Spectral reflectance for growth and yield assessment of irrigated cotton.
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
Texto Completo: | http://www.alice.cnptia.embrapa.br/alice/handle/doc/1041649 |
Resumo: | The canopy reflectance using ground-based sensors has the potential to provide information on crop nitrogen content. The objective of this study was to determine relationships between canopy spectral reflectance and leaf N content, leaf area index (LAI), aboveground biomass (Biom) and yield of irrigated cotton under four nitrogen rates (0, 90, 180 and 270kg ha-1). Measurements of canopy reflectance were made throughout the growing seasons (2009-2010) using a hand-held spectroradiometer. Samples for LAI and Biom were obtained three times from squaring until fruiting. The normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), modified soil adjusted vegetation index (MSAVI) and the modified transformed vegetation index (MTVI2) were calculated from the hyperspectral reflectance data. All vegetation indexes (VIs) and also SPAD-502 readings allowed to figure out mathematical models for N content prediction in cotton leaves with great precision (r > 0.74). It also showed good correlations (r from 0.55 to 0.96) with the LAI since the first flowering. The vegetation indexes obtained through the canopy reflectance, explained more than 64% of the variation in cotton biomass. The MTVI2 was the index that provided the best LAI prediction in advanced stages. The peak flowering stage was the best time to estimate the cotton biomass, where the MSAVI and MTVI2 showed to be excellent predictors. The results indicate that the cotton yield can be estimated through the hyperspectral reflectance since the squaring until fruiting in irrigated conditions. |
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Spectral reflectance for growth and yield assessment of irrigated cotton.Irrigated cottonNitrogen fertilizationGossypium hirsutumAlgodãoÁrea foliarleaf area indexremote sensingThe canopy reflectance using ground-based sensors has the potential to provide information on crop nitrogen content. The objective of this study was to determine relationships between canopy spectral reflectance and leaf N content, leaf area index (LAI), aboveground biomass (Biom) and yield of irrigated cotton under four nitrogen rates (0, 90, 180 and 270kg ha-1). Measurements of canopy reflectance were made throughout the growing seasons (2009-2010) using a hand-held spectroradiometer. Samples for LAI and Biom were obtained three times from squaring until fruiting. The normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), modified soil adjusted vegetation index (MSAVI) and the modified transformed vegetation index (MTVI2) were calculated from the hyperspectral reflectance data. All vegetation indexes (VIs) and also SPAD-502 readings allowed to figure out mathematical models for N content prediction in cotton leaves with great precision (r > 0.74). It also showed good correlations (r from 0.55 to 0.96) with the LAI since the first flowering. The vegetation indexes obtained through the canopy reflectance, explained more than 64% of the variation in cotton biomass. The MTVI2 was the index that provided the best LAI prediction in advanced stages. The peak flowering stage was the best time to estimate the cotton biomass, where the MSAVI and MTVI2 showed to be excellent predictors. The results indicate that the cotton yield can be estimated through the hyperspectral reflectance since the squaring until fruiting in irrigated conditions.ZIANY NEIVA BRANDAO, CNPA; VALDINEI SOFIATTI, CNPA; JOSE RENATO CORTEZ BEZERRA, CNPA; GILVAN BARBOSA FERREIRA, CNPA; JOSÉ C. MEDEIROS, CNPA.BRANDAO, Z. N.SOFIATTI, V.BEZERRA, J. R. C.FERREIRA, G. B.MEDEIROS, J. C.2016-03-22T11:11:11Z2016-03-22T11:11:11Z2016-03-2220152016-03-22T11:11:11Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleAustralian Journal of Crop Science, v. 9, n. 1, p. 75-84, jan. 2015.1835-2693http://www.alice.cnptia.embrapa.br/alice/handle/doc/1041649porinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2017-08-16T03:17:53Zoai:www.alice.cnptia.embrapa.br:doc/1041649Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542017-08-16T03:17:53falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542017-08-16T03:17:53Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Spectral reflectance for growth and yield assessment of irrigated cotton. |
