Forage mass production in integrated, extensive and intensive livestock systems in the central region of the State of São Paulo (Massa de forragem em sistemas pecuários integrados, extensivos e intensivos na região central do Estado de São Paulo)

Detalhes bibliográficos
Autor(a) principal: Nogueira, Sandra Furlan
Data de Publicação: 2022
Outros Autores: Bayma-Silva, Gustavo, Grego, Célia Regina, Santos, Patrícia Menezes, Pezzopane, Jose Ricardo Macedo
Tipo de documento: Conjunto de dados
Título da fonte: Repositório de Dados de Pesquisa da EMBRAPA (Redape)
Texto Completo: https://doi.org/10.48432/1VJD45
Resumo: The forage mass is information of great importance in the management of pastures and animals in productive systems. Unfortunately, there are still no well-established and well-founded methodologies for the estimation of forage mass values ​​on a large scale, which allow its wide adoption in livestock systems and improve decision-making and management processes. In this database, we present three spreadsheets with information on the availability of forage mass in three different livestock systems: integration crop-livestock, extensive and intensive. Heights and masses (dry and fresh) are measurements taken in the field and estimates are made using the SAFER algorithm. Methods and data collection and estimates for the project study areas are described in Bayma et al. (2019) and Nogueira et al. (2021). The spreadsheet "Forage_Mass_Data_LIV_FUT" has six tabs: 1) "Sampling_points_ICLS" tab with a high resolution image of the evaluated Integrated crop-livestock systems (5 and 6) and the data sampling points (A01 to A50); 2) "Forrage_Mass_ICLS" tab is composed of columns with the following information: Sampiling data (January 2018 to November 2019), Livestock system (ICL), ICL System Repetition (repetitions 5 and 6 of the ICL System), Paddock number (6 paddocks in each repetition - from 1 to 6), Rotation management (paddocks can be in Grazing, pre-grazing, post-grazing or Grass growth), Sampling points (A01 to A50), Latitude, Longitude, Grass height (mean of 5 heights per point - in cm), Total Dry Mass (kg ha-1), Dry Green Mass (kg ha-1), Total Fresh Mass (kg ha-1), Fresh Green Mass (kg ha-1), Fresh Dead Mass (kg ha-1), Fresh Green Mass Estimation by Safer Model (kg ha-1 day-1), Forage growing days in rotation cycle and Forage growth days and Fresh Green Mass Estimation by Safer Model (kg ha-1 month-1); 3) "Sampling_points_Extensive" tab with a high resolution image of the extensive livestock systems evaluated (7 and 8) and the data sampling points (B01 to B40); 4) "Forage_Mass_Extensive" tab is composed of columns with the following information: Sampiling data (January 2018 to November 2019), Livestock system (Extensive), Extensive System Repetition (repetitions 7 and 8 of the Extensive System), Sampling points (B01 to B40), Latitude, Longitude, Grass height (mean of 5 heights per point - in cm), Total Dry Mass (kg ha-1), Dry Green Mass (kg ha-1), Total Fresh Mass (kg ha-1), Fresh Green Mass (kg ha-1), Fresh Dead Mass (kg ha-1), Fresh Green Mass Estimation by Safer Model (kg ha-1 day-1), Forage growing days in rotation cycle and Forage growth days and Fresh Green Mass Estimation by Safer Model (kg ha-1 month-1); 5) "Sampling_points_Intensive" tab with a high resolution image of the Intensive livestock systems evaluated (9 and 10) and the data collection points (C01 to C45) and 6) "Forage_Mass_Intensive" tab is composed of columns with the following information : Sampiling data (January 2018 to November 2019), Livestock system (Intensive), Intensive System Repetition (repetitions 9 and 10 of the Intensive System), Paddock number (6 paddocks in each repetition - from 1 to 6), Rotation management (paddocks can be in Grazing, pre-grazing, post-grazing or Grass growth), Sampling points (C01 to C45), Latitude, Longitude, Grass height (mean of 5 heights per point - in cm), Total Dry Mass (kg ha-1), Dry Green Mass (kg ha-1), Total Fresh Mass (kg ha-1), Fresh Green Mass (kg ha-1), Fresh Dead Mass (kg ha-1), Fresh Green Mass Estimation by Safer Model (kg ha-1 day-1), Forage growing days in rotation cycle and Forage growth days and Fresh Green Mass Estimation by Safer Model (kg ha-1 month-1).
