Harnessing Enviromics: A Review of Environmental Data Integration for Crop Improvement
Himasree P. S. *
Department of Genetics and Plant Breeding, College of Agriculture, Vellayani, Kerala Agricultural University, India.
Beena Thomas
Department of Genetics and Plant Breeding, College of Agriculture, Vellayani, Kerala Agricultural University, India.
*Author to whom correspondence should be addressed.
Abstract
Heterogeneity of current environmental conditions and global climatic change constantly complicate the task for breeders in defining the Target Population of Environments (TPE). Moreover, the differential response of genotypes across variable environments, referred as Genotype by Environment (G × E) interaction, presents a major challenge that almost all breeding initiatives must tackle. Conventional G × E studies have primarily concentrated on estimating genetic parameters across a restricted set of experimental trials. To optimize genetic gains, it is essential to gather data on all measurable environmental factors that influence genotype performance at any specific location. The relationships between environmental variables and genotype expression can be harnessed using the modern approach known as “enviromics”, which improves precision breeding by integrating genotypic and environmental data. Enviromics refers to the characterization of micro and macro-environments based on large-scale environmental datasets. This approach utilizes Geographic Information System (GIS) as a geospatial tool to advance genetic improvement by predicting the phenotypic performance of untested genotypes through the application of “enviromic markers”. These markers are crucial for genetic research due to their cost-effectiveness, increasing availability and applicability across various species GIS offers a comprehensive view of geographical locations and aids in analysing how environmental factors impact genotypic performance, highlighting the importance of enviromics in delivering information at an omics scale. This approach offers multiple benefits like matching of genotypes to their ideal environments, enhanced zoning of breeding regions with strong genetic correlations and the identification of the most suitable sites for conducting experiments.
Keywords: Enviromics, enviromic markers, G × E interaction, target population of environments, geographic information system