title |
Spectral reflectance for growth and yield assessment of irrigated cotton. |
spellingShingle |
Spectral reflectance for growth and yield assessment of irrigated cotton. BRANDAO, Z. N. Irrigated cotton Nitrogen fertilization Gossypium hirsutum Algodão Área foliar leaf area index remote sensing |
title_short |
Spectral reflectance for growth and yield assessment of irrigated cotton. |
title_full |
Spectral reflectance for growth and yield assessment of irrigated cotton. |
title_fullStr |
Spectral reflectance for growth and yield assessment of irrigated cotton. |
title_full_unstemmed |
Spectral reflectance for growth and yield assessment of irrigated cotton. |
title_sort |
Spectral reflectance for growth and yield assessment of irrigated cotton. |
author |
BRANDAO, Z. N. |
author_facet |
BRANDAO, Z. N. SOFIATTI, V. BEZERRA, J. R. C. FERREIRA, G. B. MEDEIROS, J. C. |
author_role |
author |
author2 |
SOFIATTI, V. BEZERRA, J. R. C. FERREIRA, G. B. MEDEIROS, J. C. |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
ZIANY NEIVA BRANDAO, CNPA; VALDINEI SOFIATTI, CNPA; JOSE RENATO CORTEZ BEZERRA, CNPA; GILVAN BARBOSA FERREIRA, CNPA; JOSÉ C. MEDEIROS, CNPA. |
dc.contributor.author.fl_str_mv |
BRANDAO, Z. N. SOFIATTI, V. BEZERRA, J. R. C. FERREIRA, G. B. MEDEIROS, J. C. |
dc.subject.por.fl_str_mv |
Irrigated cotton Nitrogen fertilization Gossypium hirsutum Algodão Área foliar leaf area index remote sensing |
topic |
Irrigated cotton Nitrogen fertilization Gossypium hirsutum Algodão Área foliar leaf area index remote sensing |
description |
The canopy reflectance using ground-based sensors has the potential to provide information on crop nitrogen content. The objective of this study was to determine relationships between canopy spectral reflectance and leaf N content, leaf area index (LAI), aboveground biomass (Biom) and yield of irrigated cotton under four nitrogen rates (0, 90, 180 and 270kg ha-1). Measurements of canopy reflectance were made throughout the growing seasons (2009-2010) using a hand-held spectroradiometer. Samples for LAI and Biom were obtained three times from squaring until fruiting. The normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), modified soil adjusted vegetation index (MSAVI) and the modified transformed vegetation index (MTVI2) were calculated from the hyperspectral reflectance data. All vegetation indexes (VIs) and also SPAD-502 readings allowed to figure out mathematical models for N content prediction in cotton leaves with great precision (r > 0.74). It also showed good correlations (r from 0.55 to 0.96) with the LAI since the first flowering. The vegetation indexes obtained through the canopy reflectance, explained more than 64% of the variation in cotton biomass. The MTVI2 was the index that provided the best LAI prediction in advanced stages. The peak flowering stage was the best time to estimate the cotton biomass, where the MSAVI and MTVI2 showed to be excellent predictors. The results indicate that the cotton yield can be estimated through the hyperspectral reflectance since the squaring until fruiting in irrigated conditions. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015 2016-03-22T11:11:11Z 2016-03-22T11:11:11Z 2016-03-22 2016-03-22T11:11:11Z |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
Australian Journal of Crop Science, v. 9, n. 1, p. 75-84, jan. 2015. 1835-2693 http://www.alice.cnptia.embrapa.br/alice/handle/doc/1041649 |
identifier_str_mv |
Australian Journal of Crop Science, v. 9, n. 1, p. 75-84, jan. 2015. 1835-2693 |
url |
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1041649 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
collection |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
repository.name.fl_str_mv |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
cg-riaa@embrapa.br |
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1794503420130885632 |