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

IF 3.3 3区 农林科学 Q2 FOOD SCIENCE & TECHNOLOGY
Jing Tao, Ya-Jing Huang, Xian-Shuang Deng, Jia-Le He, Fei Zhao, Qing-Ping Xu, Jin-Liang Chen, Jia-Heng Yan
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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.

Abstract Image

Abstract Image

冷鲜鸡中沙雷菌的优势菌筛选及模型建立
冰鲜肉营养丰富,极易受到微生物污染。腐败微生物的生长与冰鲜肉的保质期有密切的关系。这些细菌的生长速度在不同的温度水平下变化很大。通过菌株特异性特征和温度参数识别特定腐败菌,以及预测模型的发展,可以推动冷链物流和冷藏食品领域的进步。本研究以鸡胸肉为研究对象,分析了鸡胸肉在4℃贮藏过程中感官、理化、微生物指标的变化。揭示了其腐败机制,并分离鉴定了其优势腐败菌。建立了鸡胸肉冷藏期预测模型。研究结果表明,在4℃贮藏条件下,鸡胸肉的pH值呈现先降低后升高的趋势,主要腐败菌数量随时间增加。第8天,感官综合评分和理化指标均达到不可接受限度。本实验鉴定出两株沙雷氏菌,它们是鸡胸肉冷藏过程中主要的优势腐败菌。采用Origin软件的Gompertz和Belehradek方程拟合沙雷菌在鸡胸肉中的生长。成功建立了4 ~ 20℃温度范围内沙雷菌生长的预测模型。评价系数R2均大于0.97,Bf值稳定在0.9 ~ 1.1之间,证明该模型能准确预测不同温度下沙雷菌的生长。在Belehradek模型中拟合温度与最大比生长率和延迟期的关系时,我们发现两者之间存在明显的线性关系。结果表明,该模型能较好地预测不同温度区域下鸡胸肉的保质期。该保质期预测模型对冷鲜肉的质量和生物安全具有实际的指导意义和应用价值。
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来源期刊
Journal of Food Measurement and Characterization
Journal of Food Measurement and Characterization Agricultural and Biological Sciences-Food Science
CiteScore
6.00
自引率
11.80%
发文量
425
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.
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