Potencial e lacunas de produtividade em soja no Brasil: uma análise pela metodologia do “Global Yield Gap Atlas”
Autor(a) principal: | |
---|---|
Data de Publicação: | 2021 |
Tipo de documento: | Tese |
Idioma: | por |
Título da fonte: | Manancial - Repositório Digital da UFSM |
Texto Completo: | http://repositorio.ufsm.br/handle/1/23380 |
Resumo: | In 2050 the world population will reach close to 10 billion inhabitants. And Brazil is of great importance due to the production of food, especially with the soybean, where it is the largest producer in the world. And for that, the yield potential is used to make decisions about agricultural policies, due to the growing demand for food and energy in many countries. The objective was to estimate the yield potential and gap in soybean in Brazil. And define the loss of yield due to the delay in the sowing date for all of Brazil. Selection of data sources and quality control are based on guidelines provided in the Global Yield Gap Atlas protocols, using calibrated models and the best available data on harvested soybean area, meteorological data, actual farmer yields and a spatial framework for the specific locations (regional and national levels). We conclude that the yield potential ranges from 5.7 to 7.5 Mg ha-¹, and the average is 6.7 Mg ha−¹. The water limited yield potential ranges from 3.1 to 6.9 Mg ha-¹ and the average is 5.5 Mg ha−¹ and the actual yield is 3.0 Mg ha−¹ for Brazil. The yield gap ranges from 2.7 to 4.6 Mg ha-¹, and the average is 3.7 Mg ha-¹. Dividing the yield gap into management gap and water gap we obtain values of 2.5 Mg ha-¹ and 1.2 Mg ha-¹, respectively, for all of Brazil. Finally, in the 5 soybean macroregions it is possible to identify the yield lost with the delay in the sowing date for all of Brazil. |
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2021-12-20T17:32:41Z2021-12-20T17:32:41Z2021-08-30http://repositorio.ufsm.br/handle/1/23380In 2050 the world population will reach close to 10 billion inhabitants. And Brazil is of great importance due to the production of food, especially with the soybean, where it is the largest producer in the world. And for that, the yield potential is used to make decisions about agricultural policies, due to the growing demand for food and energy in many countries. The objective was to estimate the yield potential and gap in soybean in Brazil. And define the loss of yield due to the delay in the sowing date for all of Brazil. Selection of data sources and quality control are based on guidelines provided in the Global Yield Gap Atlas protocols, using calibrated models and the best available data on harvested soybean area, meteorological data, actual farmer yields and a spatial framework for the specific locations (regional and national levels). We conclude that the yield potential ranges from 5.7 to 7.5 Mg ha-¹, and the average is 6.7 Mg ha−¹. The water limited yield potential ranges from 3.1 to 6.9 Mg ha-¹ and the average is 5.5 Mg ha−¹ and the actual yield is 3.0 Mg ha−¹ for Brazil. The yield gap ranges from 2.7 to 4.6 Mg ha-¹, and the average is 3.7 Mg ha-¹. Dividing the yield gap into management gap and water gap we obtain values of 2.5 Mg ha-¹ and 1.2 Mg ha-¹, respectively, for all of Brazil. Finally, in the 5 soybean macroregions it is possible to identify the yield lost with the delay in the sowing date for all of Brazil.Em 2050 a população mundial vai chegar próximo a 10 bilhões de habitantes. E o Brasil tem grande importância devido à produção de alimentos, principalmente com a cultura da soja, onde se encontra como o maior produtor mundial. E para isso, o potencial de produtividade é utilizado para tomada de decisões sobre políticas agrícolas, devido à crescente demanda de alimentos e de energia em muitos países. O objetivo foi de estimar o potencial e a lacuna de produtividade em soja no Brasil. E definir a perda de produtividade pelo atraso da época de semeadura para todo o Brasil. A seleção de fontes de dados e o controle de qualidade são baseados nas diretrizes fornecidas nos protocolos Global Yield Gap Atlas, utilizando modelos calibrados e os melhores dados disponíveis de área de soja colhida, dados meteorológicos, produtividades reais dos agricultores e uma estrutura espacial para os locais específicos (níveis regional e nacional). Concluímos que o Potencial de Produtividade varia de 5,7 a 7,5 Mg ha-¹, e a média é de 6,7 Mg ha−¹. O Potencial de Produtividade limitado por Água varia de 3,1 a 6,9 Mgha-¹ e a média é de 5,5 Mg ha−¹ e a produtividade atual está em 3,0 Mg ha−¹ para o Brasil. A Lacuna de produtividade (LP) varia de 2,7 a 4,6 Mg ha-¹, e a média é de 3,7 Mg ha-¹. Dividindo a LP em Lacuna de Manejo (LM) e Lacuna de Água (LA) obtemos valores de 2,5 Mg ha-¹ e de 1,2 Mg ha-¹ ,respectivamente, para todo o Brasil. Por fim, nas 5 macrorregiões sojícolas é possível identificar a perda de produtividade com o atraso na época de semeadura para todo o Brasil.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESFundação de Amparo à Pesquisa do Estado do Rio Grande do Sul - FAPERGSFundação de Amparo à Pesquisa do Estado de São Paulo - FAPESPporUniversidade 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/openAccessGlicine maxMacrorregiões sojícolasÉpoca de semeaduraAumento populacionalSustentabilidadeSoybean macroregionsSowing datePopulation increaseSustainabilityCNPQ::CIENCIAS AGRARIAS::AGRONOMIAPotencial e lacunas de produtividade em soja no Brasil: uma análise pela metodologia do “Global Yield Gap Atlas”Soybean yield potential and gaps in Brazil: an analysis by the methodology of the “Global Yield Gap Atlas”info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisStreck, Nereu Augustohttp://lattes.cnpq.br/8121082379157248Zanon, Alencar JuniorMedeiros, Sandro Luis PetterAlberto, Cleber MausFoloni, José Salvador Simonetihttp://lattes.cnpq.br/9736928933056158Richter, Gean Leonardo5001000000096006006006006006006003b01ed40-f2a9-4cc8-9109-59e6f482b05db55f93c1-1f74-4e3e-8e12-497141d1b16f7c7b164e-daea-46ed-90e4-44bf948e81884b569ec4-ef48-442a-84ee-9056d96aeff4f7202535-8406-401c-bf84-21fe8b3bd2531bb903df-fd87-447f-b66e-b0e97b52487areponame:Manancial - Repositório Digital da UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMLICENSElicense.txtlicense.txttext/plain; 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dc.title.por.fl_str_mv |
