Simulação do crescimento, desenvolvimento e produtividade de milho em clima presente e futuro

Detalhes bibliográficos
Autor(a) principal: Silva, Stefania Dalmolin da
Data de Publicação: 2018
Tipo de documento: Tese
Idioma: por
Título da fonte: Manancial - Repositório Digital da UFSM
Texto Completo: http://repositorio.ufsm.br/handle/1/15640
Resumo: Corn is one of the most important summer crops around the world and this grain plays an important role in the sustainability and food security of the world's population. Agricultural modeling is an important tool in planning agricultural activities. Of the existing maize models, the CSM-Ceres-Maize and Hybrid-Maize models are easy-to-use process-based models that can simulate maize growth, development and yield. The objectives of this dissertation were (a) to compare different methods of estimating genetic parameters in the CSM-Ceres-Maize model, (b) to compare the capacity of the CSM-Ceres-Maize and Hybrid-Maize models to simulate growth, development and productivity of maize with different genetic variability in a subtropical environment and (c) to simulate maize productivity in the Rio Grande do Sul State under future climate change scenarios using the Hybrid-Maize model. For the calibration of the models, field experiments were carried out during the 2013/14 and 2014/15 growing seasons, and for the evaluation of these models, data were collected in field experiment in the 2015/16 and 2017/18 growing seasons. Two improved maize cultivars, one of open pollination variety 'BRS Planalto' and one simple hybrid 'AS 1573PRO', and two 'Bico de Ouro' and 'Cinquentinha' were used. To simulate maize yields with different genetic variability in relation to future climatic scenarios, the scenarios RCP 2.6, RCP 4.5 and RCP 8.5 of the fifth IPCC report using the Hybrid-Maize model, were used. Simulations showed a decrease in maize yield in the northern half of the state, and up to 5.5 Mg ha-1, while in the southern half showed an increase in maize productivity in the period 2070-2098 in relation to the period 1975-2005.
id UFSM-20_6852685ba2f35fd548f5b60c3d2d511e
oai_identifier_str oai:repositorio.ufsm.br:1/15640
network_acronym_str UFSM-20
network_name_str Manancial - Repositório Digital da UFSM
repository_id_str 3913
spelling 2019-02-14T13:28:59Z2019-02-14T13:28:59Z2018-09-26http://repositorio.ufsm.br/handle/1/15640Corn is one of the most important summer crops around the world and this grain plays an important role in the sustainability and food security of the world's population. Agricultural modeling is an important tool in planning agricultural activities. Of the existing maize models, the CSM-Ceres-Maize and Hybrid-Maize models are easy-to-use process-based models that can simulate maize growth, development and yield. The objectives of this dissertation were (a) to compare different methods of estimating genetic parameters in the CSM-Ceres-Maize model, (b) to compare the capacity of the CSM-Ceres-Maize and Hybrid-Maize models to simulate growth, development and productivity of maize with different genetic variability in a subtropical environment and (c) to simulate maize productivity in the Rio Grande do Sul State under future climate change scenarios using the Hybrid-Maize model. For the calibration of the models, field experiments were carried out during the 2013/14 and 2014/15 growing seasons, and for the evaluation of these models, data were collected in field experiment in the 2015/16 and 2017/18 growing seasons. Two improved maize cultivars, one of open pollination variety 'BRS Planalto' and one simple hybrid 'AS 