AI-Driven Nutrigenomics: Engineering Climate-Resilient Biofortified Crops for India’s Nutrition Security

L Subathra; P Anisha; R Abinaya; M Anjali; G Priyaalini; D Sridevi

doi:10.34293/sijash.v13iS2-i3-Jan.10549

L Subathra Student, Department of Food Science and Nutrition, Dr. NGP Arts and Science College, Coimbatore, Tamil Nadu, India
P Anisha Student, Department of Food Science and Nutrition, Dr. NGP Arts and Science College, Coimbatore, Tamil Nadu, India
R Abinaya Student, Department of Food Science and Nutrition, Dr. NGP Arts and Science College, Coimbatore, Tamil Nadu, India
M Anjali Assistant Professor, Department of Food Science and Nutrition, Dr. NGP Arts and Science College, Coimbatore, Tamil Nadu, India
G Priyaalini Assistant Professor, Department of Food Science and Nutrition, Dr. NGP Arts and Science College, Coimbatore, Tamil Nadu, India
D Sridevi Professor & Head, Department of Food Science and Nutrition, Dr. NGP Arts and Science College, Coimbatore, Tamil Nadu, India

DOI: https://doi.org/10.34293/sijash.v13iS2-i3-Jan.10549

Keywords: Nutrigenomics, AI Breeding, Biofortification, Climate Resilient Crops, Sdg 2

Abstract

AI-driven nutrigenomics involves artificial intelligence to genetic analysis to improve human nutrition and agricultural productivity. By integrating genomics, nutrition science, and AI technologies, it helps identify genetic factors that influence nutrient absorption and metabolism. This approach supports personalised nutrition strategies, enhances the biofortification of staple crops, and accelerates the development of nutrient-dense, climate-resilient crop varieties. More than 150 biofortified crop cultivars of cereals, pulses, and oilseeds have been developed as a result of extensive research conducted by the National Agricultural Research Education and Extension System (NAREES), which is led by the Indian Council of Agricultural Research (ICAR) and involves State Agricultural Universities (SAUs) and Central Universities (CUs). India faces a major micronutrient challenge, with nearly 57% of children affected by zinc deficiency and about 35% suffering from iron-deficiency anaemia, and these nutritional concerns may be further aggravated by climate change, which threatens food security through declining crop yields and increased heat stress. In this context, AI-enabled nutrigenomics offers a promising solution by combining genomic selection, multi-omics analysis, and advanced gene-editing tools to speed up crop improvement. Successful outcomes include iron-enriched pearl millet (ICTP 8203) and zinc-fortified wheat (HD 3226), both designed to perform well under high-temperature conditions. The adoption of AI-based methods has significantly reduced the traditional crop breeding timelines from nearly a decade to just two to three years. These advances improve nutritional outcomes, enhance farmer incomes, and promote climate-resilient agriculture. Despite challenges such as limited genomic databases and regulatory barriers, AI-driven nutrigenomics demonstrates strong potential to strengthen nutrition security and support sustainable agricultural development in developing and emerging economies.