Field crop phenomics: enabling breeding for radiation use efficiency and biomass in cereal crops
Citations Over TimeTop 1% of 2019 papers
Abstract
Plant phenotyping forms the core of crop breeding, allowing breeders to build on physiological traits and mechanistic science to inform their selection of material for crossing and genetic gain. Recent rapid progress in high-throughput techniques based on machine vision, robotics, and computing (plant phenomics) enables crop physiologists and breeders to quantitatively measure complex and previously intractable traits. By combining these techniques with affordable genomic sequencing and genotyping, machine learning, and genome selection approaches, breeders have an opportunity to make rapid genetic progress. This review focuses on how field-based plant phenomics can enable next-generation physiological breeding in cereal crops for traits related to radiation use efficiency, photosynthesis, and crop biomass. These traits have previously been regarded as difficult and laborious to measure but have recently become a focus as cereal breeders find genetic progress from 'Green Revolution' traits such as harvest index become exhausted. Application of LiDAR, thermal imaging, leaf and canopy spectral reflectance, Chl fluorescence, and machine learning are discussed using wheat and sorghum phenotyping as case studies. A vision of how crop genomics and high-throughput phenotyping could enable the next generation of crop research and breeding is presented.
Related Papers
- → Prospectus of Genomic Selection and Phenomics in Cereal, Legume and Oilseed Breeding Programs(2022)51 cited
- → Plant Genomics(2016)18 cited
- → Efficient Breeding of Crop Plants(2022)7 cited
- Fruit crop research marches into the era of post-genomics and systems biology-the case of grapevine(2011)
- Next generation phenotyping for quantitative analyses of key productivity traits of crops: challenges and opportunities for plant phenomics and plant breeding, from controlled environments to the field.(2015)