Challenge 2: AI for Accelerated Crop Breeding 

India holds decades of breeding data, from multi-environment trials to genomic and pedigree datasets, that remain largely underused. This challenge asks: can India turn that data into a sovereign AI advantage for pulses and oilseeds? We invite proposals for breeder-ready AI tools that can compress breeding cycles from 8–10 years toward 3–4 and raise genetic gain per year by 50–100%. Solutions should cover genomic prediction, genotype-by-environment modelling, intelligent crossing design, early-generation selection, breeding-program simulation, and workflow-native breeder copilots, with a frontier track for foundation models and multi-omic integration. Data ownership must stay with ICAR and partner institutions, with open architecture, federated-learning compatibility, and benefit-sharing built in. Tools must be validated on pulses and oilseeds themselves, not assumed from cereals, and proposals need a partnership with ICAR, ICRISAT, CIMMYT, or an allied national program.

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Dr. Manish Gore

manish.gore@venturecenter.co.in I +91 74100 45657