The early detection of spoilage microorganisms and food pathogens is of paramount importance in food production systems. We propose a novel strategy for the early detection of food production defects, harnessing the product microbiome. We hypothesize that by establishing microbiome datasets of proper and defective batches, indicator bacteria signaling production errors can be identified and targeted for rapid quantification as part of routine practice. Using the production process of pastrami as a model, we characterized its live microbiome profiles throughout the production stages and in the final product, using propidium monoazide treatment followed by 16S rDNA sequencing. Pastrami demonstrated product-specific and consistent microbiome profiles predominated by
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Hakmon et al. (2024) studied this question.
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