Heterotic Grouping Strategies for Enhancing Hybrid Performance in Maize

Abstract

Maize hybrid breeding rests on the deliberate exploitation of heterosis, the superior performance of an F1 hybrid relative to its inbred parents. Central to this enterprise is the organisation of breeding germplasm into heterotic groups, pools of related genotypes chosen so that crosses between groups consistently outperform crosses within groups. Over the past decade the methods used to define, refine and deploy heterotic groups have shifted substantially, moving from pedigree records and phenotypic combining-ability trials towards genome-wide marker platforms, doubled haploid technology and genomic prediction. This review synthesises recent peer-reviewed literature on heterotic grouping strategies in maize, covering the genetic basis of heterosis, classical and molecular approaches to group classification, population improvement methods such as reciprocal recurrent selection, and the growing role of genomic selection in predicting hybrid performance across heterotic pools. Particular attention is given to regional case studies from sub-Saharan Africa and China, where breeding programmes have had to reconcile historical pedigree-based groupings with genomic evidence of divergence. The review finds that no single classification method is universally superior; combining-ability data remain the most direct predictor of hybrid performance, but molecular markers offer scalability and consistency that phenotypic trials cannot match on their own. Doubled haploid technology and genomic selection are converging to accelerate the cycle of heterotic pool improvement, although questions remain about the transferability of prediction models across germplasm and environments. The review concludes that heterotic grouping is best treated as an iterative, evidence-updated process rather than a fixed classification, and it identifies priority areas for further research, including the integration of multi-omics data and the management of genetic diversity within increasingly narrow elite pools.