1573PRO', and two 'Bico de Ouro' and 'Cinquentinha' were used. To simulate maize yields with different genetic variability in relation to future climatic scenarios, the scenarios RCP 2.6, RCP 4.5 and RCP 8.5 of the fifth IPCC report using the Hybrid-Maize model, were used. Simulations showed a decrease in maize yield in the northern half of the state, and up to 5.5 Mg ha-1, while in the southern half showed an increase in maize productivity in the period 2070-2098 in relation to the period 1975-2005.O milho é uma das principais culturas de verão ao redor do mundo e este grão desempenha um papel importante na sustentabilidade e segurança alimentar da população mundial. A modelagem agrícola é uma importante ferramenta no planejamento das atividades agrícolas. Dos modelos de milhos existentes, os modelos CSM-Ceres-Maize e Hybrid-Maize, são modelos de milho baseados em processos, de fácil utilização, que são capazes de simular o crescimento, o desenvolvimento e produtividade de milho. Os objetivos desta tese foram (a) comparar diferentes métodos de estimativa de parâmetros genéticos do modelo CSM-Ceres-Maize, (b) comparar a capacidade dos modelos CSM-Ceres-Maize e Hybrid-Maize em simular o crescimento, o desenvolvimento e produtividade de milho com diferente variabilidade genética em ambiente subtropical e (c) simular a produtividade de milho no Estado do Rio Grande do Sul em cenários futuros de mudança climática utilizando o modelo Hybrid-Maize. Para a realização da calibração dos modelos, foram realizados experimentos a campo durante os anos agrícolas 2013/14 e 2014/15, e para o teste destes modelos, foram coletados dados em experimento a campo nos anos 2015/16 e 2017/18. Foram utilizadas duas cultivares melhoradas de milho, uma variedade de polinização aberta ‘BRS Planalto’ e um híbrido simples ‘AS 1573PRO’, e duas cultivares crioulas de milho ‘Bico de Ouro’ e ‘Cinquentinha’. Para simular a produtividade de milho com diferente variabilidade genética diante a cenários climáticos futuros, foram utilizados os cenários RCP 2.6, RCP 4.5 e RCP 8.5 do quinto relatório do IPCC, utilizando o modelo Hybrid-Maize. As simulações mostraram diminuição da produtividade na metade norte do estado, e, até 5,5 Mg ha-1, enquanto que na metade sul mostraram um aumento na produtividade de milho no período de 2070-2098 em relação ao período de 1975-2005.porUniversidade Federal de Santa MariaCentro de Ciências RuraisPrograma de Pós-Graduação em Engenharia AgrícolaUFSMBrasilEngenharia AgrícolaAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessZea mays L.CSM-Ceres-MaizeHybrid-MaizeCenários climáticos futurosCultivares crioulasFuture climate scenariosLandrace cultivarsCNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLASimulação do crescimento, desenvolvimento e produtividade de milho em clima presente e futuroSimulating growth, development and yield of maize under current and future climateinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisStreck, Nereu Augustohttp://lattes.cnpq.br/8121082379157248Ferraz, Simone Erotildes Teleginskihttp://lattes.cnpq.br/5545006407615789Zanon, Alencar Juniorhttp://lattes.cnpq.br/7337698178327854Alberto, Cleber Maushttp://lattes.cnpq.br/2747295128900648Arsego, Diogo Alessandrohttp://lattes.cnpq.br/5303560663845220http://lattes.cnpq.br/8667322756483988Silva, Stefania Dalmolin da5003000000086003b01ed40-f2a9-4cc8-9109-59e6f482b05d72edfdc8-a31f-4738-be04-da1917a7689666454172-9d01-4ef2-99e6-103cb6b6eaceb206c95f-ec35-4308-a5b6-8cbd4eb6a246f7202535-8406-401c-bf84-21fe8b3bd2533e90e040-8d31-4421-b11c-eb3249681b4areponame:Manancial - Repositório