Vegetation indices in the prediction of biomass and grain yield of white oat under irrigation levels

Detalhes bibliográficos
Autor(a) principal: Coelho, Anderson Prates
Data de Publicação: 2018
Outros Autores: Rosalen, David Luciano, Faria, Rogério Teixeira De
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1590/1983-40632018v4851523
http://hdl.handle.net/11449/158218
Resumo: ABSTRACT Vegetation indices are widely used to indicate the nutritional status of crops, as well as to estimate their harvest yield. However, their accuracy is influenced by the phenological stage of evaluation and the index used. The present study aimed to evaluate the accuracy of the Normalized Difference Vegetation Index (NDVI) and Inverse Ratio Vegetation Index (IRVI) in the prediction of grain yield and biomass of white oat cultivated under irrigation levels, besides indicating the best phenological stage for evaluation. The irrigation levels consisted of 11 %, 31 %, 60 %, 87 % and 100 % of the maximum evapotranspiration, with four replicates. The mean values ​​for NDVI and IRVI were determined using an active terrestrial sensor, at four phenological stages (4, 8, 10 and 10.5.4). The white oat grain yield and biomass may be estimated with a high precision using the NDVI and IRVI. The NDVI was more accurate than the IRVI. The grain yield estimate was more accurate from the flag leaf sheath appearance stage (10), whereas, for the biomass, the best estimate was for the kernel watery ripe stage (10.5.4).
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spelling Vegetation indices in the prediction of biomass and grain yield of white oat under irrigation levelsÍndices de vegetação na predição da produtividade de biomassa e grãos de aveia-branca sob lâminas de irrigaçãoGeotechnologyremote sensingwater stressGeotecnologiasensoriamento remotoestresse hídricoABSTRACT Vegetation indices are widely used to indicate the nutritional status of crops, as well as to estimate their harvest yield. However, their accuracy is influenced by the phenological stage of evaluation and the index used. The present study aimed to evaluate the accuracy of the Normalized Difference Vegetation Index (NDVI) and Inverse Ratio Vegetation Index (IRVI) in the prediction of grain yield and biomass of white oat cultivated under irrigation levels, besides indicating the best phenological stage for evaluation. The irrigation levels consisted of 11 %, 31 %, 60 %, 87 % and 100 % of the maximum evapotranspiration, with four replicates. The mean values ​​for NDVI and IRVI were determined using an active terrestrial sensor, at four phenological stages (4, 8, 10 and 10.5.4). The white oat grain yield and biomass may be estimated with a high precision using the NDVI and IRVI. The NDVI was more accurate than the IRVI. The grain yield estimate was more accurate from the flag leaf sheath appearance stage (10), whereas, for the biomass, the best estimate was for the kernel watery ripe stage (10.5.4).RESUMO Índices de vegetação são muito utilizados para indicar o estado nutricional das culturas, bem como estimar sua produtividade final. No entanto, sua precisão é influenciada pelo estágio fenológico da avaliação e pelo índice utilizado. Objetivou-se avaliar a acurácia do Índice de Vegetação por Diferença Normalizada (IVDN) e do Índice de Vegetação de Proporção Inversa (IVPI), na predição da produtividade de grãos e biomassa de aveia-branca cultivada sob lâminas de irrigação, além de indicar o melhor estádio fenológico para avaliação. As lâminas de irrigação foram de 11 %, 31 %, 60 %, 87 % e 100 % da evapotranspiração máxima, com quatro repetições. Os valores médios de IVDN e IVPI foram determinados utilizando-se um sensor terrestre ativo, em quatro estágios fenológicos (4, 8, 10 e 10.5.4). A produtividade de grãos e biomassa de aveia branca podem ser estimadas com elevada precisão utilizando-se os índices IVDN e IVPI. O IVDN apresentou maior acurácia do que o IVPI. A estimativa da produtividade de grãos resultou em maior acurácia a partir do estádio de aparecimento da bainha da folha bandeira (10), enquanto, para a biomassa, a melhor estimativa foi para o estádio de grão aquoso (10.5.4).Universidade Estadual Paulista Faculdade de Ciências Agrárias e Veterinárias Departamento de Engenharia RuralUniversidade Estadual Paulista Faculdade de Ciências Agrárias e Veterinárias Departamento de Engenharia RuralEscola de Agronomia/UFGUniversidade Estadual Paulista (Unesp)Coelho, Anderson PratesRosalen, David LucianoFaria, Rogério Teixeira