Modelling the pastureland productivity in areas of savanna in northern Minas Gerais - Brazil.

Detalhes bibliográficos
Autor(a) principal: SILVA, L. A. P. da
Data de Publicação: 2022
Outros Autores: BOLFE, E. L., FERREIRA, M. E., VELOSO, G. A., LAURENTINO, C. M. de M., SILVA, C. R. da
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1143709
https://doi.org/10.14393/RCG238759046
Resumo: ABSTRACT. Accurate information on the quality of pastures is essential for the Brazilian economy, as livestock is relevant to the country's Gross Domestic Product (GDP); in addition, well-managed pastures are a necessary step to mitigate the emission of greenhouse gases (GHG). In this work, the productivity of pastures in savanna areas in northern Minas Gerais (Brazil) was analyzed using remote sensing techniques. It was found that dry biomass varied according to climatic seasonality, on the monthly time scale, with the highest values in the rainy season (68.79%) and the lowest in the dry period (31.21%). To observe the importance of well-managed pastures for the studied region, a correlation of environmental parameters that assume the quality of these pasturelans was carried out. We observed a more significant correlation between Gross Primary Production (GPP)), Leaf Area Index/Photosynthetically Active Radiation Absorbed (IAF/RFAA) and altitude with the dry biomass capacity of the Animal Unit (UA / Hectare). We observed that the pastures in the study region do not have enough inputs to meet the needs of the animals, thinking about the intensification logic, mainly when comparing the annual average of AU/ha of this study with the Brazilian median, with a difference of 86.37 %.
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spelling Modelling the pastureland productivity in areas of savanna in northern Minas Gerais - Brazil.Produtividade de pastagemModelagem de produtividade de pastagemUnidade animalDry MatterAnimal UnitSensoriamento RemotoMatéria SecaPasturesRemote sensingABSTRACT. Accurate information on the quality of pastures is essential for the Brazilian economy, as livestock is relevant to the country's Gross Domestic Product (GDP); in addition, well-managed pastures are a necessary step to mitigate the emission of greenhouse gases (GHG). In this work, the productivity of pastures in savanna areas in northern Minas Gerais (Brazil) was analyzed using remote sensing techniques. It was found that dry biomass varied according to climatic seasonality, on the monthly time scale, with the highest values in the rainy season (68.79%) and the lowest in the dry period (31.21%). To observe the importance of well-managed pastures for the studied region, a correlation of environmental parameters that assume the quality of these pasturelans was carried out. We observed a more significant correlation between Gross Primary Production (GPP)), Leaf Area Index/Photosynthetically Active Radiation Absorbed (IAF/RFAA) and altitude with the dry biomass capacity of the Animal Unit (UA / Hectare). We observed that the pastures in the study region do not have enough inputs to meet the needs of the animals, thinking about the intensification logic, mainly when comparing the annual average of AU/ha of this study with the Brazilian median, with a difference of 86.37 %.LUCAS AUGUSTO PEREIRA DA SILVA, UFU; EDSON LUIS BOLFE, CNPTIA; MANUEL EDUARDO FERREIRA, UFG; GABRIEL ALVES VELOSO, UFPA; CARLA MILENA DE MOURA LAURENTINO, UNIMONTES; CLAUDIONOR RIBEIRO DA SILVA, UFU.SILVA, L. A. P. daBOLFE, E. L.FERREIRA, M. E.VELOSO, G. A.LAURENTINO, C. M. de M.SILVA, C. R. da2022-06-03T15:19:55Z2022-06-03T15:19:55Z2022-06-032022info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleCaminhos de Geografia, v. 23, n. 87, p. 124-134, jun. 2022.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1143709https://doi.org/10.14393/RCG238759046enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2022-06-03T15:20:03Zoai:www.alice.cnptia.embrapa.br:doc/1143709Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542022-06-03T15:20:03falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542022-06-03T15:20:03Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Modelling the pastureland productivity in areas of savanna in northern Minas Gerais - Brazil.
title Modelling the pastureland productivity in areas of savanna in northern Minas Gerais - Brazil.
spellingShingle Modelling the pastureland productivity in areas of savanna in northern Minas Gerais - Brazil.
