Envirotyping to drive spring barley adaptation in Northwestern Europe

Context

Cereal crops are highly vulnerable to extreme climatic events. Due to the restricted genetic diversity within the existing elite germplasm used in modern breeding, developing high-yielding and stable cultivars in the context of climate change requires deciphering genotype x environment interactions (GEI), commonly observed in multi-environment trials (METs).

Objectives

Our study on two-row spring barley, an economically important short-cycle crop, aimed to (i) highlight the main environmental covariates (EC) – climatic variables calculated over phenological stages – driving GEI for yield, and (ii) characterize genotypes’ adaptation across the European spring malting barley production area.

Methods

Using data from 112 elite genotypes across 121 environments (from 2015 to 2022), 91 EC were calculated for each environment using the calibrated CERES-Barley model and analyzed for their contribution to GEI. An environmental classification was conducted on the main GEI-drivers across 1450 environments, including tested and untested locations, within the production area.

Results

Elevated temperatures during barley stem elongation, as well as solar radiation intensity and water accessibility during grain filling, were identified as the major GEI-drivers. Thermal amplitude around anthesis also emerged as an influential factor. The analysis discriminated three environment types (ET) across the European Target Population of Environments (TPE), distributed according to clear spatial and repeatability variations. They contrasted mainly in terms of temperatures during vegetative growth, solar radiation intensity, and water availability during grain filling. Specific (suited to one ET) or broad adaptation (multi-ET) were identified for the tested genotypes, offering valuable information for characterizing germplasm performance and optimizing selection criteria.

Conclusion

We showed how controlling GEI-drivers through envirotyping enhanced year-to-year field trial predictability, selection intensity, and yield genetic gain and stability. Further advancements will need to integrate the genetic sensitivity to GEI-drivers into genomic selection methods to improve accuracy in modern cereal breeding.