De2018-11-12T17:28:52Z2018-11-12T17:28:52Z2018-04-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article109-117application/pdfhttp://dx.doi.org/10.1590/1983-40632018v4851523Pesquisa Agropecuária Tropical. Escola de Agronomia/UFG, v. 48, n. 2, p. 109-117, 2018.1983-4063http://hdl.handle.net/11449/15821810.1590/1983-40632018v4851523S1983-40632018000200109S1983-40632018000200109.pdfSciELOreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengPesquisa Agropecuária Tropical0,346info:eu-repo/semantics/openAccess2024-06-06T15:18:29Zoai:repositorio.unesp.br:11449/158218Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T18:28:19.885830Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Vegetation indices in the prediction of biomass and grain yield of white oat under irrigation levels
Índices de vegetação na predição da produtividade de biomassa e grãos de aveia-branca sob lâminas de irrigação
title Vegetation indices in the prediction of biomass and grain yield of white oat under irrigation levels
spellingShingle Vegetation indices in the prediction of biomass and grain yield of white oat under irrigation levels
Coelho, Anderson Prates
Geotechnology
remote sensing
water stress
Geotecnologia
sensoriamento remoto
estresse hídrico
title_short Vegetation indices in the prediction of biomass and grain yield of white oat under irrigation levels
title_full Vegetation indices in the prediction of biomass and grain yield of white oat under irrigation levels
title_fullStr Vegetation indices in the prediction of biomass and grain yield of white oat under irrigation levels
title_full_unstemmed Vegetation indices in the prediction of biomass and grain yield of white oat under irrigation levels
title_sort Vegetation indices in the prediction of biomass and grain yield of white oat under irrigation levels
author Coelho, Anderson Prates
author_facet Coelho, Anderson Prates
Rosalen, David Luciano
Faria, Rogério Teixeira De
author_role author
author2 Rosalen, David Luciano
Faria, Rogério Teixeira De
author2_role author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Coelho, Anderson Prates
Rosalen, David Luciano
Faria, Rogério Teixeira De
dc.subject.por.fl_str_mv Geotechnology
remote sensing
water stress
Geotecnologia
sensoriamento remoto
estresse hídrico
topic Geotechnology
remote sensing
water stress
Geotecnologia
sensoriamento remoto
estresse hídrico
description ABSTRACT Vegetation indices are widely used to indicate the nutritional status of crops, as well as to estimate their harvest yield. However, their accuracy is influenced by the phenological stage of evaluation and the index used. The present study aimed to evaluate the accuracy of the Normalized Difference Vegetation Index (NDVI) and Inverse Ratio Vegetation Index (IRVI) in the prediction of grain yield and biomass of white oat cultivated under irrigation levels, besides indicating the best phenological stage for evaluation. The irrigation levels consisted of 11 %, 31 %, 60 %, 87 % and 100 % of the maximum evapotranspiration, with four replicates. The mean values ​​for NDVI and IRVI were determined using an active terrestrial sensor, at four phenological stages (4, 8, 10 and 10.5.4). The white oat grain yield and biomass may be estimated with a high precision using the NDVI and IRVI. The NDVI was more accurate than the IRVI. The grain yield estimate was more accurate from the flag leaf sheath appearance stage (10), whereas, for the biomass, the best estimate was for the kernel watery ripe stage (10.5.4).
publishDate 2018
dc.date.none.fl_str_mv 2018-11-12T17:28:52Z
2018-11-12T17:28:52Z
2018-04-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1590/1983-40632018v4851523
Pesquisa Agropecuária Tropical. Escola de Agronomia/UFG, v. 48, n. 2, p. 109-117, 2018.
1983-4063
http://hdl.handle.net/11449/158218
10.1590/1983-40632018v4851523
S1983-40632018000200109
S1983-40632018000200109.pdf
url http://dx.doi.org/10.1590/1983-40632018v4851523
http://hdl.handle.net/11449/158218
identifier_str_mv Pesquisa Agropecuária Tropical. Escola de Agronomia/UFG, v. 48, n. 2, p. 109-117, 2018.
1983-4063
10.1590/1983-40632018v4851523
S1983-40632018000200109
S1983-40632018000200109.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Pesquisa Agropecuária Tropical
0,346
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 109-117
application/pdf
dc.publisher.none.fl_str_mv Escola de Agronomia/UFG
publisher.none.fl_str_mv Escola de Agronomia/UFG
dc.source.none.fl_str_mv SciELO
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1808128937170042880

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