Balancing Short‐Term Genetic Gain and Long‐Term Diversity: Haplotype‐Based Breeding Strategies for Yield Improvement in Chickpea

ABSTRACT Chickpea ( Cicer arietinum L.) is one of the most important grain legumes and provides a major source of protein, vitamins and minerals worldwide. Despite decades of traditional breeding delivering significant genetic gains in disease resistance and adaptation, seed yield improvement has advanced only incrementally, constrained by the highly polygenic nature of the trait, pronounced genotype‐by‐environment interactions and insufficient utilisation of existing genetic diversity. This review elucidates the genetic architecture of seed yield in chickpea by integrating comprehensive QTL/association mapping across diverse populations and environments. Haplotype‐based breeding emerges as a promising strategy, leveraging linkage disequilibrium (LD) defined blocks to capture multiallelic QTL variation and beneficial alleles associated with target traits of interest. Crucially, layering multitrait information onto these haploblocks enables breeders to classify traits according to their concurrent effects on yield across the target environment, prioritising those that are yield‐enhancing and avoiding those that are yield‐reducing. We outline the operational framework: haplotype genomic selection using local genomic estimated breeding values (local GEBVs) to prioritise chromosome segments over whole‐genome truncation selection; and artificial intelligence (AI)–driven parent selection to identify complementary parental combinations from diverse populations to make progress towards an ‘ultimate genotype’ that will stack superior haplotypes for targeted traits. By integrating multitrait correlations, haplotype‐resolved QTL maps and computational optimisation, this strategy targets potential yield ideotypes while preserving adaptive diversity and minimising linkage drag, promising to break the current yield plateau and accelerate genetic gain in seed yield beyond the historical rate of up to 0.6% per year. The framework provides a blueprint for haplotype‐based breeding approaches across crops confronting polygenic yield barriers under climate‐constrained production.