Omics tools offer the opportunity to characterize and trace traditional and industrial fermented foods. Bioinformatics, through machine learning, and other advanced statistical approaches, are able to disentangle fermentation processes and to predict the evolution and metabolic outcomes of a food microbial ecosystem. By assembling microbial artificial consortia, the biotechnological advances will also be able to enhance the nutritional value and organoleptics characteristics of fermented food, preserving, at the same time, the potential of autochthonous microbial consortia and metabolic pathways, which are difficult to reproduce. Preserving the traditional methods contributes to protecting the hidden value of local biodiversity, and exploits its potential in industrial processes with the final aim of guaranteeing food security and safety, even in developing countries.

组学工具提供了表征和追踪传统和工业发酵食品的机会。生物信息学，通过机器学习和其他先进的统计方法，能够解开发酵过程并预测食物微生物生态系统的进化和代谢结果。通过组装微生物人工聚生体，生物技术的进步也将能够提高发酵食品的营养价值和感官特性，同时保留难以复制的本土微生物聚生体和代谢途径的潜力。保留传统方法有助于保护当地生物多样性的隐藏价值，并在工业过程中发挥其潜力，最终目的是保障粮食安全，