Cotton vegetation indices under diffentent control methods of ramularia leaf spot

Detalhes bibliográficos
Autor(a) principal: Martins, Luiz Marcel
Data de Publicação: 2018
Outros Autores: Neiro, Everton da Silva, Dias, Alfredo Ricere, Roque, Cassiano Garcia, Rojo Baio, Fabio Henrique, Teodoro, Paulo Eduardo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Bioscience journal (Online)
Texto Completo: https://seer.ufu.br/index.php/biosciencejournal/article/view/39975
Resumo: This work aimed to correlate treatments using fungicides to different vegetation indices in response to effects caused by ramularia leaf spot (Ramularia areola). The experiment was carried out in the municipality of Chapadão do Sul, state of Mato Grosso do Sul, in the harvest 2016/2017, and consisted of a randomized blocks design, with 17 treatments and four replications. Data were obtained from the Sequoia 4.0 passive sensor and the Green Seeker LT 200 active sensor. From the information recorded by the sensors, nine vegetation indices were generated and compared with the area under the curve of disease progression, plant height, yield, and agronomic efficiency, in 17 different treatments of fungicide products. Treatments responded differently to the product applied. The SAVI index (Soil Adjusted Vegetation Index), obtained from the band in the red spectral range, presented higher correlation to AACPD, agronomic efficiency, and yield. The NDVI index (Normalized Difference Vegetation Index) had a higher correlation to plant height and SR (simple ratio), both using the wavelength in the red spectral range.
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spelling Cotton vegetation indices under diffentent control methods of ramularia leaf spot Indices de vegetação no algodoeiro sob diferentes fungicidas de controle da mancha da ramuláriaGossypium hirsutum L.Cotton diseasesRemote sensingMultispectral sensorsBiological SciencesThis work aimed to correlate treatments using fungicides to different vegetation indices in response to effects caused by ramularia leaf spot (Ramularia areola). The experiment was carried out in the municipality of Chapadão do Sul, state of Mato Grosso do Sul, in the harvest 2016/2017, and consisted of a randomized blocks design, with 17 treatments and four replications. Data were obtained from the Sequoia 4.0 passive sensor and the Green Seeker LT 200 active sensor. From the information recorded by the sensors, nine vegetation indices were generated and compared with the area under the curve of disease progression, plant height, yield, and agronomic efficiency, in 17 different treatments of fungicide products. Treatments responded differently to the product applied. The SAVI index (Soil Adjusted Vegetation Index), obtained from the band in the red spectral range, presented higher correlation to AACPD, agronomic efficiency, and yield. The NDVI index (Normalized Difference Vegetation Index) had a higher correlation to plant height and SR (simple ratio), both using the wavelength in the red spectral range.Este trabalho objetivou correlacionar diferentes índices de vegetação em resposta aos efeitos causados pela mancha de ramulária (Ramularia areola) de vários tratamentos com produtos fungicidas. O experimento foiimplantado no município de Chapadão do Sul, Estado de Mato Grosso do Sul, no ano agrícola 2016/2017. O delineamento experimental utilizado foi blocos casualizados com 17 tratamentos com quatro repetições. Foram obtidos dados a partir do sensor passivo Sequoia 4.0 e do sensor ativo Green Seeker LT 200. A partir das informações registradas pelos sensores, foram gerados nove índices de vegetação, que foram comparados com a área abaixo da curva de progresso da doença, altura de plantas, produtividade e eficiência agronômica em 17 diferentes tratamentos de produtos de ação fungicida. Os tratamentos responderam de forma distinta em relação ao produto neles aplicados, sendo que os índices SAVI (SoilAdjusted Vegetation Index), obtidos a partir da banda na faixa espectral do Red, apresentaram maior correlação com AACPD, eficiência e produtividade. Já o índice NDVI (Normalized Difference Vegetation Index) obteve maior correlação com a altura de plantas e SR (Simple Ratio), ambos utilizando o comprimento de onda na faixa espectral da banda Red.EDUFU2018-12-14info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://seer.ufu.br/index.php/biosciencejournal/article/view/3997510.14393/BJ-v34n6a2018-39975Bioscience Journal ; Vol. 34 No. 6 (2018): Nov./Dec.; 1706-1713Bioscience Journal ; v. 34 n. 6 (2018): Nov./Dec.; 1706-17131981-3163reponame:Bioscience journal (Online)instname:Universidade Federal de Uberlândia (UFU)instacron:UFUenghttps://seer.ufu.br/index.php/biosciencejournal/article/view/39975/24852Brazil; ContemporaryCopyright (c) 2018 Luiz Marcel Martins, Everton da Silva Neiro, Alfredo Ricere Dias, Cassiano Garcia Roque, Fabio Henrique Rojo Baio, Paulo Eduardo Teodorohttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessMartins, Luiz MarcelNeiro, Everton da SilvaDias, Alfredo RicereRoque, Cassiano GarciaRojo Baio, Fabio HenriqueTeodoro, Paulo Eduardo2022-02-08T01:18:08Zoai:ojs.www.seer.ufu.br:article/39975Revistahttps://seer.ufu.br/index.php/biosciencejournalPUBhttps://seer.ufu.br/index.php/biosciencejournal/oaibiosciencej@ufu.br||1981-31631516-3725opendoar:2022-02-08T01:18:08Bioscience journal (Online) - Universidade Federal de Uberlândia (UFU)false
dc.title.none.fl_str_mv Cotton vegetation indices under diffentent control methods of ramularia leaf spot
Indices de vegetação no algodoeiro sob diferentes fungicidas de controle da mancha da ramulária
title Cotton vegetation indices under diffentent control methods of ramularia leaf spot
spellingShingle Cotton vegetation indices under diffentent control methods of ramularia leaf spot
Martins, Luiz Marcel
Gossypium hirsutum L.
