Skip to main content
ARS Home » Northeast Area » Washington, D.C. » National Arboretum » Floral and Nursery Plants Research » Research » Publications at this Location » Publication #401587
Research Project: Germplasm Development for Reduced Input Turf Management Systems

Location: Floral and Nursery Plants Research

Title: Harnessing Genebanks: High-throughput phenotyping and genotyping of crop wild relatives and landraces

Author
item CORTES, ANDRES - Columbian Agricultural Research Corporation
item Barnaby, Jinyoung

Submitted to: Frontiers in Plant Science
Publication Type: Review Article
Publication Acceptance Date: 1/26/2023
Publication Date: 3/10/2023
Citation: Cortes, A.J., Barnaby, J.Y. 2023. Harnessing Genebanks: High-throughput phenotyping and genotyping of crop wild relatives and landraces. Frontiers in Plant Science. 14:1149469. https://doi.org/10.3389/fpls.2023.1149469.
DOI: https://doi.org/10.3389/fpls.2023.1149469

Interpretive Summary: Like they did for the green revolution last century, worldwide genebanks can confer phenotypic and genetic novelty useful to increase yield and crop adaptability. However, new strategies for genebank utilization must be empowered to meet the increasing global food demand. This review article compiles major recent ‘big data’ developments that are likely to enhance the identification, conservation, and use of crop genetic resources for the development of better-adapted crop varieties.

Technical Abstract: Crop wild relatives and landraces harbor unique variations that may prove useful for climate change adaptation. Yet, their factual utilization has been hampered by poor characterizations, incompatibilities and polygenic variance. This editorial review includes the topics of (1) unlocking phenotypic and genetic variation hidden in crop wild relatives and landraces, (2) major challenges to utilize crop wild relatives and landraces to improve complex polygenic adaptive traits, (3) modern experimental (e.g. speed breeding, de novo domestication, genome editing) and analytical (e.g. predictive breeding, genomic selection, machine learning) approaches that could speed up the utilization of wild relatives and landraces within conservation and breeding programs, (4) novel approaches to merge pre- and breeding efforts towards the increase of crop adaptability and yield, (5) strategies to match future global food demands in the face of increased abiotic and biotic stresses, and (6) data compilation, ‘big data’, and database management targeting crop wild relatives and landraces.