High throughput phenotyping to accelerate crop breeding and monitoring of diseases in the field
Abstract
Effective implementation of technology that facilitates accurate and high-throughput screening of thousands of field-grown lines is critical for accelerating crop improvement and breeding strategies for higher yield and disease tolerance. Progress in the development of field-based high throughput phenotyping methods has advanced considerably in the last 10 years through technological progress in sensor development and high-performance computing. In this paper, we review recent advances in high throughput field phenotyping technologies designed to inform the genetics of quantitative traits, including crop yield and disease tolerance. Successful application of phenotyping platforms to advance crop breeding and identify and monitor disease requires: (1) high resolution of imaging and environmental sensors; (2) quality data products that facilitate computer vision, machine learning and GIS; (3) capacity infrastructure for data management and analysis; and (4) automated environmental data collection. Finally, accelerated breeding for agriculturally relevant crop traits is key to the development of improved varieties and is critically dependent on high-resolution, high-throughput field-scale phenotyping technologies that can efficiently discriminate better performing lines within a larger population and across multiple environments.
- Authors:
-
- Donald Danforth Plant Science Center, Creve Coeur, MO (United States)
- Publication Date:
- Research Org.:
- Donald Danforth Plant Science Center, Creve Coeur, MO (United States)
- Sponsoring Org.:
- USDOE Advanced Research Projects Agency - Energy (ARPA-E); USDOE Office of Science (SC), Biological and Environmental Research (BER); Bill & Melinda Gates Foundation (United States)
- OSTI Identifier:
- 1417491
- Alternate Identifier(s):
- OSTI ID: 1549642
- Grant/Contract Number:
- AR0000594; AR0000595; SC0014395; OPP1129063
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Current Opinion in Plant Biology
- Additional Journal Information:
- Journal Volume: 38; Journal ID: ISSN 1369-5266
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 09 BIOMASS FUELS
Citation Formats
Shakoor, Nadia, Lee, Scott, and Mockler, Todd C. High throughput phenotyping to accelerate crop breeding and monitoring of diseases in the field. United States: N. p., 2017.
Web. doi:10.1016/j.pbi.2017.05.006.
Shakoor, Nadia, Lee, Scott, & Mockler, Todd C. High throughput phenotyping to accelerate crop breeding and monitoring of diseases in the field. United States. https://doi.org/10.1016/j.pbi.2017.05.006
Shakoor, Nadia, Lee, Scott, and Mockler, Todd C. Fri .
"High throughput phenotyping to accelerate crop breeding and monitoring of diseases in the field". United States. https://doi.org/10.1016/j.pbi.2017.05.006. https://www.osti.gov/servlets/purl/1417491.
@article{osti_1417491,
title = {High throughput phenotyping to accelerate crop breeding and monitoring of diseases in the field},
author = {Shakoor, Nadia and Lee, Scott and Mockler, Todd C.},
abstractNote = {Effective implementation of technology that facilitates accurate and high-throughput screening of thousands of field-grown lines is critical for accelerating crop improvement and breeding strategies for higher yield and disease tolerance. Progress in the development of field-based high throughput phenotyping methods has advanced considerably in the last 10 years through technological progress in sensor development and high-performance computing. In this paper, we review recent advances in high throughput field phenotyping technologies designed to inform the genetics of quantitative traits, including crop yield and disease tolerance. Successful application of phenotyping platforms to advance crop breeding and identify and monitor disease requires: (1) high resolution of imaging and environmental sensors; (2) quality data products that facilitate computer vision, machine learning and GIS; (3) capacity infrastructure for data management and analysis; and (4) automated environmental data collection. Finally, accelerated breeding for agriculturally relevant crop traits is key to the development of improved varieties and is critically dependent on high-resolution, high-throughput field-scale phenotyping technologies that can efficiently discriminate better performing lines within a larger population and across multiple environments.},
doi = {10.1016/j.pbi.2017.05.006},
journal = {Current Opinion in Plant Biology},
number = ,
volume = 38,
place = {United States},
year = {Fri Jul 21 00:00:00 EDT 2017},
month = {Fri Jul 21 00:00:00 EDT 2017}
}
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