Combined use of low-cost remote sensing techniques and C to assess bread wheat grain yield under different water and nitrogen conditions

Vegetation indices and canopy temperature are the most usual remote sensing approaches to assess cereal performance. Understanding the relationships of these parameters and yield may help design more efficient strategies to monitor crop performance. We present an evaluation of vegetation indices (de...

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Autores: Yousfi, Salima, Gracia-Romero, Adrian, Kellas, Nassim, Kaddour, Mohamed, Chadouli, Aahmed, Karrou, Mmohamed, Araus Ortega, José Luis, Serret Molins, M. Dolors
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/151855
Acceso en línea:https://hdl.handle.net/2445/151855
Access Level:acceso abierto
Palabra clave:Blat
Genètica vegetal
Wheat
Plant genetics
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spelling Combined use of low-cost remote sensing techniques and C to assess bread wheat grain yield under different water and nitrogen conditionsYousfi, SalimaGracia-Romero, AdrianKellas, NassimKaddour, MohamedChadouli, AahmedKarrou, MmohamedAraus Ortega, José LuisSerret Molins, M. DolorsBlatGenètica vegetalWheatPlant geneticsVegetation indices and canopy temperature are the most usual remote sensing approaches to assess cereal performance. Understanding the relationships of these parameters and yield may help design more efficient strategies to monitor crop performance. We present an evaluation of vegetation indices (derived from RGB images and multispectral data) and water status traits (through the canopy temperature, stomatal conductance and carbon isotopic composition) measured during the reproductive stage for genotype phenotyping in a study of four wheat genotypes growing under different water and nitrogen regimes in north Algeria. Differences among the cultivars were reported through the vegetation indices, but not with the water status traits. Both approximations correlated significantly with grain yield (GY), reporting stronger correlations under support irrigation and N-fertilization than the rainfed or the no N-fertilization conditions. For N-fertilized trials (irrigated or rainfed) water status parameters were the main factors predicting relative GY performance, while in the absence of N-fertilization, the green canopy area (assessed through GGA) was the main factor negatively correlated with GY. Regression models for GY estimation were generated using data from three consecutive growing seasons. The results highlighted the usefulness of vegetation indices derived from RGB images predicting GY.MDPI2020202020192020info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion23 p.application/pdfhttps://hdl.handle.net/2445/151855Articles publicats en revistes (Biologia Evolutiva, Ecologia i Ciències Ambientals)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésReproducció del document publicat a: https://doi.org/10.3390/agronomy9060285Agronomy, 2019, vol. 9, num. 6, p. 285https://doi.org/10.3390/agronomy9060285cc-by (c) Yousfi, Salima et al., 2019http://creativecommons.org/licenses/by/3.0/esinfo:eu-repo/semantics/openAccessoai:recercat.cat:2445/1518552026-05-29T05:05:01Z
dc.title.none.fl_str_mv Combined use of low-cost remote sensing techniques and C to assess bread wheat grain yield under different water and nitrogen conditions
title Combined use of low-cost remote sensing techniques and C to assess bread wheat grain yield under different water and nitrogen conditions
spellingShingle Combined use of low-cost remote sensing techniques and C to assess bread wheat grain yield under different water and nitrogen conditions
Yousfi, Salima
Blat
Genètica vegetal
Wheat
Plant genetics
title_short Combined use of low-cost remote sensing techniques and C to assess bread wheat grain yield under different water and nitrogen conditions
title_full Combined use of low-cost remote sensing techniques and C to assess bread wheat grain yield under different water and nitrogen conditions
title_fullStr Combined use of low-cost remote sensing techniques and C to assess bread wheat grain yield under different water and nitrogen conditions
title_full_unstemmed Combined use of low-cost remote sensing techniques and C to assess bread wheat grain yield under different water and nitrogen conditions
title_sort Combined use of low-cost remote sensing techniques and C to assess bread wheat grain yield under different water and nitrogen conditions
dc.creator.none.fl_str_mv Yousfi, Salima
Gracia-Romero, Adrian
Kellas, Nassim
Kaddour, Mohamed
Chadouli, Aahmed
Karrou, Mmohamed
Araus Ortega, José Luis
Serret Molins, M. Dolors
author Yousfi, Salima
author_facet Yousfi, Salima
Gracia-Romero, Adrian
Kellas, Nassim
Kaddour, Mohamed
Chadouli, Aahmed
Karrou, Mmohamed
Araus Ortega, José Luis
Serret Molins, M. Dolors
author_role author
author2 Gracia-Romero, Adrian
Kellas, Nassim
Kaddour, Mohamed
Chadouli, Aahmed
Karrou, Mmohamed
Araus Ortega, José Luis
Serret Molins, M. Dolors
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Blat
Genètica vegetal
Wheat
Plant genetics
topic Blat
Genètica vegetal
Wheat
Plant genetics
description Vegetation indices and canopy temperature are the most usual remote sensing approaches to assess cereal performance. Understanding the relationships of these parameters and yield may help design more efficient strategies to monitor crop performance. We present an evaluation of vegetation indices (derived from RGB images and multispectral data) and water status traits (through the canopy temperature, stomatal conductance and carbon isotopic composition) measured during the reproductive stage for genotype phenotyping in a study of four wheat genotypes growing under different water and nitrogen regimes in north Algeria. Differences among the cultivars were reported through the vegetation indices, but not with the water status traits. Both approximations correlated significantly with grain yield (GY), reporting stronger correlations under support irrigation and N-fertilization than the rainfed or the no N-fertilization conditions. For N-fertilized trials (irrigated or rainfed) water status parameters were the main factors predicting relative GY performance, while in the absence of N-fertilization, the green canopy area (assessed through GGA) was the main factor negatively correlated with GY. Regression models for GY estimation were generated using data from three consecutive growing seasons. The results highlighted the usefulness of vegetation indices derived from RGB images predicting GY.
publishDate 2019
dc.date.none.fl_str_mv 2019
2020
2020
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/151855
url https://hdl.handle.net/2445/151855
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.3390/agronomy9060285
Agronomy, 2019, vol. 9, num. 6, p. 285
https://doi.org/10.3390/agronomy9060285
dc.rights.none.fl_str_mv cc-by (c) Yousfi, Salima et al., 2019
http://creativecommons.org/licenses/by/3.0/es
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc-by (c) Yousfi, Salima et al., 2019
http://creativecommons.org/licenses/by/3.0/es
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 23 p.
application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv Articles publicats en revistes (Biologia Evolutiva, Ecologia i Ciències Ambientals)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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