Summary The Ethiopian plateau hosts thousands of durum wheat ( Triticum turgidum subsp. durum ) farmer varieties ( FV ) with high adaptability and breeding potential. To harness their unique allelic diversity, we produced a large nested association mapping ( NAM ) population intercrossing fifty Ethiopian FV s with an international elite durum wheat variety (Asassa). The Ethiopian NAM population (Et NAM ) is composed of fifty interconnected bi‐parental families, totalling 6280 recombinant inbred lines ( RIL s) that represent both a powerful quantitative trait loci ( QTL ) mapping tool, and a large pre‐breeding panel. Here, we discuss the molecular and phenotypic diversity of the Et NAM founder lines, then we use an array featuring 13 000 single nucleotide polymorphisms ( SNP s) to characterize a subset of 1200 Et NAM RIL s from 12 families. Finally, we test the usefulness of the population by mapping phenology traits and plant height using a genome wide association ( GWA ) approach. Et NAM RIL s showed high allelic variation and a genetic makeup combining genetic diversity from Ethiopian FV s with the international durum wheat allele pool. Et NAM SNP data were projected on the fully sequenced AB genome of wild emmer wheat, and were used to estimate pairwise linkage disequilibrium ( LD ) measures that reported an LD decay distance of 7.4 Mb on average, and balanced founder contributions across Et NAM families. GWA analyses identified 11 genomic loci individually affecting up to 3 days in flowering time and more than 1.6 cm in height. We argue that the Et NAM is a powerful tool to support the production of new durum wheat varieties targeting local and global agriculture.

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In the smallholder, low-input farming systems widespread in sub-Saharan Africa, farmers select and propagate crop varieties based on their traditional knowledge and experience. A data-driven integration of their knowledge into breeding pipelines may support the sustainable intensification of local farming. Here, we combine genomics with participatory research to tap into traditional knowledge in smallholder farming systems, using durum wheat ( Triticum durum Desf.) in Ethiopia as a case study. We developed and genotyped a large multiparental population, called the Ethiopian NAM (EtNAM), that recombines an elite international breeding line with Ethiopian traditional varieties maintained by local farmers. A total of 1,200 EtNAM lines were evaluated for agronomic performance and farmers’ appreciation in three locations in Ethiopia, finding that women and men farmers could skillfully identify the worth of wheat genotypes and their potential for local adaptation. We then trained a genomic selection (GS) model using farmer appreciation scores and found that its prediction accuracy over grain yield (GY) was higher than that of a benchmark GS model trained on GY. Finally, we used forward genetics approaches to identify marker–trait associations for agronomic traits and farmer appreciation scores. We produced genetic maps for individual EtNAM families and used them to support the characterization of genomic loci of breeding relevance with pleiotropic effects on phenology, yield, and farmer preference. Our data show that farmers’ traditional knowledge can be integrated in genomics-driven breeding to support the selection of best allelic combinations for local adaptation.