Genomics-driven breeding for local adaptation of durum wheat is enhanced by farmers’ traditional knowledge

Cherinet Alem Gesesse, Bogale Nigir, Kauê de Sousa, Luca Gianfranceschi, Guido Roberto Gallo, Jesse Poland, Yosef Gebrehawaryat Kidane, Ermias Abate Desta, Carlo Fadda, Mario Enrico Pè, Matteo Dell’Acqua

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


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.
Original languageEnglish (US)
JournalProceedings of the National Academy of Sciences
Issue number14
StatePublished - Mar 27 2023

Bibliographical note

KAUST Repository Item: Exported on 2023-03-30
Acknowledgements: We thank Dejene Kassahun Mengistu and Mulugeta Tilahun for their contribution in the development of the EtNAM and in the coordination of the fieldwork. We are grateful to Mercy Macharia Wairimu and Leonardo Caproni for the useful discussions. We thank the farmers who took part in the participatory evaluation of the EtNAM. In Adet: Balew Dessie, Tewachew Alebachew, Sintayehu Hunegnaw, Atalaye Demle, Abraraw Balew, Nitsuh Geremew, Abebu Geremew, Sindu Hunegnaw, Yezebalem Kassa, Alima Emiyu. In Geregera: Admasu Yigizaw, Getie Adane, Mulat Yigzaw, Adino Tesfaw, Birhan Alemu, Eset Tesifaw, Asnaku Gizaw, Bizuayehu Yigizaw, Tsegaye Birku, Emaway Admasu. In Kulumsa: Eshetu Muger, Tekolla Tamiru, Solomon Agonafir, Ashete Bekele, Mohammed Lenjiso, Helen Tesfaye, Demekech Shimels, Mulu Gebi, Etenesh Melese, Merima Aman.

ASJC Scopus subject areas

  • General


Dive into the research topics of 'Genomics-driven breeding for local adaptation of durum wheat is enhanced by farmers’ traditional knowledge'. Together they form a unique fingerprint.

Cite this