SILVA, L. A. P. da
Produtividade de pastagem
Modelagem de produtividade de pastagem
Unidade animal
Dry Matter
Animal Unit
Sensoriamento Remoto
Matéria Seca
Pastures
Remote sensing
title_short Modelling the pastureland productivity in areas of savanna in northern Minas Gerais - Brazil.
title_full Modelling the pastureland productivity in areas of savanna in northern Minas Gerais - Brazil.
title_fullStr Modelling the pastureland productivity in areas of savanna in northern Minas Gerais - Brazil.
title_full_unstemmed Modelling the pastureland productivity in areas of savanna in northern Minas Gerais - Brazil.
title_sort Modelling the pastureland productivity in areas of savanna in northern Minas Gerais - Brazil.
author SILVA, L. A. P. da
author_facet SILVA, L. A. P. da
BOLFE, E. L.
FERREIRA, M. E.
VELOSO, G. A.
LAURENTINO, C. M. de M.
SILVA, C. R. da
author_role author
author2 BOLFE, E. L.
FERREIRA, M. E.
VELOSO, G. A.
LAURENTINO, C. M. de M.
SILVA, C. R. da
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv LUCAS AUGUSTO PEREIRA DA SILVA, UFU; EDSON LUIS BOLFE, CNPTIA; MANUEL EDUARDO FERREIRA, UFG; GABRIEL ALVES VELOSO, UFPA; CARLA MILENA DE MOURA LAURENTINO, UNIMONTES; CLAUDIONOR RIBEIRO DA SILVA, UFU.
dc.contributor.author.fl_str_mv SILVA, L. A. P. da
BOLFE, E. L.
FERREIRA, M. E.
VELOSO, G. A.
LAURENTINO, C. M. de M.
SILVA, C. R. da
dc.subject.por.fl_str_mv Produtividade de pastagem
Modelagem de produtividade de pastagem
Unidade animal
Dry Matter
Animal Unit
Sensoriamento Remoto
Matéria Seca
Pastures
Remote sensing
topic Produtividade de pastagem
Modelagem de produtividade de pastagem
Unidade animal
Dry Matter
Animal Unit
Sensoriamento Remoto
Matéria Seca
Pastures
Remote sensing
description ABSTRACT. Accurate information on the quality of pastures is essential for the Brazilian economy, as livestock is relevant to the country's Gross Domestic Product (GDP); in addition, well-managed pastures are a necessary step to mitigate the emission of greenhouse gases (GHG). In this work, the productivity of pastures in savanna areas in northern Minas Gerais (Brazil) was analyzed using remote sensing techniques. It was found that dry biomass varied according to climatic seasonality, on the monthly time scale, with the highest values in the rainy season (68.79%) and the lowest in the dry period (31.21%). To observe the importance of well-managed pastures for the studied region, a correlation of environmental parameters that assume the quality of these pasturelans was carried out. We observed a more significant correlation between Gross Primary Production (GPP)), Leaf Area Index/Photosynthetically Active Radiation Absorbed (IAF/RFAA) and altitude with the dry biomass capacity of the Animal Unit (UA / Hectare). We observed that the pastures in the study region do not have enough inputs to meet the needs of the animals, thinking about the intensification logic, mainly when comparing the annual average of AU/ha of this study with the Brazilian median, with a difference of 86.37 %.
publishDate 2022
dc.date.none.fl_str_mv 2022-06-03T15:19:55Z
2022-06-03T15:19:55Z
2022-06-03
2022
dc.type.driver.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv Caminhos de Geografia, v. 23, n. 87, p. 124-134, jun. 2022.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1143709
https://doi.org/10.14393/RCG238759046
identifier_str_mv Caminhos de Geografia, v. 23, n. 87, p. 124-134, jun. 2022.
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1143709
https://doi.org/10.14393/RCG238759046
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
collection Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository.name.fl_str_mv Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv cg-riaa@embrapa.br
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