Remote sensing techniques and stable isotopes as phenotyping tools to assess wheat yield performance: effects of growing temperature and vernalization

This study compares distinct phenotypic approaches to assess wheat performance under different growing temperatures and vernalization needs. A set of 38 (winter and facultative) wheat cultivars were planted in Valladolid (Spain) under irrigation and two contrasting planting dates: normal (late autum...

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Autores: Rezzouk, Fatima Zahra, Gracia-Romero, Adrian, Kefauver, Shawn Carlisle, Aparicio, Nieves, Aranjuelo Michelena, Iker, Serret Molins, M. Dolors, Araus Ortega, José Luis
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2019
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/176968
Acceso en línea:https://hdl.handle.net/2445/176968
Access Level:acceso abierto
Palabra clave:Agricultura
Blat
Crops
Conreus
Agriculture
Wheat
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spelling Remote sensing techniques and stable isotopes as phenotyping tools to assess wheat yield performance: effects of growing temperature and vernalizationRezzouk, Fatima ZahraGracia-Romero, AdrianKefauver, Shawn CarlisleAparicio, NievesAranjuelo Michelena, IkerSerret Molins, M. DolorsAraus Ortega, José LuisAgriculturaBlatCropsConreusAgricultureWheatThis study compares distinct phenotypic approaches to assess wheat performance under different growing temperatures and vernalization needs. A set of 38 (winter and facultative) wheat cultivars were planted in Valladolid (Spain) under irrigation and two contrasting planting dates: normal (late autumn), and late (late winter). The late plating trial exhibited a 1.5 °C increase in average crop temperature. Measurements with different remote sensing techniques were performed at heading and grain filling, as well as carbon isotope composition (δ13C) and nitrogen content analysis. Multispectral and RGB vegetation indices and canopy temperature related better to grain yield (GY) across the whole set of genotypes in the normal compared with the late planting, with indices (such as the RGB indices Hue, a* and the spectral indices NDVI, EVI and CCI) measured at grain filling performing the best. Aerially assessed remote sensing indices only performed better than ground-acquired ones at heading. Nitrogen content and δ13C correlated with GY at both planting dates. Correlations within winter and facultative genotypes were much weaker, particularly in the facultative subset. For both planting dates, the best GY prediction models were achieved when combining remote sensing indices with δ13C and nitrogen of mature grains. Implications for phenotyping in the context of increasing temperatures are further discussed.Elsevier B.V.2019info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttps://hdl.handle.net/2445/176968Articles publicats en revistes (Biologia Evolutiva, Ecologia i Ciències Ambientals)reponame:Dipòsit Digital de la UBinstname:Universidad de BarcelonaInglésVersió postprint del document publicat a: https://doi.org/10.1016/j.plantsci.2019.110281Plant Science, 2019, vol. 295, p. 110281https://doi.org/10.1016/j.plantsci.2019.110281cc-by-nc-nd (c) Elsevier B.V., 2019http://creativecommons.org/licenses/by-nc-nd/3.0/esinfo:eu-repo/semantics/openAccessoai:diposit.ub.edu:2445/1769682026-05-27T06:46:51Z
dc.title.none.fl_str_mv Remote sensing techniques and stable isotopes as phenotyping tools to assess wheat yield performance: effects of growing temperature and vernalization
title Remote sensing techniques and stable isotopes as phenotyping tools to assess wheat yield performance: effects of growing temperature and vernalization
spellingShingle Remote sensing techniques and stable isotopes as phenotyping tools to assess wheat yield performance: effects of growing temperature and vernalization
Rezzouk, Fatima Zahra
Agricultura
Blat
Crops
Conreus
Agriculture
Wheat
title_short Remote sensing techniques and stable isotopes as phenotyping tools to assess wheat yield performance: effects of growing temperature and vernalization
title_full Remote sensing techniques and stable isotopes as phenotyping tools to assess wheat yield performance: effects of growing temperature and vernalization
title_fullStr Remote sensing techniques and stable isotopes as phenotyping tools to assess wheat yield performance: effects of growing temperature and vernalization
title_full_unstemmed Remote sensing techniques and stable isotopes as phenotyping tools to assess wheat yield performance: effects of growing temperature and vernalization
title_sort Remote sensing techniques and stable isotopes as phenotyping tools to assess wheat yield performance: effects of growing temperature and vernalization
dc.creator.none.fl_str_mv Rezzouk, Fatima Zahra
Gracia-Romero, Adrian
Kefauver, Shawn Carlisle
Aparicio, Nieves
Aranjuelo Michelena, Iker
Serret Molins, M. Dolors
Araus Ortega, José Luis
author Rezzouk, Fatima Zahra
author_facet Rezzouk, Fatima Zahra
Gracia-Romero, Adrian
Kefauver, Shawn Carlisle
Aparicio, Nieves
Aranjuelo Michelena, Iker
Serret Molins, M. Dolors
Araus Ortega, José Luis
author_role author
author2 Gracia-Romero, Adrian
Kefauver, Shawn Carlisle
Aparicio, Nieves
Aranjuelo Michelena, Iker
Serret Molins, M. Dolors
Araus Ortega, José Luis
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Agricultura
Blat
Crops
Conreus
Agriculture
Wheat
topic Agricultura
Blat
Crops
Conreus
Agriculture
Wheat
description This study compares distinct phenotypic approaches to assess wheat performance under different growing temperatures and vernalization needs. A set of 38 (winter and facultative) wheat cultivars were planted in Valladolid (Spain) under irrigation and two contrasting planting dates: normal (late autumn), and late (late winter). The late plating trial exhibited a 1.5 °C increase in average crop temperature. Measurements with different remote sensing techniques were performed at heading and grain filling, as well as carbon isotope composition (δ13C) and nitrogen content analysis. Multispectral and RGB vegetation indices and canopy temperature related better to grain yield (GY) across the whole set of genotypes in the normal compared with the late planting, with indices (such as the RGB indices Hue, a* and the spectral indices NDVI, EVI and CCI) measured at grain filling performing the best. Aerially assessed remote sensing indices only performed better than ground-acquired ones at heading. Nitrogen content and δ13C correlated with GY at both planting dates. Correlations within winter and facultative genotypes were much weaker, particularly in the facultative subset. For both planting dates, the best GY prediction models were achieved when combining remote sensing indices with δ13C and nitrogen of mature grains. Implications for phenotyping in the context of increasing temperatures are further discussed.
publishDate 2019
dc.date.none.fl_str_mv 2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/176968
url https://hdl.handle.net/2445/176968
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Versió postprint del document publicat a: https://doi.org/10.1016/j.plantsci.2019.110281
Plant Science, 2019, vol. 295, p. 110281
https://doi.org/10.1016/j.plantsci.2019.110281
dc.rights.none.fl_str_mv cc-by-nc-nd (c) Elsevier B.V., 2019
http://creativecommons.org/licenses/by-nc-nd/3.0/es
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc-by-nc-nd (c) Elsevier B.V., 2019
http://creativecommons.org/licenses/by-nc-nd/3.0/es
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier B.V.
publisher.none.fl_str_mv Elsevier B.V.
dc.source.none.fl_str_mv Articles publicats en revistes (Biologia Evolutiva, Ecologia i Ciències Ambientals)
reponame:Dipòsit Digital de la UB
instname:Universidad de Barcelona
instname_str Universidad de Barcelona
reponame_str Dipòsit Digital de la UB
collection Dipòsit Digital de la UB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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