Digital insights: bridging the phenotype-to-genotype divide

Matthew F McCabe; Mark Tester

doi:10.1093/jxb/erab108

Digital insights: bridging the phenotype-to-genotype divide

J Exp Bot. 2021 Apr 2;72(8):2807-2810. doi: 10.1093/jxb/erab108.

Authors

Matthew F McCabe¹, Mark Tester²

Affiliations

¹ Hydrology, Agriculture and Land Observation (HALO) Laboratory, Water Desalination and Reuse Center, Division of Biological and Environmental Sciences and Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
² Center for Desert Agriculture, Division of Biological and Environmental Sciences and Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.

Abstract

This article comments on:

Han R, Wong AJY, Tang Z, Truco MJ, Lavelle DO, Kozik A, Jin Y, Michelmore R. 2021. Drone phenotyping and machine learning enable discovery of loci regulating daily floral opening in lettuce. Journal of Experimental Botany 72,2979–2994.

Keywords: Digital agriculture; drones; genome-wide association studies; genotype; machine learning; phenotype; remote sensing; unmanned aerial vehicles.

Publication types

Research Support, Non-U.S. Gov't
Comment

MeSH terms

Genotype
Lactuca*
Machine Learning
Phenotype
Remote Sensing Technology*