Simulação do crescimento, desenvolvimento e produtividade de milho em clima presente e futuro
Autor(a) principal: | |
---|---|
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. |
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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; 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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 |
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info:eu-repo/semantics/doctoralThesis |
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doctoralThesis |
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publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.ufsm.br/handle/1/15640 |
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http://repositorio.ufsm.br/handle/1/15640 |
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por |
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por |
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500300000008 |
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600 |
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Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
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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 |
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