Agrometeorological models for estimating sweet cassava yield
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1590/1983-40632018v4850451 http://hdl.handle.net/11449/158217 |
Resumo: | ABSTRACT Brazil is the fourth largest producer of cassava in the world, with climate conditions being the main factor regulating its production. This study aimed to develop agrometeorological models to estimate the sweet cassava yield for the São Paulo state, as well as to identify which climatic variables have more influence on yield. The models were built with multiple linear regression and classified by the following statistical indexes: lower mean absolute percentage error, higher adjusted determination coefficient and significance (p-value < 0.05). It was observed that the mean air temperature has a great influence on the sweet cassava yield during the whole cycle for all regions in the state. Water deficit and soil water storage were the most influential variables at the beginning and final stages. The models accuracy ranged in 3.11 %, 6.40 %, 6.77 % and 7.15 %, respectively for Registro, Mogi Mirim, Assis and Jaboticabal. |
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Agrometeorological models for estimating sweet cassava yieldModelos agrometeorológicos para estimar o rendimento de mandioca doceManihot esculentacrop modelingclimatologyManihot esculentamodelagem de culturasclimatologiaABSTRACT Brazil is the fourth largest producer of cassava in the world, with climate conditions being the main factor regulating its production. This study aimed to develop agrometeorological models to estimate the sweet cassava yield for the São Paulo state, as well as to identify which climatic variables have more influence on yield. The models were built with multiple linear regression and classified by the following statistical indexes: lower mean absolute percentage error, higher adjusted determination coefficient and significance (p-value < 0.05). It was observed that the mean air temperature has a great influence on the sweet cassava yield during the whole cycle for all regions in the state. Water deficit and soil water storage were the most influential variables at the beginning and final stages. The models accuracy ranged in 3.11 %, 6.40 %, 6.77 % and 7.15 %, respectively for Registro, Mogi Mirim, Assis and Jaboticabal.RESUMO O Brasil é o quarto maior produtor mundial de mandioca, tendo as condições climáticas como principais fatores na regulação de sua produção. Objetivou-se desenvolver modelos agrometeorológicos para estimar a produtividade de mandioca doce para o estado de São Paulo, bem como identificar quais variáveis ​​climáticas exercem maior influência sobre a produtividade. Os modelos foram construídos com regressão linear múltipla e classificados pelos seguintes índices estatísticos: menor erro percentual absoluto médio, maior coeficiente de determinação ajustado e significância (p-valor < 0.05). Identificou-se que a temperatura média do ar tem grande influência no rendimento da mandioca durante todo o ciclo, para todas as regiões do estado. O déficit hídrico e o armazenamento de água no solo foram as variáveis ​​mais influentes nos estágios inicial e final. A precisão dos modelos variou em 3,11 %, 6,40 %, 6,77 % e 7,15 %, respectivamente para Registro, Mogi Mirim, Assis e Jaboticabal.Universidade Estadual Paulista Faculdade de Ciências Agrárias e Veterinárias Departamento de Ciências ExatasInstituto Federal de Educação, Ciência e Tecnologia de Mato Grosso do SulUniversidade Estadual Paulista Faculdade de Ciências Agrárias e Veterinárias Departamento de Ciências ExatasEscola de Agronomia/UFGUniversidade Estadual Paulista (Unesp)Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso do SulMoreto, Victor BruniniAparecido, Lucas Eduardo De OliveiraRolim, Glauco De SouzaMoraes, José Reinaldo Da Silva Cabral De2018-11-12T17:28:52Z2018-11-12T17:28:52Z2018-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article43-51application/pdfhttp://dx.doi.org/10.1590/1983-40632018v4850451Pesquisa Agropecuária Tropical. Escola de Agronomia/UFG, v. 48, n. 1, p. 43-51, 2018.1983-4063http://hdl.handle.net/11449/15821710.1590/1983-40632018v4850451S1983-40632018000100043S1983-40632018000100043.pdfSciELOreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengPesquisa Agropecuária Tropical0,346info:eu-repo/semantics/openAccess2024-06-06T13:42:49Zoai:repositorio.unesp.br:11449/158217Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:47:43.029481Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Agrometeorological models for estimating sweet cassava yield Modelos agrometeorológicos para estimar o rendimento de mandioca doce |
title |
Agrometeorological models for estimating sweet cassava yield |
spellingShingle |
Agrometeorological models for estimating sweet cassava yield Moreto, Victor Brunini Manihot esculenta crop modeling climatology Manihot esculenta modelagem de culturas climatologia |
title_short |
Agrometeorological models for estimating sweet cassava yield |
title_full |
Agrometeorological models for estimating sweet cassava yield |
title_fullStr |
Agrometeorological models for estimating sweet cassava yield |
title_full_unstemmed |
Agrometeorological models for estimating sweet cassava yield |
title_sort |
Agrometeorological models for estimating sweet cassava yield |
author |
Moreto, Victor Brunini |
author_facet |
Moreto, Victor Brunini Aparecido, Lucas Eduardo De Oliveira Rolim, Glauco De Souza Moraes, José Reinaldo Da Silva Cabral De |
author_role |
author |
author2 |
Aparecido, Lucas Eduardo De Oliveira Rolim, Glauco De Souza Moraes, José Reinaldo Da Silva Cabral De |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso do Sul |
dc.contributor.author.fl_str_mv |
Moreto, Victor Brunini Aparecido, Lucas Eduardo De Oliveira Rolim, Glauco De Souza Moraes, José Reinaldo Da Silva Cabral De |
dc.subject.por.fl_str_mv |
Manihot esculenta crop modeling climatology Manihot esculenta modelagem de culturas climatologia |
topic |
Manihot esculenta crop modeling climatology Manihot esculenta modelagem de culturas climatologia |
description |
ABSTRACT Brazil is the fourth largest producer of cassava in the world, with climate conditions being the main factor regulating its production. This study aimed to develop agrometeorological models to estimate the sweet cassava yield for the São Paulo state, as well as to identify which climatic variables have more influence on yield. The models were built with multiple linear regression and classified by the following statistical indexes: lower mean absolute percentage error, higher adjusted determination coefficient and significance (p-value < 0.05). It was observed that the mean air temperature has a great influence on the sweet cassava yield during the whole cycle for all regions in the state. Water deficit and soil water storage were the most influential variables at the beginning and final stages. The models accuracy ranged in 3.11 %, 6.40 %, 6.77 % and 7.15 %, respectively for Registro, Mogi Mirim, Assis and Jaboticabal. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-11-12T17:28:52Z 2018-11-12T17:28:52Z 2018-01-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1590/1983-40632018v4850451 Pesquisa Agropecuária Tropical. Escola de Agronomia/UFG, v. 48, n. 1, p. 43-51, 2018. 1983-4063 http://hdl.handle.net/11449/158217 10.1590/1983-40632018v4850451 S1983-40632018000100043 S1983-40632018000100043.pdf |
url |
http://dx.doi.org/10.1590/1983-40632018v4850451 http://hdl.handle.net/11449/158217 |
identifier_str_mv |
Pesquisa Agropecuária Tropical. Escola de Agronomia/UFG, v. 48, n. 1, p. 43-51, 2018. 1983-4063 10.1590/1983-40632018v4850451 S1983-40632018000100043 S1983-40632018000100043.pdf |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Pesquisa Agropecuária Tropical 0,346 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
43-51 application/pdf |
dc.publisher.none.fl_str_mv |
Escola de Agronomia/UFG |
publisher.none.fl_str_mv |
Escola de Agronomia/UFG |
dc.source.none.fl_str_mv |
SciELO reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128859284963328 |