KAUST DepartmentEnvironmental Science and Engineering Program
Water Desalination and Reuse Research Center (WDRC)
Biological and Environmental Sciences and Engineering (BESE) Division
Desert Agriculture Initiative
Permanent link to this recordhttp://hdl.handle.net/10754/668582
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AbstractThe convergence of autonomous platforms for field-based phenotyping with advances in machine learning for big data analytics and rapid sequencing for genome description herald the promise of new insights and discoveries in the plant sciences. Han et al. (2021) leverage these emerging tools to navigate the challenging path from field-based mapping of phenotypic features to identifying specific genetic loci in the laboratory: in this case, loci responsible for regulating daily flowering time in lettuce. While their contribution neatly illustrates these exciting technological developments, it also highlights the work that remains to bridge these multidisciplinary fields to more fully deliver upon the promise of digital agriculture.
CitationMcCabe, M. F., & Tester, M. (2021). Digital insights: bridging the phenotype-to-genotype divide. Journal of Experimental Botany, 72(8), 2807–2810. doi:10.1093/jxb/erab108
SponsorsProf. M.F.M and M.T. are funded by the King Abdullah University of Science and Technology.
PublisherOxford University Press (OUP)
JournalJournal of Experimental Botany
Except where otherwise noted, this item's license is described as © The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Experimental Biology.