J. Hein M. van Lieverloo , Mounia Bijlaart , Marjon H.J. Wells-Bennik , Heidy M.W. Den Besten , Marcel H. Zwietering
{"title":"在调整了水活度、糖含量和pH值的影响后,食物链中常见的7属植物性细菌病原体的热失活动力学相似","authors":"J. Hein M. van Lieverloo , Mounia Bijlaart , Marjon H.J. Wells-Bennik , Heidy M.W. Den Besten , Marcel H. Zwietering","doi":"10.1016/j.mran.2021.100174","DOIUrl":null,"url":null,"abstract":"<div><p>A predictive model was made for the logarithm of the thermal decimal reduction time (logD) of <em>Salmonella enterica</em> (<em>D</em> = time to 90% reduction by inactivation). The model was fitted with multiple linear regression from 521 logD-values reported in literature for laboratory media and foods highly varying in water activity and pH. The single regression model with temperature as the only variable had a high residual standard error (RSE) of 0.883 logD and no predictive value (fraction of variance explained (R<sup>2</sup>) < 0.001). Adding water activity, sugar content and pH as predictors resulted in a model with a lower RSE of 0.458 logD and an adjusted R<sup>2</sup> of 0.73. The model was validated by comparing 985 predicted with observed logD for <em>S. enterica</em> from other publications. The model was subsequently validated with 1498 published logD-values for inactivation of vegetative cells of nine other pathogenic bacteria genera (mainly <em>Listeria monocytogenes, Escherichia coli, Clostridium perfringens, Cronobacter</em> spp., <em>Staphylococcus aureus, Yersinia enterocolitica</em>) in or on a variety of laboratory media, meat, fish, dairy, nuts, fruits and vegetables. Regression analyses for validation with the 985 logD of <em>S. enterica</em> and 2483 logD of all genera show deviations from the expected slope of 1 (both 0.81) and the expected intercept of 0 (0.04 and 0.19 logD respectively). However, only 0.7% and 2% respectively of the new logD (expected: 0.5%) were observed above the 99% prediction interval of the original <em>S. enterica</em> model based on 521 logD. The findings suggest that i) the variability of thermal resistance of strains within species is larger than between genera and species; ii) one generic predictive model, also accounting for variability, suffices for designing the thermal inactivation of a variety of vegetative pathogenic bacteria in many food types.</p></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"19 ","pages":"Article 100174"},"PeriodicalIF":3.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.mran.2021.100174","citationCount":"2","resultStr":"{\"title\":\"Thermal inactivation kinetics of seven genera of vegetative bacterial pathogens common to the food chain are similar after adjusting for effects of water activity, sugar content and pH\",\"authors\":\"J. Hein M. van Lieverloo , Mounia Bijlaart , Marjon H.J. Wells-Bennik , Heidy M.W. Den Besten , Marcel H. Zwietering\",\"doi\":\"10.1016/j.mran.2021.100174\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>A predictive model was made for the logarithm of the thermal decimal reduction time (logD) of <em>Salmonella enterica</em> (<em>D</em> = time to 90% reduction by inactivation). The model was fitted with multiple linear regression from 521 logD-values reported in literature for laboratory media and foods highly varying in water activity and pH. The single regression model with temperature as the only variable had a high residual standard error (RSE) of 0.883 logD and no predictive value (fraction of variance explained (R<sup>2</sup>) < 0.001). Adding water activity, sugar content and pH as predictors resulted in a model with a lower RSE of 0.458 logD and an adjusted R<sup>2</sup> of 0.73. The model was validated by comparing 985 predicted with observed logD for <em>S. enterica</em> from other publications. The model was subsequently validated with 1498 published logD-values for inactivation of vegetative cells of nine other pathogenic bacteria genera (mainly <em>Listeria monocytogenes, Escherichia coli, Clostridium perfringens, Cronobacter</em> spp., <em>Staphylococcus aureus, Yersinia enterocolitica</em>) in or on a variety of laboratory media, meat, fish, dairy, nuts, fruits and vegetables. Regression analyses for validation with the 985 logD of <em>S. enterica</em> and 2483 logD of all genera show deviations from the expected slope of 1 (both 0.81) and the expected intercept of 0 (0.04 and 0.19 logD respectively). However, only 0.7% and 2% respectively of the new logD (expected: 0.5%) were observed above the 99% prediction interval of the original <em>S. enterica</em> model based on 521 logD. The findings suggest that i) the variability of thermal resistance of strains within species is larger than between genera and species; ii) one generic predictive model, also accounting for variability, suffices for designing the thermal inactivation of a variety of vegetative pathogenic bacteria in many food types.</p></div>\",\"PeriodicalId\":48593,\"journal\":{\"name\":\"Microbial Risk Analysis\",\"volume\":\"19 \",\"pages\":\"Article 100174\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2021-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.mran.2021.100174\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Microbial Risk Analysis\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352352221000165\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Microbial Risk Analysis","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352352221000165","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Thermal inactivation kinetics of seven genera of vegetative bacterial pathogens common to the food chain are similar after adjusting for effects of water activity, sugar content and pH
A predictive model was made for the logarithm of the thermal decimal reduction time (logD) of Salmonella enterica (D = time to 90% reduction by inactivation). The model was fitted with multiple linear regression from 521 logD-values reported in literature for laboratory media and foods highly varying in water activity and pH. The single regression model with temperature as the only variable had a high residual standard error (RSE) of 0.883 logD and no predictive value (fraction of variance explained (R2) < 0.001). Adding water activity, sugar content and pH as predictors resulted in a model with a lower RSE of 0.458 logD and an adjusted R2 of 0.73. The model was validated by comparing 985 predicted with observed logD for S. enterica from other publications. The model was subsequently validated with 1498 published logD-values for inactivation of vegetative cells of nine other pathogenic bacteria genera (mainly Listeria monocytogenes, Escherichia coli, Clostridium perfringens, Cronobacter spp., Staphylococcus aureus, Yersinia enterocolitica) in or on a variety of laboratory media, meat, fish, dairy, nuts, fruits and vegetables. Regression analyses for validation with the 985 logD of S. enterica and 2483 logD of all genera show deviations from the expected slope of 1 (both 0.81) and the expected intercept of 0 (0.04 and 0.19 logD respectively). However, only 0.7% and 2% respectively of the new logD (expected: 0.5%) were observed above the 99% prediction interval of the original S. enterica model based on 521 logD. The findings suggest that i) the variability of thermal resistance of strains within species is larger than between genera and species; ii) one generic predictive model, also accounting for variability, suffices for designing the thermal inactivation of a variety of vegetative pathogenic bacteria in many food types.
期刊介绍:
The journal Microbial Risk Analysis accepts articles dealing with the study of risk analysis applied to microbial hazards. Manuscripts should at least cover any of the components of risk assessment (risk characterization, exposure assessment, etc.), risk management and/or risk communication in any microbiology field (clinical, environmental, food, veterinary, etc.). This journal also accepts article dealing with predictive microbiology, quantitative microbial ecology, mathematical modeling, risk studies applied to microbial ecology, quantitative microbiology for epidemiological studies, statistical methods applied to microbiology, and laws and regulatory policies aimed at lessening the risk of microbial hazards. Work focusing on risk studies of viruses, parasites, microbial toxins, antimicrobial resistant organisms, genetically modified organisms (GMOs), and recombinant DNA products are also acceptable.