Liu-Yean Goh , Tzu-Ping Kao , Yi-Chun Pan , Ching-Wen Chang , Kuan-Hung Lu
{"title":"生牛肉和熟牛肉中尿路致病性大肠杆菌的生长模型作为储存温度的函数,用于保质期预测","authors":"Liu-Yean Goh , Tzu-Ping Kao , Yi-Chun Pan , Ching-Wen Chang , Kuan-Hung Lu","doi":"10.1016/j.ijfoodmicro.2025.111359","DOIUrl":null,"url":null,"abstract":"<div><div>In this study, we investigated the presence of uropathogenic <em>Escherichia coli</em> (UPEC) in retail beef in Taiwan and evaluated the effects of storage temperatures on UPEC growth in raw and cooked beef. In total, 50 beef samples were analyzed for <em>E. coli</em> using plate count methods, with UPEC identified via a polymerase chain reaction. In addition, a four-strain UPEC cocktail, including two locally isolated strains, was inoculated onto raw and cooked beef and incubated at 4, 10, 20, 25, and 35 °C. Growth data were fitted using four primary models (Huang, Baranyi, reparameterized Gompertz, and no-lag phase), while secondary models (Ratkowsky and Huang square-root) were used to assess temperature effects on growth rates. From the sampling campaign, UPEC was detected in 5/30 (16.7%) raw and 2/20 (10.0%) ready-to-eat beef samples. In challenge-test studies, growth occurred in both beef types between 10 and 35 °C, with negligible lag phases. The no-lag phase model, combined with Ratkowsky square-root for raw beef and Huang square-root for cooked beef, provided the best fit (low root mean squared error (RMSE), 0.036–0.095). The estimated minimum growth temperatures for raw and cooked beef were 5.8 ± 2.1 and 6.4 ± 0.7 °C, respectively. Validation at 30 °C demonstrated reliable predictions for raw (RMSE, 0.38 log CFU/g; <em>R</em><sup>2</sup><sub>adj</sub>, 0.99) and cooked (RMSE, 0.49 log CFU/g; <em>R</em><sup>2</sup><sub>adj</sub>, 0.99) beef chuck. Predictions for ground beef remained acceptable (RMSE, 0.68 for raw, 0.58 for cooked). Moreover, shelf life charts were developed based on models established in this study. These findings underscore the presence of UPEC in retail beef and provide a validated predictive model for UPEC growth which can be applied to microbial risk assessments. Integrating predictive modeling and shelf life estimation offers a valuable tool for food retailers and the meat industry, enabling more-accurate UPEC growth predictions and enhancing microbial safety strategies.</div></div>","PeriodicalId":14095,"journal":{"name":"International journal of food microbiology","volume":"442 ","pages":"Article 111359"},"PeriodicalIF":5.2000,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Growth modeling of uropathogenic Escherichia coli in raw and cooked beef as a function of storage temperature for shelf life predictions\",\"authors\":\"Liu-Yean Goh , Tzu-Ping Kao , Yi-Chun Pan , Ching-Wen Chang , Kuan-Hung Lu\",\"doi\":\"10.1016/j.ijfoodmicro.2025.111359\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In this study, we investigated the presence of uropathogenic <em>Escherichia coli</em> (UPEC) in retail beef in Taiwan and evaluated the effects of storage temperatures on UPEC growth in raw and cooked beef. In total, 50 beef samples were analyzed for <em>E. coli</em> using plate count methods, with UPEC identified via a polymerase chain reaction. In addition, a four-strain UPEC cocktail, including two locally isolated strains, was inoculated onto raw and cooked beef and incubated at 4, 10, 20, 25, and 35 °C. Growth data were fitted using four primary models (Huang, Baranyi, reparameterized Gompertz, and no-lag phase), while secondary models (Ratkowsky and Huang square-root) were used to assess temperature effects on growth rates. From the sampling campaign, UPEC was detected in 5/30 (16.7%) raw and 2/20 (10.0%) ready-to-eat beef samples. In challenge-test studies, growth occurred in both beef types between 10 and 35 °C, with negligible lag phases. The no-lag phase model, combined with Ratkowsky square-root for raw beef and Huang square-root for cooked beef, provided the best fit (low root mean squared error (RMSE), 0.036–0.095). The estimated minimum growth temperatures for raw and cooked