Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize

[Background] Recent developments in unmanned aerial platforms (UAP) have provided research opportunities in assessing land allocation and crop physiological traits, including response to abiotic and biotic stresses. UAP-based remote sensing can be used to rapidly and cost-effectively phenotype large...

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Detalles Bibliográficos
Autores: Zaman-Allah, Mainassara, Zarco-Tejada, Pablo J., Hornero, Alberto, Cairns, Jill E.
Tipo de recurso: artículo
Fecha de publicación:2015
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/125557
Acceso en línea:http://hdl.handle.net/10261/125557
Access Level:acceso abierto
Palabra clave:Maize
Phenotyping platform
Remote sensing
UAP
Nitrogen fertilization
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spelling Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maizeZaman-Allah, MainassaraZarco-Tejada, Pablo J.Hornero, AlbertoCairns, Jill E.MaizePhenotyping platformRemote sensingUAPNitrogen fertilization[Background] Recent developments in unmanned aerial platforms (UAP) have provided research opportunities in assessing land allocation and crop physiological traits, including response to abiotic and biotic stresses. UAP-based remote sensing can be used to rapidly and cost-effectively phenotype large numbers of plots and field trials in a dynamic way using time series. This is anticipated to have tremendous implications for progress in crop genetic improvement.[Results] We present the use of a UAP equipped with sensors for multispectral imaging in spatial field variability assessment and phenotyping for low-nitrogen (low-N) stress tolerance in maize. Multispectral aerial images were used to (1) characterize experimental fields for spatial soil-nitrogen variability and (2) derive indices for crop performance under low-N stress. Overall, results showed that the aerial platform enables to effectively characterize spatial field variation and assess crop performance under low-N stress. The Normalized Difference Vegetation Index (NDVI) data derived from spectral imaging presented a strong correlation with ground-measured NDVI, crop senescence index and grain yield.[Conclusion] This work suggests that the aerial sensing platform designed for phenotyping studies has the potential to effectively assist in crop genetic improvement against abiotic stresses like low-N provided that sensors have enough resolution for plot level data collection. Limitations and future potential uses are also discussed.This work was supported by CRP-Maize Grant from CIMMYT, funding (AGL2012-40053-C03-01 and AGL2013-44147-R.) from the Spanish Ministerio de Economia y Competitividad and the Improved Maize for African Soils (IMAS) project.BioMed CentralCentro Internacional de Mejoramiento de Maíz y Trigo (México)Ministerio de Economía y Competitividad (España)Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2015201520152015info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501http://hdl.handle.net/10261/125557reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#Publisher's versioninfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/AGL2013-44147-Rhttp://dx.doi.org/10.1186/s13007-015-0078-2Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/1255572026-05-22T06:33:51Z
dc.title.none.fl_str_mv Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize
title Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize
spellingShingle Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize
Zaman-Allah, Mainassara
Maize
Phenotyping platform
Remote sensing
UAP
Nitrogen fertilization
title_short Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize
title_full Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize
title_fullStr Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize
title_full_unstemmed Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize
title_sort Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize
dc.creator.none.fl_str_mv Zaman-Allah, Mainassara
Zarco-Tejada, Pablo J.
Hornero, Alberto
Cairns, Jill E.
author Zaman-Allah, Mainassara
author_facet Zaman-Allah, Mainassara
Zarco-Tejada, Pablo J.
Hornero, Alberto
Cairns, Jill E.
author_role author
author2 Zarco-Tejada, Pablo J.
Hornero, Alberto
Cairns, Jill E.
author2_role author
author
author
dc.contributor.none.fl_str_mv Centro Internacional de Mejoramiento de Maíz y Trigo (México)
Ministerio de Economía y Competitividad (España)
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Maize
Phenotyping platform
Remote sensing
UAP
Nitrogen fertilization
topic Maize
Phenotyping platform
Remote sensing
UAP
Nitrogen fertilization
description [Background] Recent developments in unmanned aerial platforms (UAP) have provided research opportunities in assessing land allocation and crop physiological traits, including response to abiotic and biotic stresses. UAP-based remote sensing can be used to rapidly and cost-effectively phenotype large numbers of plots and field trials in a dynamic way using time series. This is anticipated to have tremendous implications for progress in crop genetic improvement.
publishDate 2015
dc.date.none.fl_str_mv 2015
2015
2015
2015
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/125557
url http://hdl.handle.net/10261/125557
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
Publisher's version
info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/AGL2013-44147-R
http://dx.doi.org/10.1186/s13007-015-0078-2
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv BioMed Central
publisher.none.fl_str_mv BioMed Central
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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