Digital da UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805http://repositorio.ufsm.br/bitstream/1/15640/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81956http://repositorio.ufsm.br/bitstream/1/15640/3/license.txt2f0571ecee68693bd5cd3f17c1e075dfMD53ORIGINALTES_PPGEA_2018_SILVA_STEFANIA.pdfTES_PPGEA_2018_SILVA_STEFANIA.pdfTese de Doutoradoapplication/pdf5459488http://repositorio.ufsm.br/bitstream/1/15640/1/TES_PPGEA_2018_SILVA_STEFANIA.pdf830c8ca83e0392f86526cd2fe65995bbMD51TEXTTES_PPGEA_2018_SILVA_STEFANIA.pdf.txtTES_PPGEA_2018_SILVA_STEFANIA.pdf.txtExtracted texttext/plain150966http://repositorio.ufsm.br/bitstream/1/15640/4/TES_PPGEA_2018_SILVA_STEFANIA.pdf.txt5a68d6b33d58bf994a1ef7e096103f10MD54THUMBNAILTES_PPGEA_2018_SILVA_STEFANIA.pdf.jpgTES_PPGEA_2018_SILVA_STEFANIA.pdf.jpgIM Thumbnailimage/jpeg4445http://repositorio.ufsm.br/bitstream/1/15640/5/TES_PPGEA_2018_SILVA_STEFANIA.pdf.jpg972b02b3daf4f552d4e7c20d98afeac4MD551/156402022-08-31 12:33:56.497oai:repositorio.ufsm.br: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ório Institucionalhttp://repositorio.ufsm.br/PUBhttp://repositorio.ufsm.br/oai/requestopendoar:39132022-08-31T15:33:56Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM)false
dc.title.por.fl_str_mv Simulação do crescimento, desenvolvimento e produtividade de milho em clima presente e futuro
dc.title.alternative.eng.fl_str_mv Simulating growth, development and yield of maize under current and future climate
title Simulação do crescimento, desenvolvimento e produtividade de milho em clima presente e futuro
spellingShingle Simulação do crescimento, desenvolvimento e produtividade de milho em clima presente e futuro
Silva, Stefania Dalmolin da
Zea mays L.
CSM-Ceres-Maize
Hybrid-Maize
Cenários climáticos futuros
Cultivares crioulas
Future climate scenarios
Landrace cultivars
CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA
title_short Simulação do crescimento, desenvolvimento e produtividade de milho em clima presente e futuro
title_full Simulação do crescimento, desenvolvimento e produtividade de milho em clima presente e futuro
title_fullStr Simulação do crescimento, desenvolvimento e produtividade de milho em clima presente e futuro
title_full_unstemmed Simulação do crescimento, desenvolvimento e produtividade de milho em clima presente e futuro
title_sort Simulação do crescimento, desenvolvimento e produtividade de milho em clima presente e futuro
author Silva, Stefania Dalmolin da
author_facet Silva, Stefania Dalmolin da
author_role author
dc.contributor.advisor1.fl_str_mv Streck, Nereu Augusto
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/8121082379157248
dc.contributor.referee1.fl_str_mv Ferraz, Simone Erotildes Teleginski
dc.contributor.referee1Lattes.fl_str_mv http://lattes.cnpq.br/5545006407615789
dc.contributor.referee2.fl_str_mv Zanon, Alencar Junior
dc.contributor.referee2Lattes.fl_str_mv http://lattes.cnpq.br/7337698178327854
dc.contributor.referee3.fl_str_mv Alberto, Cleber Maus
dc.contributor.referee3Lattes.fl_str_mv http://lattes.cnpq.br/2747295128900648
dc.contributor.referee4.fl_str_mv Arsego, Diogo Alessandro
dc.contributor.referee4Lattes.fl_str_mv http://lattes.cnpq.br/5303560663845220
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/8667322756483988
dc.contributor.author.fl_str_mv Silva, Stefania Dalmolin da
contributor_str_mv Streck, Nereu Augusto
Ferraz, Simone Erotildes Teleginski
Zanon, Alencar Junior
Alberto, Cleber Maus
Arsego, Diogo Alessandro
dc.subject.por.fl_str_mv Zea mays L.
CSM-Ceres-Maize
Hybrid-Maize
Cenários climáticos futuros
Cultivares crioulas
topic Zea mays L.
