European Journal of Sustainable Agroecosystems

Background: Sorghum (Sorghum bicolor (L.) Moench) is a staple for more than half a billion people across the semi-arid tropics and is increasingly promoted as a climate-resilient cereal. However, grain yield is strongly modulated by genotype × environment (G×E) interaction, which biases selection and complicates the recommendation of stable, broadly adapted cultivars under intensifying climate variability.
Objective: This review synthesises the methodological landscape and empirical evidence on G×E interaction and yield-stability analysis in sorghum, and evaluates how emerging enviromic and genomic tools are reshaping the pursuit of climate resilience.
Method: Peer-reviewed literature (2015–2025) was retrieved from Scopus, Web of Science, PubMed and Google Scholar, supplemented by FAO and international-organisation reports, and screened using a PRISMA-style protocol yielding 34 core studies.
Result: Across multi-environment trials, the environment typically dominates the treatment sum of squares, yet G×E interaction frequently exceeds the genotype main effect, confirming that single-site selection is unreliable. Additive main effects and multiplicative interaction (AMMI) and genotype-plus-genotype-by-environment (GGE) biplot models remain the analytical mainstays, increasingly complemented by mixed-model WAASB indices that jointly optimise performance and stability. Physiological and genomic evidence links stay-green QTLs (Stg1–Stg4), transpiration-efficiency traits and heat-shock loci to buffered yield, while envirotyping and enviromic-assisted genomic prediction improve performance forecasts in untested environments.
Research gaps: Enviromic data remain under-exploited, crop-growth models are weakly coupled to statistical stability frameworks, multi-year testing is sparse, and farmer-preferred traits are rarely weighted in stability indices.
Conclusion: Integrating mixed-model stability analytics with envirotyping, high-throughput phenotyping and genomic prediction offers the most credible route to delivering stable, climate-resilient sorghum cultivars, but demands standardised reporting, open multi-environment datasets and evaluation under realistic deployment scenarios.