Accelerated Breeding for Pearl Millet in Senegal Case Study

• Cereal: Pearl Millet
• Abiotic Stressor: Drought and Heat
• Principal Investigator: Modou Mbaye, Senegalese Institute of Agricultural Research (ISRA-CERAAS)

Improving how pearl millet performs under heat and drought requires better tools to guide breeding decisions in variable environments. Current rates of genetic gain in millet remain low, limiting progress in developing germplasm adapted to stress-prone production systems. This effort addresses that gap by providing breeders with methods to quantify performance constraints, prioritize key traits, and accelerate selection.

The project integrates three complementary approaches: Breeding Gap Analysis (BGA) to define the difference between current and attainable productivity, Trait Profiling Assessment (TPA) to identify trait combinations needed to close those gaps, and Crop Growth Model–Genomic Selection (CGM-GS) to predict performance and guide selection decisions. These tools will be applied to the Senegalese pearl millet core collection, supported by targeted field experiments that generate high-quality phenotypic data and improve model calibration. Crop modeling will be combined with genomic data to evaluate trait performance across environments and strengthen predictive accuracy.

Key outputs include calibrated crop models, trait prioritization frameworks, genomic prediction tools, and integrated phenotypic and genotypic datasets that support data-driven breeding decisions. These resources will be implemented within national breeding program in Senegal, enabling continued use and adaptation. In parallel, the project builds capacity in crop growth modeling, genomic selection, and data integration, supporting sustained application of these tools to advance allele discovery, validation, and selection in millet breeding programs.