for both temperature scenarios assayed. Predictions from Growth Predictor and Sym'Previus overestimated pathogen growth. The average values of B(f), A(f), and GoF were 1.173, 1.174, 1.162, and 0.956, 1.115, 0.713 for [corrected] Growth Predictor and Sym'Previus, respectively.