Growth indices ans productivity in sugarcane

Detalhes bibliográficos
Autor(a) principal: Simões,Maurício dos Santos
Data de Publicação: 2005
Outros Autores: Rocha,Jansle Vieira, Lamparelli,Rubens Augusto Camargo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Scientia Agrícola (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162005000100005
Resumo: A knowledge about the temporal development of agronomic variables in sugarcane is a very important aspect for the development of crop yield prediction models using remote sensing, and further studies are still needed. This paper describes the temporal evolution of sugarcane biophysical parameters, such as total biomass, leaf area index, number of plants per meter, and productivity. During two seasons, a commercial field in Araras/SP, planted with variety SP80-1842, on the 4th and 5th cuts, was monitored on eight different dates, and data were obtained for 2 m of sugarcane in three crop rows at 18 sampling points. Linear and multiple regression analyses were used to study growth analysis and to correlate agronomic variables (leaf area index and number of plants per meter) with biomass and productivity. Gompertz model, a sigmoidal curve, was the best adjustment curve for total biomass and yield in relation to days after cutting (r² = 0.8987 and r² = 0.9682, respectively); number of plants and leaf area index showed best fit with a cubic exponential model and a quadratic exponential model, respectively. Total biomass and cane productivity were well correlated with LAI in the first two stages of the sugarcane cycle using linear regression. At the end of the cycle, total biomass and cane productivity were more related to number of plants, and lower r² values than in other stages were obtained by the models.
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spelling Growth indices ans productivity in sugarcanebiomassleaf area indexcrop temporal evolutionA knowledge about the temporal development of agronomic variables in sugarcane is a very important aspect for the development of crop yield prediction models using remote sensing, and further studies are still needed. This paper describes the temporal evolution of sugarcane biophysical parameters, such as total biomass, leaf area index, number of plants per meter, and productivity. During two seasons, a commercial field in Araras/SP, planted with variety SP80-1842, on the 4th and 5th cuts, was monitored on eight different dates, and data were obtained for 2 m of sugarcane in three crop rows at 18 sampling points. Linear and multiple regression analyses were used to study growth analysis and to correlate agronomic variables (leaf area index and number of plants per meter) with biomass and productivity. Gompertz model, a sigmoidal curve, was the best adjustment curve for total biomass and yield in relation to days after cutting (r² = 0.8987 and r² = 0.9682, respectively); number of plants and leaf area index showed best fit with a cubic exponential model and a quadratic exponential model, respectively. Total biomass and cane productivity were well correlated with LAI in the first two stages of the sugarcane cycle using linear regression. At the end of the cycle, total biomass and cane productivity were more related to number of plants, and lower r² values than in other stages were obtained by the models.Escola Superior de Agricultura "Luiz de Queiroz"2005-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162005000100005Scientia Agricola v.62 n.1 2005reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USP10.1590/S0103-90162005000100005info:eu-repo/semantics/openAccessSimões,Maurício dos SantosRocha,Jansle VieiraLamparelli,Rubens Augusto Camargoeng2005-02-23T00:00:00Zoai:scielo:S0103-90162005000100005Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2005-02-23T00:00Scientia Agrícola (Online) - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Growth indices ans productivity in sugarcane
title Growth indices ans productivity in sugarcane
spellingShingle Growth indices ans productivity in sugarcane
Simões,Maurício dos Santos
biomass
leaf area index
crop temporal evolution
title_short Growth indices ans productivity in sugarcane
title_full Growth indices ans productivity in sugarcane
title_fullStr Growth indices ans productivity in sugarcane
title_full_unstemmed Growth indices ans productivity in sugarcane
title_sort Growth indices ans productivity in sugarcane
author Simões,Maurício dos Santos
author_facet Simões,Maurício dos Santos
Rocha,Jansle Vieira
Lamparelli,Rubens Augusto Camargo
author_role author
author2 Rocha,Jansle Vieira
Lamparelli,Rubens Augusto Camargo
author2_role author
author
dc.contributor.author.fl_str_mv Simões,Maurício dos Santos
Rocha,Jansle Vieira
Lamparelli,Rubens Augusto Camargo
dc.subject.por.fl_str_mv biomass
leaf area index
crop temporal evolution
topic biomass
leaf area index
crop temporal evolution
description A knowledge about the temporal development of agronomic variables in sugarcane is a very important aspect for the development of crop yield prediction models using remote sensing, and further studies are still needed. This paper describes the temporal evolution of sugarcane biophysical parameters, such as total biomass, leaf area index, number of plants per meter, and productivity. During two seasons, a commercial field in Araras/SP, planted with variety SP80-1842, on the 4th and 5th cuts, was monitored on eight different dates, and data were obtained for 2 m of sugarcane in three crop rows at 18 sampling points. Linear and multiple regression analyses were used to study growth analysis and to correlate agronomic variables (leaf area index and number of plants per meter) with biomass and productivity. Gompertz model, a sigmoidal curve, was the best adjustment curve for total biomass and yield in relation to days after cutting (r² = 0.8987 and r² = 0.9682, respectively); number of plants and leaf area index showed best fit with a cubic exponential model and a quadratic exponential model, respectively. Total biomass and cane productivity were well correlated with LAI in the first two stages of the sugarcane cycle using linear regression. At the end of the cycle, total biomass and cane productivity were more related to number of plants, and lower r² values than in other stages were obtained by the models.
publishDate 2005
dc.date.none.fl_str_mv 2005-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162005000100005
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0103-90162005000100005
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Escola Superior de Agricultura "Luiz de Queiroz"
publisher.none.fl_str_mv Escola Superior de Agricultura "Luiz de Queiroz"
dc.source.none.fl_str_mv Scientia Agricola v.62 n.1 2005
reponame:Scientia Agrícola (Online)
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Scientia Agrícola (Online)
collection Scientia Agrícola (Online)
repository.name.fl_str_mv Scientia Agrícola (Online) - Universidade de São Paulo (USP)
repository.mail.fl_str_mv scientia@usp.br||alleoni@usp.br
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