Genotype-Environment Interaction Analysis in Crop Breeding

Genotype-environment interaction (G×E) analysis lies at the heart of modern crop improvement, revealing how genetic variation influences performance across diverse climates, soils and management regimes. By disentangling the relative contributions of genetic main effects, environmental main effects and their interaction, breeders can identify genotypes that combine high yield with stability and specific adaptation. Multivariate approaches such as additive main effects and multiplicative interaction (AMMI) models and genotype and genotype × environment (GGE) biplots provide graphical and statistical tools to partition variation, assess mega-environments and highlight winning genotypes. Recent advances integrate multiple traits, deploying composite indices that account for agronomic, quality and resistance attributes. This integrative strategy accelerates the selection of broadly adapted or environment-specific cultivars and underpins decision-making in pre-breeding, trial site optimisation and the deployment of climate-resilient varieties on a global scale.

Research from Nature Portfolio

Recent studies have demonstrated the value of combining yield with other key traits in the selection process. One investigation introduced a genotype by yield × trait (GYT) biplot that ranks genotypes by simultaneously combining yield with agronomic, quality or resistance objectives; this graphical method allows breeders to visualise strengths and weaknesses across multiple targets without subjective weighting. Another study applied AMMI and GGE biplot analyses to multi-environment trials of Bambara groundnut, revealing that season and location explained the majority of G×E variation and identifying a subset of genotypes that excel in both mean yield and stability across Malaysian environments. These approaches underscore the shift towards visual, objective and multi-trait support tools for genotype selection under heterogeneous conditions.

Research from all publishers

Investigations in sorghum have employed AMMI, GGE biplot and cluster analyses across three Ethiopian sites to quantify the contributions of genotype, environment and G×E to yield and yield components; the work highlighted the need for multi-environment testing, identified high-yielding stable landraces and pinpointed representative and discriminating test sites. In guar, the introduction of Multi-Trait Stability Index (MTSI) and Multi-Trait Genotype-Ideotype Distance Index (MGIDI) enabled breeders to select accessions with favourable gum content, short cycle and seed yield simultaneously across seasons, demonstrating the power of multivariate trait selection. A methodological review of long-term field experiments emphasised transparent reporting, outlier management, inclusion of confounders, detrending and temporal autocorrelation, and offered guidance on choosing and interpreting stability measures, thereby improving comparability and robustness in G×E analyses.

Genotype-Environment Interaction Analysis in Crop Breeding publication trend

The graph below shows the total number of articles in genotype-environment interaction analysis in crop breeding across all publications each year (not limited to Nature Index journals).

Technical terms

Genotype-Environment Interaction (G×E): The differential performance of genotypes across varying environmental conditions, reflecting the non-additive interplay between genetic and environmental effects.

Additive Main Effects and Multiplicative Interaction (AMMI) Model: A statistical method that combines analysis of variance for main effects with principal component analysis of G×E interaction to reveal patterns of stability and adaptation.

Genotype and Genotype × Environment (GGE) Biplot: A graphical tool that displays both genotype main effects and G×E interaction in a two-dimensional plot, facilitating comparison of genotypes and environments.

Multi-Trait Stability Index (MTSI): An index that integrates multiple phenotypic traits to rank genotypes based on both performance and stability across environments.

Multi-Trait Genotype-Ideotype Distance Index (MGIDI): A selection index measuring the distance of each genotype from an ideal combination of trait values, aiding simultaneous multi-trait improvement.

References

1. Genotype by Yield*Trait (GYT) Biplot: a Novel Approach for Genotype Selection based on Multiple Traits. Scientific Reports (2018).
2. AMMI and GGE biplot analysis for yield performance and stability assessment of selected Bambara groundnut (Vigna subterranea L. Verdc.) genotypes under the multi-environmental trials (METs). Scientific Reports (2021).
3. Genotype by environment interaction, correlation, AMMI, GGE biplot and cluster analysis for grain yield and other agronomic traits in sorghum (Sorghum bicolor L. Moench). PLOS ONE (2021).
4. A Framework for Identification of Stable Genotypes Basedon MTSI and MGDII Indexes: An Example in Guar (Cymopsis tetragonoloba L.). Agronomy (2021).
5. Methods of yield stability analysis in long-term field experiments. A review. Agronomy for Sustainable Development (2021).