{"title":"Screening dominant bacteria and establishing models to predict the growth of Serratia in cold fresh chicken","authors":"Jing Tao, Ya-Jing Huang, Xian-Shuang Deng, Jia-Le He, Fei Zhao, Qing-Ping Xu, Jin-Liang Chen, Jia-Heng Yan","doi":"10.1007/s11694-025-03349-9","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>Chilled meat is highly susceptible to microbial contamination due to its rich nutrition. There is a close relationship between the growth of spoilage microorganisms and the shelf life of chilled meat. The growth rate of these bacteria varies significantly at different temperature levels. The identification of specific spoilage bacteria through strain-specific traits and temperature parameters, along with the development of predictive models, can advance the progress of cold chain logistics and the chilled food sector. In this study, chicken breast meat was used as the research object to analyze the changes in sensory, physicochemical, and microbial indicators of chicken breast meat during storage at 4 °C. The mechanism of its spoilage was revealed, and the dominant spoilage bacteria were isolated and identified. A shelf life prediction model for chicken breast meat during cold storage was established. The research results indicate that the pH of chicken breast meat stored at 4 °C shows a trend of first decreasing and then increasing, and the number of main spoilage bacteria increases over time. On the 8th day, the comprehensive sensory score and physicochemical indicators reach unacceptable limits. The experiment identified two strains of <i>Serratia</i>, which are the main dominant spoilage bacteria in chicken breast meat during cold storage. The Gompertz and Belehradek equations of Origin software were used to fit the growth of <i>Serratia</i> in chicken breast meat. A prediction model for <i>Serratia</i> growth was successfully established within the temperature range of 4–20 °C. The evaluation coefficients R<sup>2</sup> are all greater than 0.97, and the Bf value is stable between 0.9 and 1.1, which proves that the model can accurately predict the growth of <i>Serratia</i> at different temperatures. When fitting the relationship between temperature and maximum specific growth rate and delay period in the Belehradek model, we found a clear linear relationship between the two. This indicates that the model can reliably predict the shelf life of chicken breast meat in different temperature regions. The shelf life prediction model has practical guiding significance and application value for the quality and biosafety of chilled meat.</p>\n </div>","PeriodicalId":631,"journal":{"name":"Journal of Food Measurement and Characterization","volume":"19 8","pages":"5708 - 5719"},"PeriodicalIF":3.3000,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Food Measurement and Characterization","FirstCategoryId":"97","ListUrlMain":"https://link.springer.com/article/10.1007/s11694-025-03349-9","RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Chilled meat is highly susceptible to microbial contamination due to its rich nutrition. There is a close relationship between the growth of spoilage microorganisms and the shelf life of chilled meat. The growth rate of these bacteria varies significantly at different temperature levels. The identification of specific spoilage bacteria through strain-specific traits and temperature parameters, along with the development of predictive models, can advance the progress of cold chain logistics and the chilled food sector. In this study, chicken breast meat was used as the research object to analyze the changes in sensory, physicochemical, and microbial indicators of chicken breast meat during storage at 4 °C. The mechanism of its spoilage was revealed, and the dominant spoilage bacteria were isolated and identified. A shelf life prediction model for chicken breast meat during cold storage was established. The research results indicate that the pH of chicken breast meat stored at 4 °C shows a trend of first decreasing and then increasing, and the number of main spoilage bacteria increases over time. On the 8th day, the comprehensive sensory score and physicochemical indicators reach unacceptable limits. The experiment identified two strains of Serratia, which are the main dominant spoilage bacteria in chicken breast meat during cold storage. The Gompertz and Belehradek equations of Origin software were used to fit the growth of Serratia in chicken breast meat. A prediction model for Serratia growth was successfully established within the temperature range of 4–20 °C. The evaluation coefficients R2 are all greater than 0.97, and the Bf value is stable between 0.9 and 1.1, which proves that the model can accurately predict the growth of Serratia at different temperatures. When fitting the relationship between temperature and maximum specific growth rate and delay period in the Belehradek model, we found a clear linear relationship between the two. This indicates that the model can reliably predict the shelf life of chicken breast meat in different temperature regions. The shelf life prediction model has practical guiding significance and application value for the quality and biosafety of chilled meat.
期刊介绍:
This interdisciplinary journal publishes new measurement results, characteristic properties, differentiating patterns, measurement methods and procedures for such purposes as food process innovation, product development, quality control, and safety assurance.
The journal encompasses all topics related to food property measurement and characterization, including all types of measured properties of food and food materials, features and patterns, measurement principles and techniques, development and evaluation of technologies, novel uses and applications, and industrial implementation of systems and procedures.