Desempenho do modelo Simanihot em ambiente tropical
Autor(a) principal: | |
---|---|
Data de Publicação: | 2021 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Manancial - Repositório Digital da UFSM |
Texto Completo: | http://repositorio.ufsm.br/handle/1/29077 |
Resumo: | Appropriate tools and methodologies are required to quantify a country's ability to produce food in a context of food security. The use of crop simulation models makes possible to assess the interaction of genotype, environment and management practices, allowing the identification of the main causes responsible for reducing and limiting the productivity of agricultural crops. The climate is one of the main causes of productivity variability, and the main cause of climate variability is the El Niño Southern Oscillation (ENSO), which has a worldwide impact. Cassava is an important source of calories, and Brazil is one of the largest producers of cassava in the world. Thus, the present study aims to evaluate the performance of the Simanihot model to represent the cassava producing regions of Brazil in a tropical environment. Simulations were performed in the yield potential (Yp) and water-limited yield potential (Yw) in 20 locations in Brazil during the period from 1980 to 2017. Cassava root yield data published in the literature were used to validate the model's performance to estimate yield potential (Yp). The model was exposed to sensitivity tests to capture the effects of the ENSO phenomenon and to identify Brazilian biomes. The performance of the model was analyzed using the statistics of root-mean-square error (RMSE), normalized root-meansquare error (RMSEn), the BIAS index and the dw agreement index. It was identified that the model satisfactorily estimates the yield potential with a normalized error of 17.54% (RMSEn). The model also showed sensitivity in: (i) capturing Brazilian biomes in terms of apparent water balance; (ii) capture the reduction in yield due: delay in the planting date, and the lower available water capacity (AWC) for the soil types of sandy soil, loam soil and clay soil; and (iii) did not identify an impact of the ENSO phenomenon on the yield of cassava roots. |
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2023-05-15T12:14:15Z2023-05-15T12:14:15Z2021-10-05http://repositorio.ufsm.br/handle/1/29077Appropriate tools and methodologies are required to quantify a country's ability to produce food in a context of food security. The use of crop simulation models makes possible to assess the interaction of genotype, environment and management practices, allowing the identification of the main causes responsible for reducing and limiting the productivity of agricultural crops. The climate is one of the main causes of productivity variability, and the main cause of climate variability is the El Niño Southern Oscillation (ENSO), which has a worldwide impact. Cassava is an important source of calories, and Brazil is one of the largest producers of cassava in the world. Thus, the present study aims to evaluate the performance of the Simanihot model to represent the cassava producing regions of Brazil in a tropical environment. Simulations were performed in the yield potential (Yp) and water-limited yield potential (Yw) in 20 locations in Brazil during the period from 1980 to 2017. Cassava root yield data published in the literature were used to validate the model's performance to estimate yield potential (Yp). The model was exposed to sensitivity tests to capture the effects of the ENSO phenomenon and to identify Brazilian biomes. The performance of the model was analyzed using the statistics of root-mean-square error (RMSE), normalized root-meansquare error (RMSEn), the BIAS index and the dw agreement index. It was identified that the model satisfactorily estimates the yield potential with a normalized error of 17.54% (RMSEn). The model also showed sensitivity in: (i) capturing Brazilian biomes in terms of apparent water balance; (ii) capture the reduction in yield due: delay in the planting date, and the lower available water capacity (AWC) for the soil types of sandy soil, loam soil and clay soil; and (iii) did not identify an impact of the ENSO phenomenon on the yield of cassava roots.Dentro de um contexto de soberania e segurança alimentar são exigidas ferramentas e metodologias apropriadas para quantificar a capacidade de um país em produzir alimentos. O emprego de modelos ecofisiológicos possibilitam avaliar a interação do genótipo, ambiente e práticas de manejo, permitindo identificar as principais causas responsáveis por reduzirem e limitarem a produtividade dos cultivos agrícolas. O clima é uma das principais causas da variabilidade de produtividade, sendo que o principal causador da variabilidade do clima é o Fenômeno El Niño-Oscilação Sul (ENOS), que apresenta uma atuação a nível mundial. A cultura da mandioca é uma importante fonte de calorias, sendo que o Brasil é um dos maiores produtores de mandioca no mundo. Dessa forma o presente estudo tem por objetivo avaliar o desempenho do modelo Simanihot para representar as regiões produtoras de mandioca do Brasil em ambiente tropical. Foram realizadas simulações na condição potencial (Yp) e limitada por água (Yw) em 20 locais do Brasil durante o período de 1980 a 2017. Foram utilizados dados de produtividade de raízes de mandioca publicados na literatura para validar o desempenho do modelo. O modelo foi exposto a testes de sensibilidade para capturar os efeitos do fenômeno ENOS e identificar os biomas brasileiros. O desempenho do modelo foi analisado por meio das estatísticas da raiz do quadrado médio do erro (RQME), raiz do quadrado médio do erro normalizado (RQMEn), o índice BIAS e o índice de concordância dw. Foi identificado que o modelo estima de forma satisfatória o potencial de produtividade com um erro normalizado de 17,54% (RQMEn). O modelo também apresentou sensibilidade em: (i) capturar os biomas brasileiros quanto a disponibilidade hídrica; (ii) capturar a redução na produtividade devido à época de plantio e da restrição da capacidade de água disponível (CAD) para as categorias de solo arenoso, médio e argiloso; e (iii) não identificou um impacto do fenômeno ENOS na produtividade de raízes de mandioca.