Physiological model to estimate the maturity of sugarcane
Autor(a) principal: | |
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Data de Publicação: | 2009 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Scientia Agrícola (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162009000500006 |
Resumo: | Sugarcane (Saccharum spp.) grows in different weather and management conditions which directly affect crop maturation. These conditions lead to the necessity of quantifying crop response to different stimuli for planning purposes. Forecast models for the quality of raw material are important tools in sugarcane farming, especially the forecast curve of sucrose accumulation in shoots. The goal of these models is to supply yield estimates during the crop cycle, aiming to characterize alternatives and to increase the efficacy for management and strategic decisions. The objective of this project was to develop empiric models capable of obtaining estimates of total recoverable sugar (TRS), for the varieties RB72454, SP81-3250 and SP80-1842 during the crop cycle, using reference data as the production factors. Sugarcane harvest results obtained in Piracicaba, State of São Paulo, Brazil were analyzed using the following parameters: maturation, stand age, type of soil, variety, flowering and management for the crops in the years 1998/99, 1999/00, 2000/01, 2001/02 and 2002/03. Models developed for these years were used to estimate TRS from the 2003/04 cropping season. All the forecast models for ratoon crops were significant indicating that they are an excellent tool to optimize agricultural planning. |
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Physiological model to estimate the maturity of sugarcaneclimatologycrop modelsproductivityregressionsucroseSugarcane (Saccharum spp.) grows in different weather and management conditions which directly affect crop maturation. These conditions lead to the necessity of quantifying crop response to different stimuli for planning purposes. Forecast models for the quality of raw material are important tools in sugarcane farming, especially the forecast curve of sucrose accumulation in shoots. The goal of these models is to supply yield estimates during the crop cycle, aiming to characterize alternatives and to increase the efficacy for management and strategic decisions. The objective of this project was to develop empiric models capable of obtaining estimates of total recoverable sugar (TRS), for the varieties RB72454, SP81-3250 and SP80-1842 during the crop cycle, using reference data as the production factors. Sugarcane harvest results obtained in Piracicaba, State of São Paulo, Brazil were analyzed using the following parameters: maturation, stand age, type of soil, variety, flowering and management for the crops in the years 1998/99, 1999/00, 2000/01, 2001/02 and 2002/03. Models developed for these years were used to estimate TRS from the 2003/04 cropping season. All the forecast models for ratoon crops were significant indicating that they are an excellent tool to optimize agricultural planning.Escola Superior de Agricultura "Luiz de Queiroz"2009-10-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162009000500006Scientia Agricola v.66 n.5 2009reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USP10.1590/S0103-90162009000500006info:eu-repo/semantics/openAccessScarpari,Maximiliano SallesBeauclair,Edgar Gomes Ferreira deeng2009-10-05T00:00:00Zoai:scielo:S0103-90162009000500006Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2009-10-05T00:00Scientia Agrícola (Online) - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Physiological model to estimate the maturity of sugarcane |
title |
Physiological model to estimate the maturity of sugarcane |
spellingShingle |
Physiological model to estimate the maturity of sugarcane Scarpari,Maximiliano Salles climatology crop models productivity regression sucrose |
title_short |
Physiological model to estimate the maturity of sugarcane |
title_full |
Physiological model to estimate the maturity of sugarcane |
title_fullStr |
Physiological model to estimate the maturity of sugarcane |
title_full_unstemmed |
Physiological model to estimate the maturity of sugarcane |
title_sort |
Physiological model to estimate the maturity of sugarcane |
author |
Scarpari,Maximiliano Salles |
author_facet |
Scarpari,Maximiliano Salles Beauclair,Edgar Gomes Ferreira de |
author_role |
author |
author2 |
Beauclair,Edgar Gomes Ferreira de |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Scarpari,Maximiliano Salles Beauclair,Edgar Gomes Ferreira de |
dc.subject.por.fl_str_mv |
climatology crop models productivity regression sucrose |
topic |
climatology crop models productivity regression sucrose |
description |
Sugarcane (Saccharum spp.) grows in different weather and management conditions which directly affect crop maturation. These conditions lead to the necessity of quantifying crop response to different stimuli for planning purposes. Forecast models for the quality of raw material are important tools in sugarcane farming, especially the forecast curve of sucrose accumulation in shoots. The goal of these models is to supply yield estimates during the crop cycle, aiming to characterize alternatives and to increase the efficacy for management and strategic decisions. The objective of this project was to develop empiric models capable of obtaining estimates of total recoverable sugar (TRS), for the varieties RB72454, SP81-3250 and SP80-1842 during the crop cycle, using reference data as the production factors. Sugarcane harvest results obtained in Piracicaba, State of São Paulo, Brazil were analyzed using the following parameters: maturation, stand age, type of soil, variety, flowering and management for the crops in the years 1998/99, 1999/00, 2000/01, 2001/02 and 2002/03. Models developed for these years were used to estimate TRS from the 2003/04 cropping season. All the forecast models for ratoon crops were significant indicating that they are an excellent tool to optimize agricultural planning. |
publishDate |
2009 |
dc.date.none.fl_str_mv |
2009-10-01 |
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=S0103-90162009000500006 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162009000500006 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S0103-90162009000500006 |
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.66 n.5 2009 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 |
_version_ |
1748936461527285760 |