CSM-Ceres-Maize
Hybrid-Maize
Cenários climáticos futuros
Cultivares crioulas
Future climate scenarios
Landrace cultivars
CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA
dc.subject.eng.fl_str_mv Future climate scenarios
Landrace cultivars
dc.subject.cnpq.fl_str_mv CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA
description Corn is one of the most important summer crops around the world and this grain plays an important role in the sustainability and food security of the world's population. Agricultural modeling is an important tool in planning agricultural activities. Of the existing maize models, the CSM-Ceres-Maize and Hybrid-Maize models are easy-to-use process-based models that can simulate maize growth, development and yield. The objectives of this dissertation were (a) to compare different methods of estimating genetic parameters in the CSM-Ceres-Maize model, (b) to compare the capacity of the CSM-Ceres-Maize and Hybrid-Maize models to simulate growth, development and productivity of maize with different genetic variability in a subtropical environment and (c) to simulate maize productivity in the Rio Grande do Sul State under future climate change scenarios using the Hybrid-Maize model. For the calibration of the models, field experiments were carried out during the 2013/14 and 2014/15 growing seasons, and for the evaluation of these models, data were collected in field experiment in the 2015/16 and 2017/18 growing seasons. Two improved maize cultivars, one of open pollination variety 'BRS Planalto' and one simple hybrid 'AS 1573PRO', and two 'Bico de Ouro' and 'Cinquentinha' were used. To simulate maize yields with different genetic variability in relation to future climatic scenarios, the scenarios RCP 2.6, RCP 4.5 and RCP 8.5 of the fifth IPCC report using the Hybrid-Maize model, were used. Simulations showed a decrease in maize yield in the northern half of the state, and up to 5.5 Mg ha-1, while in the southern half showed an increase in maize productivity in the period 2070-2098 in relation to the period 1975-2005.
publishDate 2018
dc.date.issued.fl_str_mv 2018-09-26
dc.date.accessioned.fl_str_mv 2019-02-14T13:28:59Z
dc.date.available.fl_str_mv 2019-02-14T13:28:59Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://repositorio.ufsm.br/handle/1/15640
url http://repositorio.ufsm.br/handle/1/15640
dc.language.iso.fl_str_mv por
language por
dc.relation.cnpq.fl_str_mv 500300000008
dc.relation.confidence.fl_str_mv 600
dc.relation.authority.fl_str_mv 3b01ed40-f2a9-4cc8-9109-59e6f482b05d
72edfdc8-a31f-4738-be04-da1917a76896
66454172-9d01-4ef2-99e6-103cb6b6eace
b206c95f-ec35-4308-a5b6-8cbd4eb6a246
f7202535-8406-401c-bf84-21fe8b3bd253
3e90e040-8d31-4421-b11c-eb3249681b4a
dc.rights.driver.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Universidade Federal de Santa Maria
Centro de Ciências Rurais
dc.publisher.program.fl_str_mv Programa de Pós-Graduação em Engenharia Agrícola
dc.publisher.initials.fl_str_mv UFSM
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv Engenharia Agrícola
publisher.none.fl_str_mv Universidade Federal de Santa Maria
Centro de Ciências Rurais
dc.source.none.fl_str_mv reponame:Manancial - Repositório Digital da UFSM
instname:Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
instname_str Universidade Federal de Santa Maria (UFSM)
instacron_str UFSM
institution UFSM
reponame_str Manancial - Repositório Digital da UFSM
collection Manancial - Repositório Digital da UFSM
bitstream.url.fl_str_mv http://repositorio.ufsm.br/bitstream/1/15640/2/license_rdf
http://repositorio.ufsm.br/bitstream/1/15640/3/license.txt
http://repositorio.ufsm.br/bitstream/1/15640/1/TES_PPGEA_2018_SILVA_STEFANIA.pdf
http://repositorio.ufsm.br/bitstream/1/15640/4/TES_PPGEA_2018_SILVA_STEFANIA.pdf.txt
http://repositorio.ufsm.br/bitstream/1/15640/5/TES_PPGEA_2018_SILVA_STEFANIA.pdf.jpg
bitstream.checksum.fl_str_mv 4460e5956bc1d1639be9ae6146a50347
2f0571ecee68693bd5cd3f17c1e075df
830c8ca83e0392f86526cd2fe65995bb
5a68d6b33d58bf994a1ef7e096103f10
972b02b3daf4f552d4e7c20d98afeac4
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
MD5
MD5
repository.name.fl_str_mv Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM)
repository.mail.fl_str_mv
_version_ 1794523831725981696