Challenges related to natural resource degradation, climate change and their projected impact on food security are the major concerns for humanity in the densely populated Indian subcontinent. Sustainable intensification practices based on conservation agriculture (CA) have demonstrated potential to address many of these challenges and are being advocated to ensure sustainable food security in the future. In general, high yielding crop varieties are developed and evaluated under conventional agronomic management practices. However, varieties developed and tested under conventional agronomic practices may perform differently under conservation agriculture practices in a specific mega-environment. Therefore, development of high yielding, resource efficient, climate-smart varieties when combined with improved agronomic management, especially CA-based cropping system optimization, may minimize yield gaps while addressing natural resource challenges. Therefore, it is imperative to capture G x E x M interactions in major mega-environments to define recommendation domains.
Prepare a minimum dataset template for analyzing G x E x M interactions.
• Collect and analyze weather and soil data of major wheat mega-environments in India.
• Collect and manage G x E x M data of CIMMYT wheat trials conducted during the past 3-4 years.
• Collect additional/missing data from ongoing trials.
• Analyze G x E x M datasets and develop at least one research article for a high impact journal.
Good knowledge of spoken and written English. Ability to work in the field on data collection, compilation and management. Strong skills in basic applications, statistical tools and techniques, and data analysis. Candidates with knowledge of GIS are encouraged to apply.