Field crop phenomics enabling breeding for radiation use efficiency and biomass in cereal crops

Field crop phenomics : enabling breeding for radiation use efficiency and biomass in cereal crops

© 2019 The Authors. New Phytologist © 2019 New Phytologist Trust.

Bibliographische Detailangaben
Veröffentlicht in:The New phytologist. - 1979. - 223(2019), 4 vom: 01. Sept., Seite 1714-1727
1. Verfasser: Furbank, Robert T (VerfasserIn)
Weitere Verfasser: Jimenez-Berni, Jose A, George-Jaeggli, Barbara, Potgieter, Andries B, Deery, David M
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2019
Zugriff auf das übergeordnete Werk:The New phytologist
Schlagworte:Journal Article Research Support, Non-U.S. Gov't Review big data canopy temperature crop breeding crop physiology photosynthesis sorghum stomatal conductance wheat
Beschreibung
Zusammenfassung:© 2019 The Authors. New Phytologist © 2019 New Phytologist Trust.
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
Beschreibung:Date Completed 27.02.2020
Date Revised 30.09.2020
published: Print-Electronic
Citation Status MEDLINE
ISSN:1469-8137
DOI:10.1111/nph.15817