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

ABSTRACT

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.

KEYWORDS:

• Microbial biomarker
• 16S rDNA
• meat quality
• spoilage
• food microbiology

Acknowledgments

The present study used the same samples and datasets reported in a previous study (Zhang et al. 2021). By using the same samples and dataset, similar results are obtained in both studies. Similar results are mainly concerned with the changes in the microbiota composition of chilled chicken samples during storage and have been acknowledged and cited in the manuscript. Nevertheless, the main results reported in the two studies are different and the two studies had distinct aims. The previous study aimed to explore the mechanisms of chilled chicken spoilage caused by microbiota using an integrated microbiome and metabolome analysis. The present study analysed the association between microbiota composition and storage time and explored the potential of microbiota in predicting the freshness of chilled chicken. Moreover, the methods used in the two studies were largely different. In addition, the authors would like to thank Guangzhou Genedenovo Biotechnology Co., Ltd for assisting in 16s rRNA analysis.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are openly available in [Genome Sequence Archive (GSA)] at [https://ngdc.cncb.ac.cn/gsa/], reference number [CRA003975].

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

This work was supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD); China Agriculture Research System of MOF and MARA [CARS-41]; The Natural Science Foundation of Jiangsu Province [BK20180909]; The New Agricultural Breeds Creation Project in Jiangsu Province [PZCZ201730] and The Open Project Program of Joint International Research Laboratory of Agriculture and Agri-Product Safety, The Ministry of Education of China, Yangzhou University [JILAR-KF202016].