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESporUniversidade Federal de Santa MariaCentro de Ciências RuraisPrograma de Pós-Graduação em AgronomiaUFSMBrasilAgronomiaAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessManihot esculentaModelagemPotencial de produtividadeLacuna de produtividadeCrop modelYield potentialYield gapCNPQ::CIENCIAS AGRARIAS::AGRONOMIADesempenho do modelo Simanihot em ambiente tropicalPerformance evaluation of Simanihot model in a tropical environmentinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisZanon, Alencar Juniorhttp://lattes.cnpq.br/7337698178327854Streck, Nereu AugustoTironi, Luana FernandesFollmann, Diego Nicolauhttp://lattes.cnpq.br/4155401275254117Nascimento, Moises de Freitas do50010000000960060060060060060058307035-b49c-4cd8-b0c7-93cc1905cb1f0085067b-5877-4c25-9dd9-f8556cd606d256a426d2-4602-48e2-a27a-90c939a6b158a24fb89e-697b-4f00-96f2-5f7321476241d0815f49-5308-4e49-812f-a5e3a86be59freponame:Manancial - Repositório Digital da UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMORIGINALDIS_PPGAGRONOMIA_2021_NASCIMENTO_MOISES.pdfDIS_PPGAGRONOMIA_2021_NASCIMENTO_MOISES.pdfDissertação de Mestradoapplication/pdf1989737http://repositorio.ufsm.br/bitstream/1/29077/1/DIS_PPGAGRONOMIA_2021_NASCIMENTO_MOISES.pdf0d8b1ee3dab2ae2f3047e386412e7238MD51LICENSElicense.txtlicense.txttext/plain; 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dc.title.por.fl_str_mv |
Desempenho do modelo Simanihot em ambiente tropical |
dc.title.alternative.eng.fl_str_mv |
Performance evaluation of Simanihot model in a tropical environment |
title |
Desempenho do modelo Simanihot em ambiente tropical |
spellingShingle |
Desempenho do modelo Simanihot em ambiente tropical Nascimento, Moises de Freitas do Manihot esculenta Modelagem Potencial de produtividade Lacuna de produtividade Crop model Yield potential Yield gap CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
title_short |
Desempenho do modelo Simanihot em ambiente tropical |
title_full |
Desempenho do modelo Simanihot em ambiente tropical |
title_fullStr |
Desempenho do modelo Simanihot em ambiente tropical |
title_full_unstemmed |
Desempenho do modelo Simanihot em ambiente tropical |
title_sort |
Desempenho do modelo Simanihot em ambiente tropical |
author |
Nascimento, Moises de Freitas do |
author_facet |
Nascimento, Moises de Freitas do |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Zanon, Alencar Junior |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/7337698178327854 |
dc.contributor.advisor-co1.fl_str_mv |
Streck, Nereu Augusto |
dc.contributor.referee1.fl_str_mv |
Tironi, Luana Fernandes |
dc.contributor.referee2.fl_str_mv |
Follmann, Diego Nicolau |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/4155401275254117 |
dc.contributor.author.fl_str_mv |
Nascimento, Moises de Freitas do |
contributor_str_mv |
Zanon, Alencar Junior Streck, Nereu Augusto Tironi, Luana Fernandes Follmann, Diego Nicolau |
dc.subject.por.fl_str_mv |
Manihot esculenta Modelagem Potencial de produtividade Lacuna de produtividade |
topic |
Manihot esculenta Modelagem Potencial de produtividade Lacuna de produtividade Crop model Yield potential Yield gap CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
dc.subject.eng.fl_str_mv |
Crop model Yield potential Yield gap |
dc.subject.cnpq.fl_str_mv |
CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
description |
Appropriate tools and methodologies are required to quantify a country's ability to produce food in a context of food security. The use of crop simulation models makes possible to assess the interaction of genotype, environment and management practices, allowing the identification of the main causes responsible for reducing and limiting the productivity of agricultural crops. The climate is one of the main causes of productivity variability, and the main cause of climate variability is the El Niño Southern Oscillation (ENSO), which has a worldwide impact. Cassava is an important source of calories, and Brazil is one of the largest producers of cassava in the world. Thus, the present study aims to evaluate the performance of the Simanihot model to represent the cassava producing regions of Brazil in a tropical environment. Simulations were performed in the yield potential (Yp) and water-limited yield potential (Yw) in 20 locations in Brazil during the period from 1980 to 2017. Cassava root yield data published in the literature were used to validate the model's performance to estimate yield potential (Yp). The model was exposed to sensitivity tests to capture the effects of the ENSO phenomenon and to identify Brazilian biomes. The performance of the model was analyzed using the statistics of root-mean-square error (RMSE), normalized root-meansquare error (RMSEn), the BIAS index and the dw agreement index. It was identified that the model satisfactorily estimates the yield potential with a normalized error of 17.54% (RMSEn). The model also showed sensitivity in: (i) capturing Brazilian biomes in terms of apparent water balance; (ii) capture the reduction in yield due: delay in the planting date, and the lower available water capacity (AWC) for the soil types of sandy soil, loam soil and clay soil; and (iii) did not identify an impact of the ENSO phenomenon on the yield of cassava roots. |
publishDate |
2021 |
dc.date.issued.fl_str_mv |
2021-10-05 |
dc.date.accessioned.fl_str_mv |
2023-05-15T12:14:15Z |
dc.date.available.fl_str_mv |
2023-05-15T12:14:15Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
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publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.ufsm.br/handle/1/29077 |
url |
http://repositorio.ufsm.br/handle/1/29077 |
dc.language.iso.fl_str_mv |
por |
language |
por |
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500100000009 |
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600 600 600 600 600 600 |
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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/ |
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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 Agronomia |
dc.publisher.initials.fl_str_mv |
UFSM |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Agronomia |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Centro de Ciências Rurais |
dc.source.none.fl_str_mv |
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