Quantifying senescence in bread wheat using multispectral imaging from an unmanned aerial vehicle and QTL mapping

Environmental stresses from climate change can alter source–sink relations during plant maturation, leading to premature senescence and decreased yields. Elucidating the genetic control of natural variations for senescence in wheat (Triticum aestivum) can be accelerated using recent developments in...

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Detalles Bibliográficos
Autores: Hassan, M.A., Mengjiao Yang, Rasheed, A., Xiuling Tian, Reynolds, M.P., Xianchun Xia, Yonggui Xiao, He Zhonghu
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:México
Institución:Centro Internacional de Mejoramiento de Maíz y Trigo
Repositorio:Repositorio Institucional de Publicaciones Multimedia del CIMMYT
OAI Identifier:oai:repository.cimmyt.org:10883/21770
Acceso en línea:https://hdl.handle.net/10883/21770
Access Level:acceso abierto
Palabra clave:AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
SENESCENCE
SOFT WHEAT
MULTISPECTRAL IMAGERY
UNMANNED AERIAL VEHICLES
CHROMOSOME MAPPING
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spelling Quantifying senescence in bread wheat using multispectral imaging from an unmanned aerial vehicle and QTL mappingHassan, M.A.Mengjiao YangRasheed, A.Xiuling TianReynolds, M.P.Xianchun XiaYonggui XiaoHe ZhonghuAGRICULTURAL SCIENCES AND BIOTECHNOLOGYSENESCENCESOFT WHEATMULTISPECTRAL IMAGERYUNMANNED AERIAL VEHICLESCHROMOSOME MAPPINGEnvironmental stresses from climate change can alter source–sink relations during plant maturation, leading to premature senescence and decreased yields. Elucidating the genetic control of natural variations for senescence in wheat (Triticum aestivum) can be accelerated using recent developments in unmanned aerial vehicle (UAV)-based imaging techniques. Here, we describe the use of UAVs to quantify senescence in wheat using vegetative indices (VIs) derived from multispectral images. We detected senescence with high heritability, as well as its impact on grain yield (GY), in a doubled-haploid population and parent cultivars at various growth time points (TPs) after anthesis in the field. Selecting for slow senescence using a combination of different UAV-based VIs was more effective than using a single ground-based vegetation index. We identified 28 quantitative trait loci (QTL) for vegetative growth, senescence, and GY using a 660K single-nucleotide polymorphism array. Seventeen of these new QTL for VIs from UAV-based multispectral imaging were mapped on chromosomes 2B, 3A, 3D, 5A, 5D, 5B, and 6D; these QTL have not been reported previously using conventional phenotyping methods. This integrated approach allowed us to identify an important, previously unreported, senescence-related locus on chromosome 5D that showed high phenotypic variation (up to 18.1%) for all UAV-based VIs at all TPs during grain filling. This QTL was validated for slow senescence by developing kompetitive allele-specific PCR markers in a natural population. Our results suggest that UAV-based high-throughput phenotyping is advantageous for temporal assessment of the genetics underlying for senescence in wheat.2623-2636Oxford University Press2021-12-14T01:20:16Z2021-12-14T01:20:16Z2021Published Versioninfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10883/2177010.1093/plphys/kiab43141870032-0889Plant Physiologyreponame:Repositorio Institucional de Publicaciones Multimedia del CIMMYTinstname:Centro Internacional de Mejoramiento de Maíz y Trigoinstacron:CIMMYTEnglishhttps://academic.oup.com/plphys/article/187/4/2623/6380558#319780621USACIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purposeOpen Accessinfo:eu-repo/semantics/openAccessoai:repository.cimmyt.org:10883/217702024-10-11T19:59:02Z
dc.title.none.fl_str_mv Quantifying senescence in bread wheat using multispectral imaging from an unmanned aerial vehicle and QTL mapping
title Quantifying senescence in bread wheat using multispectral imaging from an unmanned aerial vehicle and QTL mapping
spellingShingle Quantifying senescence in bread wheat using multispectral imaging from an unmanned aerial vehicle and QTL mapping
Hassan, M.A.
AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
SENESCENCE
SOFT WHEAT
MULTISPECTRAL IMAGERY
UNMANNED AERIAL VEHICLES
CHROMOSOME MAPPING
title_short Quantifying senescence in bread wheat using multispectral imaging from an unmanned aerial vehicle and QTL mapping
title_full Quantifying senescence in bread wheat using multispectral imaging from an unmanned aerial vehicle and QTL mapping
title_fullStr Quantifying senescence in bread wheat using multispectral imaging from an unmanned aerial vehicle and QTL mapping
title_full_unstemmed Quantifying senescence in bread wheat using multispectral imaging from an unmanned aerial vehicle and QTL mapping
title_sort Quantifying senescence in bread wheat using multispectral imaging from an unmanned aerial vehicle and QTL mapping
dc.creator.none.fl_str_mv Hassan, M.A.
Mengjiao Yang
Rasheed, A.
Xiuling Tian
Reynolds, M.P.
Xianchun Xia
Yonggui Xiao
He Zhonghu
author Hassan, M.A.
author_facet Hassan, M.A.
Mengjiao Yang
Rasheed, A.
Xiuling Tian
Reynolds, M.P.
Xianchun Xia
Yonggui Xiao
He Zhonghu
author_role author
author2 Mengjiao Yang
Rasheed, A.
Xiuling Tian
Reynolds, M.P.
Xianchun Xia
Yonggui Xiao
He Zhonghu
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
SENESCENCE
SOFT WHEAT
MULTISPECTRAL IMAGERY
UNMANNED AERIAL VEHICLES
CHROMOSOME MAPPING
topic AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
SENESCENCE
SOFT WHEAT
MULTISPECTRAL IMAGERY
UNMANNED AERIAL VEHICLES
CHROMOSOME MAPPING
description Environmental stresses from climate change can alter source–sink relations during plant maturation, leading to premature senescence and decreased yields. Elucidating the genetic control of natural variations for senescence in wheat (Triticum aestivum) can be accelerated using recent developments in unmanned aerial vehicle (UAV)-based imaging techniques. Here, we describe the use of UAVs to quantify senescence in wheat using vegetative indices (VIs) derived from multispectral images. We detected senescence with high heritability, as well as its impact on grain yield (GY), in a doubled-haploid population and parent cultivars at various growth time points (TPs) after anthesis in the field. Selecting for slow senescence using a combination of different UAV-based VIs was more effective than using a single ground-based vegetation index. We identified 28 quantitative trait loci (QTL) for vegetative growth, senescence, and GY using a 660K single-nucleotide polymorphism array. Seventeen of these new QTL for VIs from UAV-based multispectral imaging were mapped on chromosomes 2B, 3A, 3D, 5A, 5D, 5B, and 6D; these QTL have not been reported previously using conventional phenotyping methods. This integrated approach allowed us to identify an important, previously unreported, senescence-related locus on chromosome 5D that showed high phenotypic variation (up to 18.1%) for all UAV-based VIs at all TPs during grain filling. This QTL was validated for slow senescence by developing kompetitive allele-specific PCR markers in a natural population. Our results suggest that UAV-based high-throughput phenotyping is advantageous for temporal assessment of the genetics underlying for senescence in wheat.
publishDate 2021
dc.date.none.fl_str_mv 2021-12-14T01:20:16Z
2021-12-14T01:20:16Z
2021
dc.type.none.fl_str_mv Published Version
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/10883/21770
10.1093/plphys/kiab431
url https://hdl.handle.net/10883/21770
identifier_str_mv 10.1093/plphys/kiab431
dc.language.none.fl_str_mv English
language_invalid_str_mv English
dc.relation.none.fl_str_mv https://academic.oup.com/plphys/article/187/4/2623/6380558#319780621
dc.rights.none.fl_str_mv Open Access
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Open Access
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.coverage.none.fl_str_mv USA
dc.publisher.none.fl_str_mv Oxford University Press
publisher.none.fl_str_mv Oxford University Press
dc.source.none.fl_str_mv 4
187
0032-0889
Plant Physiology
reponame:Repositorio Institucional de Publicaciones Multimedia del CIMMYT
instname:Centro Internacional de Mejoramiento de Maíz y Trigo
instacron:CIMMYT
instname_str Centro Internacional de Mejoramiento de Maíz y Trigo
instacron_str CIMMYT
institution CIMMYT
reponame_str Repositorio Institucional de Publicaciones Multimedia del CIMMYT
collection Repositorio Institucional de Publicaciones Multimedia del CIMMYT
repository.name.fl_str_mv
repository.mail.fl_str_mv
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