MODELLING THE PASTURELAND PRODUCTIVITY IN AREAS OF SAVANNA IN NORTHERN MINAS GERAIS – BRAZIL
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Caminhos de Geografia |
Texto Completo: | https://seer.ufu.br/index.php/caminhosdegeografia/article/view/59046 |
Resumo: | 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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MODELLING THE PASTURELAND PRODUCTIVITY IN AREAS OF SAVANNA IN NORTHERN MINAS GERAIS – BRAZILMODELLING THE PASTURELAND PRODUCTIVITY IN AREAS OF SAVANNA IN NORTHERN MINAS GERAIS – BRAZILRemote SensingAnimal UnitDry MatterDry MatterAnimal UnitRemote SensingAccurate 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 %.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 %.EDUFU - Editora da Universidade Federal de Uberlândia2022-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionAvaliado pelos paresapplication/pdfhttps://seer.ufu.br/index.php/caminhosdegeografia/article/view/5904610.14393/RCG238759046Caminhos de Geografia; Vol. 23 No. 87 (2022): Junho; 124-134Caminhos de Geografia; Vol. 23 Núm. 87 (2022): Junho; 124-134Caminhos de Geografia; v. 23 n. 87 (2022): Junho; 124-1341678-6343reponame:Caminhos de Geografiainstname:Universidade Federal de Uberlândia (UFU)instacron:UFUenghttps://seer.ufu.br/index.php/caminhosdegeografia/article/view/59046/33959Copyright (c) 2022 Lucas Augusto Pereira da Silva, Édson Luís Bolfe, Manuel Eduardo Ferreira, Gabriel Alves Veloso, Carla Milena de Moura Laurentino, Claudionor Ribeiro da Silvahttp://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessda Silva, Lucas Augusto PereiraBolfe, Édson LuísFerreira, Manuel EduardoVeloso, Gabriel AlvesLaurentino, Carla Milena de Mourada Silva, Claudionor Ribeiro2022-07-25T12:30:51Zoai:ojs.www.seer.ufu.br:article/59046Revistahttps://seer.ufu.br/index.php/caminhosdegeografia/indexPUBhttp://www.seer.ufu.br/index.php/caminhosdegeografia/oaiflaviasantosgeo@gmail.com1678-63431678-6343opendoar:2022-07-25T12:30:51Caminhos de Geografia - Universidade Federal de Uberlândia (UFU)false |
dc.title.none.fl_str_mv |
MODELLING THE PASTURELAND PRODUCTIVITY IN AREAS OF SAVANNA IN NORTHERN MINAS GERAIS – BRAZIL 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 da Silva, Lucas Augusto Pereira Remote Sensing Animal Unit Dry Matter Dry Matter Animal Unit 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 |
da Silva, Lucas Augusto Pereira |
author_facet |
da Silva, Lucas Augusto Pereira Bolfe, Édson Luís Ferreira, Manuel Eduardo Veloso, Gabriel Alves Laurentino, Carla Milena de Moura da Silva, Claudionor Ribeiro |
author_role |
author |
author2 |
Bolfe, Édson Luís Ferreira, Manuel Eduardo Veloso, Gabriel Alves Laurentino, Carla Milena de Moura da Silva, Claudionor Ribeiro |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
da Silva, Lucas Augusto Pereira Bolfe, Édson Luís Ferreira, Manuel Eduardo Veloso, Gabriel Alves Laurentino, Carla Milena de Moura da Silva, Claudionor Ribeiro |
dc.subject.por.fl_str_mv |
Remote Sensing Animal Unit Dry Matter Dry Matter Animal Unit Remote Sensing |
topic |
Remote Sensing Animal Unit Dry Matter Dry Matter Animal Unit Remote Sensing |
description |
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 |
2022-06-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Avaliado pelos pares |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://seer.ufu.br/index.php/caminhosdegeografia/article/view/59046 10.14393/RCG238759046 |
url |
https://seer.ufu.br/index.php/caminhosdegeografia/article/view/59046 |
identifier_str_mv |
10.14393/RCG238759046 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://seer.ufu.br/index.php/caminhosdegeografia/article/view/59046/33959 |
dc.rights.driver.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
EDUFU - Editora da Universidade Federal de Uberlândia |
publisher.none.fl_str_mv |
EDUFU - Editora da Universidade Federal de Uberlândia |
dc.source.none.fl_str_mv |
Caminhos de Geografia; Vol. 23 No. 87 (2022): Junho; 124-134 Caminhos de Geografia; Vol. 23 Núm. 87 (2022): Junho; 124-134 Caminhos de Geografia; v. 23 n. 87 (2022): Junho; 124-134 1678-6343 reponame:Caminhos de Geografia instname:Universidade Federal de Uberlândia (UFU) instacron:UFU |
instname_str |
Universidade Federal de Uberlândia (UFU) |
instacron_str |
UFU |
institution |
UFU |
reponame_str |
Caminhos de Geografia |
collection |
Caminhos de Geografia |
repository.name.fl_str_mv |
Caminhos de Geografia - Universidade Federal de Uberlândia (UFU) |
repository.mail.fl_str_mv |
flaviasantosgeo@gmail.com |
_version_ |
1797067018735714304 |