Diverse Data Integration for Exploiting Genotype-by-Environment-by-Management Interactions

Recent advances in plant breeding and agronomy have made it possible to move beyond breeding for wide adaptation to identifying optimal genotypes for specific environmental and management conditions. To fully exploit genotype × environment × management (G×E×M) interactions, it becomes necessary to ascertain a wide array of data types pertaining to the plant, environment, and management practices. The extensive collection of diverse data derived from genotyping, remote sensing/imaging, “envirotyping,” and precision farming presents a challenge for data management and utilization. Strategies for managing and utilizing diverse data types as they pertain to two on-going initiatives to exploit G×E×M will be presented. First, we have partnered with the New York Corn and Soybean Growers Association to collect high resolution soil, topographical, and harvest data from participating growers across the State of New York to optimize planting density and hybrid selection. Second, we are working with the International Maize and Wheat Improvement Center to integrate aerial imaging into multi-environment breeding schemes. Effective approaches to integrate data types from a range of sources will be required to fully exploit G×E×M interactions.