Modeling the Microbiological Shelf Life of Foods and Beverages

From about 1985 to 2015, the subject of predictive microbiology has become a mature area of study in and of itself. The ability to predict the growth of a bacterial species within a food matrix for a given set of intrinsic and environmental conditions offers many advantages and benefits to the food industry professional, and chief among these is the ability to determine shelf life using mathematical models.

[1]  Li Zhang,et al.  Growth behavior prediction of fresh catfish fillet with Pseudomonas aeruginosa under stresses of allyl isothiocyanate, temperature and modified atmosphere , 2015 .

[2]  H. Ingmer,et al.  Modeling the Growth of Listeria monocytogenes in Soft Blue-White Cheese , 2012, Applied and Environmental Microbiology.

[3]  P Dalgaard,et al.  Modelling of microbial activity and prediction of shelf life for packed fresh fish. , 1995, International journal of food microbiology.

[4]  B. Tiwari,et al.  Quantitative assessment of the shelf life of ozonated apple juice , 2011 .

[5]  D. Thuault,et al.  Development and application of a predictive model of Aspergillus candidus growth as a tool to improve shelf life of bakery products. , 2013, Food microbiology.

[6]  S. Koseki,et al.  Predictive modelling of the recovery of Listeria monocytogenes on sliced cooked ham after high pressure processing. , 2007, International journal of food microbiology.

[7]  J Baranyi,et al.  Validating and comparing predictive models. , 1999, International journal of food microbiology.

[8]  Denyse I. LeBlanc,et al.  Comparative simulation of Escherichia coli O157:H7 behaviour in packaged fresh-cut lettuce distributed in a typical Canadian supply chain in the summer and winter , 2014 .

[9]  Xinglian Xu,et al.  Development and validation of a molecular predictive model to describe the growth of Listeria monocytogenes in vacuum-packaged chilled pork , 2013 .

[10]  S. André,et al.  Quantitative assessment of the risk of microbial spoilage in foods. Prediction of non-stability at 55 °C caused by Geobacillus stearothermophilus in canned green beans. , 2014, International journal of food microbiology.

[11]  T. A. Roberts,et al.  The effect of sodium chloride and temperature on the rate and extent of growth of Clostridium botulinum type A in pasteurized pork slurry. , 1987, The Journal of applied bacteriology.

[12]  B. Onno,et al.  Modeling growth of three bakery product spoilage molds as a function of water activity, temperature and pH. , 2014, International journal of food microbiology.

[13]  Tom Ross,et al.  Predictive Microbiology : Theory and Application , 1993 .

[14]  Thomas E Oscar,et al.  Validation of Lag Time and Growth Rate Models for Salmonella Typhimurium: Acceptable Prediction Zone Method , 2005 .

[15]  J. Sofos,et al.  Modeling the effect of storage atmosphere on growth-no growth interface of Listeria monocytogenes as a function of temperature, sodium lactate, sodium diacetate, and NaCl. , 2007, Journal of food protection.

[16]  P. Bonilauri,et al.  Quantitative risk assessment of verocytotoxin-producing Escherichia coli O157 and Campylobacter jejuni related to consumption of raw milk in a province in Northern Italy. , 2012, Journal of food protection.

[17]  L. Gálvez,et al.  Principal Component Analysis as an exploration tool for kinetic modeling of food quality: A case study of a dried apple cluster snack , 2013 .

[18]  Paw Dalgaard,et al.  Modelling the effect of lactic acid bacteria from starter- and aroma culture on growth of Listeria monocytogenes in cottage cheese. , 2014, International journal of food microbiology.

[19]  Li Bo,et al.  Modeling the effect of temperature on the growth rate and lag phase of Penicillium expansum in apples. , 2007, International journal of food microbiology.

[20]  L. Finn,et al.  Evaluation of Factors Involved in Antibotulinal Properties of Pasteurized Process Cheese Spreads. , 1986, Journal of food protection.

[21]  J. Gurtler,et al.  Growth kinetics and model comparison of Cronobacter sakazakii in reconstituted powdered infant formula. , 2012, Journal of food science.

[22]  J. Membré,et al.  Predicting and preventing mold spoilage of food products. , 2013, Journal of food protection.

[23]  W. Yoon,et al.  Predictive modeling for growth of non- and cold-adapted Listeria monocytogenes on fresh-cut cantaloupe at different storage temperatures. , 2014, Journal of food science.

[24]  T. Oscar.  Predictive models for growth of Salmonella typhimurium DT104 from low and high initial density on ground chicken with a natural microflora. , 2007, Food microbiology.

[25]  F. Patrignani,et al.  Antimicrobial Activity of Aroma Compounds against Saccharomyces cerevisiae and Improvement of Microbiological Stability of Soft Drinks as Assessed by Logistic Regression , 2007, Applied and Environmental Microbiology.

[26]  J Olley,et al.  Relationship between temperature and growth rate of bacterial cultures , 1982, Journal of bacteriology.

[27]  G. D. García de Fernando,et al.  Modeling the Listeria innocua micropopulation lag phase and its variability. , 2013, International journal of food microbiology.

[28]  G. Box.  Robustness in the Strategy of Scientific Model Building. , 1979 .

[29]  Antonio Valero,et al.  Predictive Microbiology in Foods , 2012 .

[31]  A. N. Stokes,et al.  Model for bacterial culture growth rate throughout the entire biokinetic temperature range , 1983, Journal of bacteriology.

[32]  J Baranyi,et al.  A dynamic approach to predicting bacterial growth in food. , 1994, International journal of food microbiology.

