Chapter 19 – Unraveling Food Production Microbiomes: Concepts and Future Directions

Characterization of the microbiota in food production systems both in the live animal and in postharvest food–processing settings has always been a part of the analytical landscape. Certainly, foodborne pathogen detection has been important from a public health standpoint and continues to offer challenges for development of control measures to limit the impact of the presence of foodborne pathogens in all phases of food production from farm to fork. With the advent of improvements and subsequent widescale application of 16S ribosomal RNA gene–based microbiome sequencing, a new appreciation of microbial community dynamics is becoming realized. The interaction between the gastrointestinal tract microbiome and the host animal has helped to establish the concept of a healthy gut and identification of factors that may negatively influence the gut ecosystem is just one such example. However, as the data sets expand at a rapid rate and become multidimensional, the computational bioinformatics can become a limitation. There are several software pipelines currently available that are relatively accessible. In the future, computer program tools such as machine learning may provide further insight into microbiome data and potentially be used for making predictions based on data availability. Such approaches could be useful for the food industry to appraise various intervention strategies implemented in food production.