Enviromics in breeding: applications and perspectives on envirotypic-assisted selection

Area of Science:

• Plant breeding
• Genetics
• Environmental science

Background:

• Genotype by environment interaction (GEI) studies traditionally use limited experimental trials.
• Geographic Information System (GIS) techniques offer new ways to understand and manage GEI.
• Accurate prediction of genotype performance across all sites, including un-tested ones, is crucial.

Purpose of the Study:

• Introduce "enviromics" and "envirotypic-assisted breeding" framework.
• Develop and illustrate an index-based enviromics method (GIS-GEI) for improved breeding decisions.
• Enhance selection accuracy and optimize experimental site selection.

Main Methods:

• Applied enviromics on an "omics" scale of environmental attributes.
• Utilized Geographic Information System (GIS) techniques.
• Developed an index-based enviromics method (GIS-GEI) using simulated data.

Main Results:

• The GIS-GEI method provides higher granular resolution than standard methods.
• Accurate matching of sites to appropriate genotypes.
• Better definition of breeding areas with high genetic correlation for selection gains.
• Efficient determination of optimal experimental sites.

Conclusions:

• Enviromics enables prediction of unobserved genotype performances by assessing site similarity on an "omics" scale.
• Envirotyping provides inexpensive, transferable markers for genetic studies.
• Enviromics integration with advanced genotyping/phenotyping and statistical modeling promises a future for plant breeding, especially for climate change adaptation.