Editorial: Measurements and modelling of methane emissions from agricultural cropping systems

2025) show that intermittent irrigation in rice systems can substantially reduce CH₄ emissions in some cases, eliminating emissions without yield penalties across contrasting environments, making water management a pragmatic, site-adaptable lever. Kalita and Borah (2026) document nutrient management trade-offs in the Brahmaputra Valley: organic management increases CH 4 production potential via greater carbon availability but also improves soil organic carbon, microbial biomass, grain quality, and yield, illustrating that input-specific strategies can reconcile mitigation with agronomic goals.Together, these studies define a practical pathway: standardized measurements reduce uncertainty, high-throughput sensing increases data density, and AI models convert complex signals into farm-level guidance. Linked, these elements form a measurement modelling management loop that enables targeted, context-sensitive mitigation while accounting for soil-health and productivity trade-offs and co-benefits.Priorities to scale this pathway: adopt interoperable data standards and open repositories; expand CH4 measurement comparison among continuous measurement systems; build geographically and management-diverse training datasets; evaluate performance of CH4 models using ensemble modeling approach; fund long-term studies tracking climate and soil health trade-offs and co-benefits preferably with both the public and private sector support to continuity and scientific rigor; and pair technical advances with socio-economic and behavioral research to ensure recommendations are practical, cost-effective, and equitable.Policymakers should fund measurement infrastructure, data interoperability, and on-farm trials that link measurements to actionable guidance, and support high-throughput networks and open data to accelerate model development. Practitioners should adopt measurement-ready practices and evaluate mitigation within