Scholarlink

<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&#xa0;°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&#xa0;°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&#xa0;°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>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Screening dominant bacteria and establishing models to predict the growth of Serratia in cold fresh chicken

  • 期刊论文

  • 发表日期：

    2025年7月2日

查看全文
  • Jing Tao,
  • Ya-Jing Huang,
  • Xian-Shuang Deng,
  • Jia-Le He,
  • Fei Zhao,
  • Qing-Ping Xu,
  • Jin-Liang Chen,
  • Jia-Heng Yan

摘要

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.