beef were 5.8 ± 2.1 and 6.4 ± 0.7 °C, respectively. Validation at 30 °C demonstrated reliable predictions for raw (RMSE, 0.38 log CFU/g; <em>R</em><sup>2</sup><sub>adj</sub>, 0.99) and cooked (RMSE, 0.49 log CFU/g; <em>R</em><sup>2</sup><sub>adj</sub>, 0.99) beef chuck. Predictions for ground beef remained acceptable (RMSE, 0.68 for raw, 0.58 for cooked). Moreover, shelf life charts were developed based on models established in this study. These findings underscore the presence of UPEC in retail beef and provide a validated predictive model for UPEC growth which can be applied to microbial risk assessments. Integrating predictive modeling and shelf life estimation offers a valuable tool for food retailers and the meat industry, enabling more-accurate UPEC growth predictions and enhancing microbial safety strategies.</div></div>\",\"PeriodicalId\":14095,\"journal\":{\"name\":\"International journal of food microbiology\",\"volume\":\"442 \",\"pages\":\"Article 111359\"},\"PeriodicalIF\":5.2000,\"publicationDate\":\"2025-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of food microbiology\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0168160525003046\",\"RegionNum\":1,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"FOOD SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of food microbiology","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0168160525003046","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
Growth modeling of uropathogenic Escherichia coli in raw and cooked beef as a function of storage temperature for shelf life predictions
In this study, we investigated the presence of uropathogenic Escherichia coli (UPEC) in retail beef in Taiwan and evaluated the effects of storage temperatures on UPEC growth in raw and cooked beef. In total, 50 beef samples were analyzed for E. coli using plate count methods, with UPEC identified via a polymerase chain reaction. In addition, a four-strain UPEC cocktail, including two locally isolated strains, was inoculated onto raw and cooked beef and incubated at 4, 10, 20, 25, and 35 °C. Growth data were fitted using four primary models (Huang, Baranyi, reparameterized Gompertz, and no-lag phase), while secondary models (Ratkowsky and Huang square-root) were used to assess temperature effects on growth rates. From the sampling campaign, UPEC was detected in 5/30 (16.7%) raw and 2/20 (10.0%) ready-to-eat beef samples. In challenge-test studies, growth occurred in both beef types between 10 and 35 °C, with negligible lag phases. The no-lag phase model, combined with Ratkowsky square-root for raw beef and Huang square-root for cooked beef, provided the best fit (low root mean squared error (RMSE), 0.036–0.095). The estimated minimum growth temperatures for raw and cooked beef were 5.8 ± 2.1 and 6.4 ± 0.7 °C, respectively. Validation at 30 °C demonstrated reliable predictions for raw (RMSE, 0.38 log CFU/g; R2adj, 0.99) and cooked (RMSE, 0.49 log CFU/g; R2adj, 0.99) beef chuck. Predictions for ground beef remained acceptable (RMSE, 0.68 for raw, 0.58 for cooked). Moreover, shelf life charts were developed based on models established in this study. These findings underscore the presence of UPEC in retail beef and provide a validated predictive model for UPEC growth which can be applied to microbial risk assessments. Integrating predictive modeling and shelf life estimation offers a valuable tool for food retailers and the meat industry, enabling more-accurate UPEC growth predictions and enhancing microbial safety strategies.
期刊介绍:
The International Journal of Food Microbiology publishes papers dealing with all aspects of food microbiology. Articles must present information that is novel, has high impact and interest, and is of high scientific quality. They should provide scientific or technological advancement in the specific field of interest of the journal and enhance its strong international reputation. Preliminary or confirmatory results as well as contributions not strictly related to food microbiology will not be considered for publication.