Communications Biology (Aug 2021)

Data-driven decentralized breeding increases prediction accuracy in a challenging crop production environment

  • Kauê de Sousa,
  • Jacob van Etten,
  • Jesse Poland,
  • Carlo Fadda,
  • Jean-Luc Jannink,
  • Yosef Gebrehawaryat Kidane,
  • Basazen Fantahun Lakew,
  • Dejene Kassahun Mengistu,
  • Mario Enrico Pè,
  • Svein Øivind Solberg,
  • Matteo Dell’Acqua

DOI
https://doi.org/10.1038/s42003-021-02463-w
Journal volume & issue
Vol. 4, no. 1
pp. 1 – 9

Abstract

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de Sousa et al. present a data-driven decentralized crop breeding approach called 3D-breeding that is geared toward improving yields for smallholder farmers. 3D-breeding is applied to a case study of durum wheat in Ethiopia, which demonstrates higher prediction accuracies for grain yield than the existing model.