[33]  J. Augustin,et al.  Combining Individual-Based Modeling and Food Microenvironment Descriptions To Predict the Growth of Listeria monocytogenes on Smear Soft Cheese , 2013, Applied and Environmental Microbiology.

[34]  Modeling of Fungal and Bacterial Spore Germination under Static and Dynamic Conditions , 2013, Applied and Environmental Microbiology.

[35]  A. Geeraerd,et al.  A Predictive Model for the Growth/No Growth Boundary of Zygosaccharomyces bailii at 7 °C and Conditions Mimicking Acidified Sauces , 2012, Food and Bioprocess Technology.

[36]  S. Tromp,et al.  Modeling the impact of the indigenous microbial population on the maximum population density of Salmonella on alfalfa , 2013, World Journal of Microbiology and Biotechnology.

[37]  M. Danyluk,et al.  Modeling the growth of Listeria monocytogenes on cut cantaloupe, honeydew and watermelon. , 2014, Food microbiology.

[38]  D. Oh,et al.  Growth model of Escherichia coli O157:H7 at various storage temperatures on kale treated by thermosonication combined with slightly acidic electrolyzed water. , 2014, Journal of food protection.

[39]  Kenneth Davey,et al.  Validation of a model for predicting the combined effect of three environmental factors on both exponential and lag phases of bacterial growth: temperature, salt concentration and pH , 1995 .

[40]  T. Ross.  Indices for performance evaluation of predictive models in food microbiology. , 1996, The Journal of applied bacteriology.

[41]  Stavros G. Manios,et al.  A generic model for spoilage of acidic emulsified foods: combining physicochemical data, diversity and levels of specific spoilage organisms. , 2014, International journal of food microbiology.

[42]  Paw Dalgaard,et al.  Modelling and predicting the simultaneous growth of Listeria monocytogenes and psychrotolerant lactic acid bacteria in processed seafood and mayonnaise-based seafood salads. , 2015, Food microbiology.

[43]  E. Topp,et al.  Evaluation of different approaches for modeling Escherichia coli O157:H7 survival on field lettuce. , 2014, International journal of food microbiology.

[44]  P. Dalgaard,et al.  Application of an iterative approach for development of a microbial model predicting the shelf-life of packed fish. , 1997, International journal of food microbiology.

[45]  Miaoyun Li,et al.  Evaluating growth models of Pseudomonas spp. in seasoned prepared chicken stored at different temperatures by the principal component analysis (PCA). , 2014, Food microbiology.

[46]  J P Flandrois,et al.  Convenient Model To Describe the Combined Effects of Temperature and pH on Microbial Growth , 1995, Applied and environmental microbiology.

[47]  R. Moreira,et al.  Modeling the growth rates of Escherichia coli spp. and Salmonella Typhimurium LT2 in baby spinach leaves under slow cooling , 2013 .

[48]  M. Danyluk,et al.  Development and validation of a mathematical model for growth of pathogens in cut melons. , 2013, Journal of food protection.

[49]  Isabelle Albert,et al.  Inferring an Augmented Bayesian Network to Confront a Complex Quantitative Microbial Risk Assessment Model with Durability Studies: Application to Bacillus Cereus on a Courgette Purée Production Chain , 2013, Risk analysis : an official publication of the Society for Risk Analysis.

[50]  M. Peleg,et al.  Microbial Growth Curves: What the Models Tell Us and What They Cannot , 2011, Critical reviews in food science and nutrition.

[51]  Paulo Ricardo Santos da Silva,et al.  Integrating a kinetic microbial model with a heat transfer model to predict Byssochlamys fulva growth in refrigerated papaya pulp , 2013 .

[52]  Arie H Havelaar,et al.  Fine-tuning Food Safety Objectives and risk assessment. , 2004, International journal of food microbiology.

[53]  S. Duffy,et al.  Modeling Yeast Spoilage in Cold-Filled Ready-To-Drink Beverages with Saccharomyces cerevisiae, Zygosaccharomyces bailii, and Candida lipolytica , 2002, Applied and Environmental Microbiology.

[54]  A. M. Lammerding,et al.  Predictive microbiology in quantitative risk assessment. , 2004 .

[55]  Frank M. Rombouts,et al.  A decision support system for prediction of microbial spoilage in foods , 2005, Journal of Industrial Microbiology.

[56]  D W Schaffner,et al.  Modelling bacterial spoilage in cold‐filled ready to drink beverages by Acinetobacter calcoaceticus and Gluconobacter oxydans , 2001, Journal of applied microbiology.

[57]  Tian Ding,et al.  Development of predictive models for the growth of Escherichia coli O157:H7 on cabbage in Korea. , 2012, Journal of food science.

[58]  R. C. Whiting,et al.  When is simple good enough: a comparison of the Gompertz, Baranyi, and three-phase linear models for fitting bacterial growth curves , 1997 .

[59]  Lihan Huang.  Mathematical modeling and numerical analysis of the growth of non-O157 Shiga toxin-producing Escherichia coli in spinach leaves. , 2012, International journal of food microbiology.

[60]  Xuewen Lu,et al.  Modeling Microbial Responses in Food , 2003 .

[61]  F. López-Gálvez,et al.  Modelling growth of Escherichia coli O157:H7 in fresh-cut lettuce submitted to commercial process conditions: chlorine washing and modified atmosphere packaging. , 2013, Food microbiology.

[62]  Donald W. Schaffner,et al.  Modeling the growth rate and lag time of different strains of Salmonella enterica and Listeria monocytogenes in ready-to-eat lettuce. , 2012, Food microbiology.