The potential effect of microbiota in predicting the freshness of chilled chicken

1. The goals of this study were to analyse the changes in microbiota composition of chilled chicken during storage and identify microbial biomarkers related to meat freshness.
2. The study used 16S rDNA sequencing to track the microbiota shift in chilled chicken during storage. Associations between microbiota composition and storage time were analysed and microbial biomarkers were identified.
3. The results showed that microbial diversity of chilled chicken decreased with the storage time. A total of 27 and 24 microbial biomarkers were identified by using orthogonal partial least squares (OPLS) and the random forest regression approach, respectively. The receiver operating characteristic (ROC) curve analysis indicated that the OPLS regression approach had better performance in identifying freshness-related biomarkers. The multiple stepwise regression analysis identified four key microbial biomarkers, including Streptococcus, Carnobacterium, Serratia and Photobacterium genera and constructed a predictive model.
4. The study provided microbial biomarkers and a model related to the freshness of chilled chicken. These findings provide a basis for developing detection methods of the freshness of chilled chicken.