AI-Guided Precision Fermentation for the Development of Personalized Functional Foods: A Food Technology Framework for Nutritional Optimization
Year: 2026
Type: article
Abstract: Artificial intelligence (AI) is transforming food technology by enabling data-driven optimization of food formulation, processing, and nutritional personalization. Precision fermentation has emerged as a promising technology for producing functional ingredients with enhanced nutritional and health-promoting properties. The integration of AI with precision fermentation offers opportunities to design personalized functional foods tailored to individual nutritional requirements, metabolic profiles, and health objectives. This study proposes an AI-guided precision fermentation framework for the development of personalized functional foods. The framework integrates machine learning algorithms, microbial strain selection, fermentation parameter optimization, and personalized nutritional profiling to maximize nutritional performance and functional efficacy. Four theoretical production scenarios were evaluated, including a conventional fermentation control and three progressively advanced AI-assisted optimization models. Anticipated outcomes were generated based on established principles of food biotechnology, fermentation science, nutritional modeling, and artificial intelligence. The proposed framework demonstrates the potential of AI-assisted fermentation systems to improve nutrient bioavailability, functional compound production, process efficiency, and personalization accuracy. The study serves as a conceptual model and methodological template for future experimental validation and industrial implementation.
Source: Research consortium archive.
Author: Research Consortium Archive
Language: English
Subfield: Food Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W7165361486