Holistic integration of omics data reveals the drivers that shape the ecology of microbial meat spoilage scenarios.

ABSTRACT:

Background

The use of omics data for monitoring the microbial flow of fresh meat products along a production line and the development of spoilage prediction tools from these data is a promising but challenging task. In this context, we produced a large multivariate dataset (over 600 samples) obtained on the production lines of two similar types of fresh meat products (poultry and raw pork sausages). We describe a full analysis of this dataset in order to decipher how the spoilage microbial ecology of these two similar products may be shaped differently depending on production parameter characteristics.

Methods

Our strategy involved a holistic approach to integrate unsupervised and supervised statistical methods on multivariate data (OTU-based microbial diversity; metabolomic

SUBMITTER: Poirier S 

PROVIDER: S-EPMC10619683 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature