1 – Predictive Microbiology
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[1] H. Marks,et al. Characterizing asymptotic D-values for Salmonella spp. subjected to different heating rates in sous-vide cooked beef , 2003 .
[2] Mariem Ellouze,et al. Software for predictive microbiology and risk assessment: a description and comparison of tools presented at the ICPMF8 Software Fair. , 2015, Food microbiology.
[3] I. Albert,et al. Probabilistic exposure assessment model to estimate aseptic-UHT product failure rate. , 2015, International journal of food microbiology.
[4] Dominique Vercammen,et al. Toward a next generation of predictive models: A systems biology primer , 2013 .
[5] G. Nychas,et al. Bacterial Synergism or Antagonism in a Gel Cassette System , 2003, Applied and Environmental Microbiology.
[6] 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.
[7] Zhao Zhang,et al. Modeling Vibrio parahaemolyticus inactivation by acidic electrolyzed water on cooked shrimp using response surface methodology , 2014 .
[8] Konstantinos P. Koutsoumanis,et al. A comparative study on growth limits of Listeria monocytogenes as affected by temperature, pH and aw when grown in suspension or on a solid surface , 2004 .
[9] Lihan Huang,et al. IPMP 2013--a comprehensive data analysis tool for predictive microbiology. , 2014, International journal of food microbiology.
[10] M. Hendrickx,et al. Model based process design of the combined high pressure and mild heat treatment ensuring safety and quality of a carrot simulant system , 2007 .
[11] S. Koseki,et al. Modelling the bacterial survival/death interface induced by high pressure processing. , 2007, International journal of food microbiology.
[12] S. Koseki,et al. Microbial Responses Viewer (MRV): a new ComBase-derived database of microbial responses to food environments. , 2009, International journal of food microbiology.
[13] A H Geeraerd,et al. GInaFiT, a freeware tool to assess non-log-linear microbial survivor curves. , 2005, International journal of food microbiology.
[14] B Leporq,et al. The "Sym'Previus" software, a tool to support decisions to the foodstuff safety. , 2005, International journal of food microbiology.
[15] S M Alzamora,et al. Probabilistic modeling of Saccharomyces cerevisiae inhibition under the effects of water activity, pH, and potassium sorbate concentration. , 2000, Journal of food protection.
[16] Bart Nicolai,et al. Application note: OptiPa, an essential primer to develop models in the postharvest area , 2007 .
[17] V. Valdramidis,et al. Modelling the recovery of Listeria monocytogenes in high pressure processed simulated cured meat , 2015 .
[18] J Olley,et al. Predictive microbiology: towards the interface and beyond. , 2002, International journal of food microbiology.
[19] J Baranyi,et al. A dynamic approach to predicting bacterial growth in food. , 1994, International journal of food microbiology.
[20] C. Pin,et al. Modelling the effect of the temperature and carbon dioxide on the growth of spoilage bacteria in packed fish products , 2013 .
[21] W. D. Bigelow,et al. The logarithmic nature of thermal death time curves , 1921 .
[22] J. V. Van Impe,et al. Reflections on the use of robust and least-squares non-linear regression to model challenge tests conducted in/on food products. , 2005, International journal of food microbiology.
[23] S. Koseki,et al. Use of mild-heat treatment following high-pressure processing to prevent recovery of pressure-injured Listeria monocytogenes in milk. , 2008, Food microbiology.
[24] P. Taoukis,et al. Kinetic study of high pressure microbial and enzyme inactivation and selection of pasteurisation conditions for Valencia Orange Juice. , 2010 .
[25] F N Arroyo López,et al. Modelling of the growth-no growth interface of Issatchenkia occidentalis, an olive spoiling yeast, as a function of the culture media, NaCl, citric and sorbic acid concentrations: study of its inactivation in the no growth region. , 2007, International journal of food microbiology.
[26] W. Graham,et al. Defining the stability interfaces of apple juice: Implications on the optimisation and design of High Hydrostatic Pressure treatment , 2009 .
[27] P. Dantigny,et al. Application of Doehlert design to determine the combined effects of temperature, water activity and pH on conidial germination of Penicillium chrysogenum , 2001, Journal of applied microbiology.
[28] J. Sutherland,et al. Validating predictive models of food spoilage organisms , 1999, Journal of applied microbiology.
[29] R. C. Whiting,et al. Microbial modeling in foods. , 1995, Critical reviews in food science and nutrition.
[30] K. H. Driscoll,et al. Determination of thermal lethality of Listeria monocytogenes in fully cooked chicken breast fillets and strips during postcook in-package pasteurization. , 2003, Journal of food protection.
[31] S. Arrhenius. Über die Reaktionsgeschwindigkeit bei der Inversion von Rohrzucker durch Säuren , 1889 .
[32] Stanley Brul,et al. Microbial systems biology: new frontiers open to predictive microbiology. , 2008, International journal of food microbiology.
[33] T. Brocklehurst,et al. Modelling microbial growth in structured foods: towards a unified approach. , 2002, International journal of food microbiology.
[34] Jan Van Impe,et al. Comparing experimental design schemes in predictive food microbiology: Optimal parameter estimation of secondary models , 2012 .
[35] 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.
[36] T. Ross,et al. Modelling the bacterial growth/no growth interface , 1995 .
[37] George-John E. Nychas,et al. Original papers: Development and validation of a tertiary simulation model for predicting the growth of the food microorganisms under dynamic and static temperature conditions , 2011 .
[38] K Bernaerts,et al. Exploring the performance of logistic regression model types on growth/no growth data of Listeria monocytogenes. , 2007, International journal of food microbiology.
[39] Paw Dalgaard,et al. Seafood Spoilage Predictor--development and distribution of a product specific application software. , 2002, International journal of food microbiology.
[40] R. C. Whiting,et al. Model for the survival of Staphylococcus aureus in nongrowth environments. , 1996, International journal of food microbiology.
[41] M. Peleg,et al. Interactive software for estimating the efficacy of non-isothermal heat preservation processes. , 2008, Journal of food microbiology.
[42] 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.
[43] Roos D. Servaes,et al. Optimal temperature input design for estimation of the square root model parameters: parameter accuracy and model validity restrictions. , 2002, International journal of food microbiology.
[44] W. Fang,et al. A predictive model for assessment of decontamination effects of lactic acid and chitosan used in combination on Vibrio parahaemolyticus in shrimps. , 2013, International journal of food microbiology.
[45] I. Leguerinel,et al. Quantification of spore resistance for assessment and optimization of heating processes: a never-ending story. , 2010, Food microbiology.