Cotton diseases
Remote sensing
Multispectral sensors
Biological Sciences
title_short Cotton vegetation indices under diffentent control methods of ramularia leaf spot
title_full Cotton vegetation indices under diffentent control methods of ramularia leaf spot
title_fullStr Cotton vegetation indices under diffentent control methods of ramularia leaf spot
title_full_unstemmed Cotton vegetation indices under diffentent control methods of ramularia leaf spot
title_sort Cotton vegetation indices under diffentent control methods of ramularia leaf spot
author Martins, Luiz Marcel
author_facet Martins, Luiz Marcel
Neiro, Everton da Silva
Dias, Alfredo Ricere
Roque, Cassiano Garcia
Rojo Baio, Fabio Henrique
Teodoro, Paulo Eduardo
author_role author
author2 Neiro, Everton da Silva
Dias, Alfredo Ricere
Roque, Cassiano Garcia
Rojo Baio, Fabio Henrique
Teodoro, Paulo Eduardo
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Martins, Luiz Marcel
Neiro, Everton da Silva
Dias, Alfredo Ricere
Roque, Cassiano Garcia
Rojo Baio, Fabio Henrique
Teodoro, Paulo Eduardo
dc.subject.por.fl_str_mv Gossypium hirsutum L.
Cotton diseases
Remote sensing
Multispectral sensors
Biological Sciences
topic Gossypium hirsutum L.
Cotton diseases
Remote sensing
Multispectral sensors
Biological Sciences
description This work aimed to correlate treatments using fungicides to different vegetation indices in response to effects caused by ramularia leaf spot (Ramularia areola). The experiment was carried out in the municipality of Chapadão do Sul, state of Mato Grosso do Sul, in the harvest 2016/2017, and consisted of a randomized blocks design, with 17 treatments and four replications. Data were obtained from the Sequoia 4.0 passive sensor and the Green Seeker LT 200 active sensor. From the information recorded by the sensors, nine vegetation indices were generated and compared with the area under the curve of disease progression, plant height, yield, and agronomic efficiency, in 17 different treatments of fungicide products. Treatments responded differently to the product applied. The SAVI index (Soil Adjusted Vegetation Index), obtained from the band in the red spectral range, presented higher correlation to AACPD, agronomic efficiency, and yield. The NDVI index (Normalized Difference Vegetation Index) had a higher correlation to plant height and SR (simple ratio), both using the wavelength in the red spectral range.
publishDate 2018
dc.date.none.fl_str_mv 2018-12-14
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://seer.ufu.br/index.php/biosciencejournal/article/view/39975
10.14393/BJ-v34n6a2018-39975
url https://seer.ufu.br/index.php/biosciencejournal/article/view/39975
identifier_str_mv 10.14393/BJ-v34n6a2018-39975
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://seer.ufu.br/index.php/biosciencejournal/article/view/39975/24852
dc.rights.driver.fl_str_mv https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.coverage.none.fl_str_mv Brazil; Contemporary
dc.publisher.none.fl_str_mv EDUFU
publisher.none.fl_str_mv EDUFU
dc.source.none.fl_str_mv Bioscience Journal ; Vol. 34 No. 6 (2018): Nov./Dec.; 1706-1713
Bioscience Journal ; v. 34 n. 6 (2018): Nov./Dec.; 1706-1713
1981-3163
reponame:Bioscience journal (Online)
instname:Universidade Federal de Uberlândia (UFU)
instacron:UFU
instname_str Universidade Federal de Uberlândia (UFU)
instacron_str UFU
institution UFU
reponame_str Bioscience journal (Online)
collection Bioscience journal (Online)
repository.name.fl_str_mv Bioscience journal (Online) - Universidade Federal de Uberlândia (UFU)
repository.mail.fl_str_mv biosciencej@ufu.br||
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