Potencial e lacunas de produtividade em soja no Brasil: uma análise pela metodologia do “Global Yield Gap Atlas” |
dc.title.alternative.eng.fl_str_mv |
Soybean yield potential and gaps in Brazil: an analysis by the methodology of the “Global Yield Gap Atlas” |
title |
Potencial e lacunas de produtividade em soja no Brasil: uma análise pela metodologia do “Global Yield Gap Atlas” |
spellingShingle |
Potencial e lacunas de produtividade em soja no Brasil: uma análise pela metodologia do “Global Yield Gap Atlas” Richter, Gean Leonardo Glicine max Macrorregiões sojícolas Época de semeadura Aumento populacional Sustentabilidade Soybean macroregions Sowing date Population increase Sustainability CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
title_short |
Potencial e lacunas de produtividade em soja no Brasil: uma análise pela metodologia do “Global Yield Gap Atlas” |
title_full |
Potencial e lacunas de produtividade em soja no Brasil: uma análise pela metodologia do “Global Yield Gap Atlas” |
title_fullStr |
Potencial e lacunas de produtividade em soja no Brasil: uma análise pela metodologia do “Global Yield Gap Atlas” |
title_full_unstemmed |
Potencial e lacunas de produtividade em soja no Brasil: uma análise pela metodologia do “Global Yield Gap Atlas” |
title_sort |
Potencial e lacunas de produtividade em soja no Brasil: uma análise pela metodologia do “Global Yield Gap Atlas” |
author |
Richter, Gean Leonardo |
author_facet |
Richter, Gean Leonardo |
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 |
Zanon, Alencar Junior |
dc.contributor.referee2.fl_str_mv |
Medeiros, Sandro Luis Petter |
dc.contributor.referee3.fl_str_mv |
Alberto, Cleber Maus |
dc.contributor.referee4.fl_str_mv |
Foloni, José Salvador Simoneti |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/9736928933056158 |
dc.contributor.author.fl_str_mv |
Richter, Gean Leonardo |
contributor_str_mv |
Streck, Nereu Augusto Zanon, Alencar Junior Medeiros, Sandro Luis Petter Alberto, Cleber Maus Foloni, José Salvador Simoneti |
dc.subject.por.fl_str_mv |
Glicine max Macrorregiões sojícolas Época de semeadura Aumento populacional Sustentabilidade |
topic |
Glicine max Macrorregiões sojícolas Época de semeadura Aumento populacional Sustentabilidade Soybean macroregions Sowing date Population increase Sustainability CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
dc.subject.eng.fl_str_mv |
Soybean macroregions Sowing date Population increase Sustainability |
dc.subject.cnpq.fl_str_mv |
CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
description |
In 2050 the world population will reach close to 10 billion inhabitants. And Brazil is of great importance due to the production of food, especially with the soybean, where it is the largest producer in the world. And for that, the yield potential is used to make decisions about agricultural policies, due to the growing demand for food and energy in many countries. The objective was to estimate the yield potential and gap in soybean in Brazil. And define the loss of yield due to the delay in the sowing date for all of Brazil. Selection of data sources and quality control are based on guidelines provided in the Global Yield Gap Atlas protocols, using calibrated models and the best available data on harvested soybean area, meteorological data, actual farmer yields and a spatial framework for the specific locations (regional and national levels). We conclude that the yield potential ranges from 5.7 to 7.5 Mg ha-¹, and the average is 6.7 Mg ha−¹. The water limited yield potential ranges from 3.1 to 6.9 Mg ha-¹ and the average is 5.5 Mg ha−¹ and the actual yield is 3.0 Mg ha−¹ for Brazil. The yield gap ranges from 2.7 to 4.6 Mg ha-¹, and the average is 3.7 Mg ha-¹. Dividing the yield gap into management gap and water gap we obtain values of 2.5 Mg ha-¹ and 1.2 Mg ha-¹, respectively, for all of Brazil. Finally, in the 5 soybean macroregions it is possible to identify the yield lost with the delay in the sowing date for all of Brazil. |
publishDate |
2021 |
dc.date.accessioned.fl_str_mv |
2021-12-20T17:32:41Z |
dc.date.available.fl_str_mv |
2021-12-20T17:32:41Z |
dc.date.issued.fl_str_mv |
2021-08-30 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
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doctoralThesis |
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http://repositorio.ufsm.br/handle/1/23380 |
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http://repositorio.ufsm.br/handle/1/23380 |
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por |
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500100000009 |
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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 |
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