description
- Feeding a growing population under increasing climate disruption demands a shift toward sustainable, stress-resilient cropping systems that minimize fertilizer and pesticide inputs while restoring soil health and improving crop nutrition. Bioinoculants - microbes that enhance plant growth, nutrient uptake and stress resilience - show great promise, yet their field effectiveness remains inconsistent. Current bioinoculant development depends on empirical evaluation, constrained by our limited understanding of the ecological and molecular rules governing plant microbiome assembly and function. By uniting crop science, microbial ecology, data science and Artificial Intelligence (AI), NOAH will establish the first AI foundation model for crop microbiomes: ARCA (AI-guided Root microbiome engineering for ClimAte-resilient and nutritious crops). Building on the deterministic principles of microbiome assembly, NOAH’s ARCA integrates microbial functional traits, host genotype, and environmental metadata to model and design microbiome configurations that optimize crop performance. ARCA will be trained on over 300,000 curated public microbiome datasets, enhanced by large language model-driven metadata extraction, and tailored using high-resolution data from five major crops: wheat, tomato, faba bean, oilseed rape, and apple across diverse soils and stress conditions. Iterative design–build–test–learn (DBTL) cycles under controlled and field conditions ensure a progressive refinement of model accuracy and generalization. NOAH will deliver a predictive and generative AI biotechnology capable of identifying beneficial microbial consortia and revealing missing functional components in suboptimal microbiomes. This breakthrough approach will transform microbiome engineering from empirical discovery into rational, model-driven design, accelerating the effective deployment of bioinoculants that enhance crop climate resilience and nutritional quality in a sustainable manner.