REVIEW article
Front. Nutr.
Sec. Nutrition and Food Science Technology
Volume 12 - 2025 | doi: 10.3389/fnut.2025.1659511
Precision to Plate: AI-Driven Innovations in Fermentation and Hyper-Personalized Diets
Provisionally accepted
- 1Horticultural College and Research Institute, Tamil Nadu Agricultural University, Coimbatore, India
- 2Tamil Nadu Agricultural University Horticultural College and Research Institute Coimbatore, Coimbatore, India
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The global food system faces unprecedented challenges, including climate-driven agricultural instability, rising malnutrition, and consumer demand for sustainable yet appealing products. Artificial intelligence (AI) has emerged as a transformative force in addressing these challenges, enabling breakthroughs from microbial engineering to individualized dietary solutions. This review synthesizes advances in AI-driven precision fermentation-where CRISPR-based microbial optimization and reinforcement learning accelerate bioactive compound synthesis-and hyper-personalized nutrition, where predictive modeling tailors diets to genetic, metabolic, and cultural profiles. We highlight how AI decodes sensory attributes (e.g., flavour, texture) through deep learning and natural language processing, bridging gaps between lab-scale innovation and consumer acceptance. However, the adoption of these technologies raises critical ethical concerns, including data privacy risks from wearable health monitors and algorithmic biases exacerbating nutritional disparities. Key findings include 300% yield increases for alt-proteins via AI-CRISPR fusion, 60% reduction in bioreactor failures through RL optimization, and 25% lower childhood anemia rates via equitable AI-nutrition platforms-though ethical gaps persist in data privacy (72% GDPR non-compliance) and algorithmic bias. By analyzing regulatory frameworks and proposing equityfocused design principles, this article advocates for a balanced approach to AI deployment in food systems. Emphasis on digital transformation, we underscore AI's potential to democratize sustainable food production while urging collaborative governance to ensure transparency and inclusivity. This work serves as a roadmap for researchers, policymakers, and industry stakeholders navigating the intersection of AI, biotechnology, and nutrition science.
Keywords: precision fermentation, CRISPR-microbe engineering, hyper-personalized nutrition, Algorithmic bias, Sustainable food systems
Received: 04 Jul 2025; Accepted: 12 Aug 2025.
Copyright: © 2025 D, I, S and V. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Priyadharshini D, Horticultural College and Research Institute, Tamil Nadu Agricultural University, Coimbatore, India
Muthuvel I, Horticultural College and Research Institute, Tamil Nadu Agricultural University, Coimbatore, India
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.