Exploring phenotypic space for mining genotypes and alleles in maize
Abstract
Crop species rely on genetic and phenotypic diversity to adapt to various environments. Genotypes respond differently, resulting in genotype-by-environment interactions (GxE). Recent advances in phenomics and modeling allow for the prediction of GxE for traits related to sustainability and productivity. However, a phenotype-centered framework that effectively navigates the interplay between genetics, physiology, and the environment is needed. Here we present maize data from phenotyping platforms and field experiments and explore strategies to integrate concepts and techniques from ecophysiology, ecology, and math to: (i) define and describe phenotypic space across spatial, temporal, and biological scales; (ii) identify unique phenotypic combinations and constraints; and (iii) identify territories of the phenotypic space representing favorable adaptations for crop improvement. Our findings demonstrate the value of phenotype-focused perspectives for adapting crops to climate change.