Vegetation indices in the prediction of biomass and grain yield of white oat under irrigation levels
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Pesquisa Agropecuária Tropical (Online) |
Texto Completo: | https://revistas.ufg.br/pat/article/view/51523 |
Resumo: | 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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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 da aveia-branca sob lâminas de irrigaçãoGeotechnologyremote sensingwater stress.GeotecnologiaSensoriamento remotoEstresse hídricoVegetation 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).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).Escola de Agronomia - Universidade Federal de Goiás2018-06-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionAvaliado por paresapplication/pdfhttps://revistas.ufg.br/pat/article/view/51523Pesquisa Agropecuária Tropical [Agricultural Research in the Tropics]; v. 48, n. 2, Apr./Jun. 2018; 109-117Pesquisa Agropecuária Tropical (Agricultural Research in the Tropics); v. 48, n. 2, abr./jun. 2018; 109-117Pesquisa Agropecuária Tropical; v. 48, n. 2, abr./jun. 2018; 109-1171983-4063reponame:Pesquisa Agropecuária Tropical (Online)instname:Universidade Federal de Goiás (UFG)instacron:UFGenghttps://revistas.ufg.br/pat/article/view/51523/25659Copyright (c) 2018 Pesquisa Agropecuária Tropical (Agricultural Research in the Tropics)info:eu-repo/semantics/openAccessPrates Coelho, AndersonLuciano Rosalen, DavidTeixeira de Faria, Rogério2020-07-13T19:04:21Zoai:ojs.revistas.ufg.br:article/51523Revistahttps://revistas.ufg.br/patPUBhttps://revistas.ufg.br/pat/oaiaseleguini.pat@gmail.com||mgoes@agro.ufg.br1983-40631517-6398opendoar:2024-05-21T19:56:19.744273Pesquisa Agropecuária Tropical (Online) - Universidade Federal de Goiás (UFG)true |
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 da 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 Prates Coelho, Anderson 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 |
Prates Coelho, Anderson |
author_facet |
Prates Coelho, Anderson Luciano Rosalen, David Teixeira de Faria, Rogério |
author_role |
author |
author2 |
Luciano Rosalen, David Teixeira de Faria, Rogério |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Prates Coelho, Anderson Luciano Rosalen, David Teixeira de Faria, Rogério |
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 |
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 |
2018-06-07 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Avaliado por pares |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://revistas.ufg.br/pat/article/view/51523 |
url |
https://revistas.ufg.br/pat/article/view/51523 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://revistas.ufg.br/pat/article/view/51523/25659 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2018 Pesquisa Agropecuária Tropical (Agricultural Research in the Tropics) info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2018 Pesquisa Agropecuária Tropical (Agricultural Research in the Tropics) |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Escola de Agronomia - Universidade Federal de Goiás |
publisher.none.fl_str_mv |
Escola de Agronomia - Universidade Federal de Goiás |
dc.source.none.fl_str_mv |
Pesquisa Agropecuária Tropical [Agricultural Research in the Tropics]; v. 48, n. 2, Apr./Jun. 2018; 109-117 Pesquisa Agropecuária Tropical (Agricultural Research in the Tropics); v. 48, n. 2, abr./jun. 2018; 109-117 Pesquisa Agropecuária Tropical; v. 48, n. 2, abr./jun. 2018; 109-117 1983-4063 reponame:Pesquisa Agropecuária Tropical (Online) instname:Universidade Federal de Goiás (UFG) instacron:UFG |
instname_str |
Universidade Federal de Goiás (UFG) |
instacron_str |
UFG |
institution |
UFG |
reponame_str |
Pesquisa Agropecuária Tropical (Online) |
collection |
Pesquisa Agropecuária Tropical (Online) |
repository.name.fl_str_mv |
Pesquisa Agropecuária Tropical (Online) - Universidade Federal de Goiás (UFG) |
repository.mail.fl_str_mv |
aseleguini.pat@gmail.com||mgoes@agro.ufg.br |
_version_ |
1799874819921018880 |