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spelling https://doi.org/10.48432/1VJD45Nogueira, Sandra FurlanBayma-Silva, GustavoGrego, Célia ReginaSantos, Patrícia MenezesPezzopane, Jose Ricardo MacedoForage mass production in integrated, extensive and intensive livestock systems in the central region of the State of São Paulo (Massa de forragem em sistemas pecuários integrados, extensivos e intensivos na região central do Estado de São Paulo)Forage mass data from field monitoring and estimation by spectral agrometeorological modelRedapeThe forage mass is information of great importance in the management of pastures and animals in productive systems. Unfortunately, there are still no well-established and well-founded methodologies for the estimation of forage mass values ​​on a large scale, which allow its wide adoption in livestock systems and improve decision-making and management processes. In this database, we present three spreadsheets with information on the availability of forage mass in three different livestock systems: integration crop-livestock, extensive and intensive. Heights and masses (dry and fresh) are measurements taken in the field and estimates are made using the SAFER algorithm. Methods and data collection and estimates for the project study areas are described in Bayma et al. (2019) and Nogueira et al. (2021). The spreadsheet "Forage_Mass_Data_LIV_FUT" has six tabs: 1) "Sampling_points_ICLS" tab with a high resolution image of the evaluated Integrated crop-livestock systems (5 and 6) and the data sampling points (A01 to A50); 2) "Forrage_Mass_ICLS" tab is composed of columns with the following information: Sampiling data (January 2018 to November 2019), Livestock system (ICL), ICL System Repetition (repetitions 5 and 6 of the ICL System), Paddock number (6 paddocks in each repetition - from 1 to 6), Rotation management (paddocks can be in Grazing, pre-grazing, post-grazing or Grass growth), Sampling points (A01 to A50), Latitude, Longitude, Grass height (mean of 5 heights per point - in cm), Total Dry Mass (kg ha-1), Dry Green Mass (kg ha-1), Total Fresh Mass (kg ha-1), Fresh Green Mass (kg ha-1), Fresh Dead Mass (kg ha-1), Fresh Green Mass Estimation by Safer Model (kg ha-1 day-1), Forage growing days in rotation cycle and Forage growth days and Fresh Green Mass Estimation by Safer Model (kg ha-1 month-1); 3) "Sampling_points_Extensive" tab with a high resolution image of the extensive livestock systems evaluated (7 and 8) and the data sampling points (B01 to B40); 4) "Forage_Mass_Extensive" tab is composed of columns with the following information: Sampiling data (January 2018 to November 2019), Livestock system (Extensive), Extensive System Repetition (repetitions 7 and 8 of the Extensive System), Sampling points (B01 to B40), Latitude, Longitude, Grass height (mean of 5 heights per point - in cm), Total Dry Mass (kg ha-1), Dry Green Mass (kg ha-1), Total Fresh Mass (kg ha-1), Fresh Green Mass (kg ha-1), Fresh Dead Mass (kg ha-1), Fresh Green Mass Estimation by Safer Model (kg ha-1 day-1), Forage growing days in rotation cycle and Forage growth days and Fresh Green Mass Estimation by Safer Model (kg ha-1 month-1); 5) "Sampling_points_Intensive" tab with a high resolution image of the Intensive livestock systems evaluated (9 and 10) and the data collection points (C01 to C45) and 6) "Forage_Mass_Intensive" tab is composed of columns with the following information : Sampiling data (January 2018 to November 2019), Livestock system (Intensive), Intensive System Repetition (repetitions 9 and 10 of the Intensive System), Paddock number (6 paddocks in each repetition - from 1 to 6), Rotation management (paddocks can be in Grazing, pre-grazing, post-grazing or Grass growth), Sampling points (C01 to C45), Latitude, Longitude, Grass height (mean of 5 heights per point - in cm), Total Dry Mass (kg ha-1), Dry Green Mass (kg ha-1), Total Fresh Mass (kg ha-1), Fresh Green Mass (kg ha-1), Fresh Dead Mass (kg ha-1), Fresh Green Mass Estimation by Safer Model (kg ha-1 day-1), Forage growing days in rotation cycle and Forage growth days and Fresh Green Mass Estimation by Safer Model (kg ha-1 month-1).2022-03-25info:eu-repo/semantics/openAccesshttps://www.redape.dados.embrapa.br/licenses/embrapa-by-nc-4.0.xhtmlAgricultural SciencesEarth and Environmental SciencesForageForragemForage massSatellite imagerySafer agrometeorological modelEvapotranspirationRemote sensingSensor remotoDigital AgricultureAgricultura digitalAgrometeorologyAgrometeorologiaFeedsMethodsActivitiesinfo:eu-repo/semantics/datasetinfo:eu-repo/semantics/datasetinfo:eu-repo/semantics/publishedVersionDatasetreponame:Repositório de Dados de Pesquisa da EMBRAPA (Redape)instname:EMBRAPAinstacron:EMBRAPARepositório de Dados de PesquisaPUBhttps://www.redape.dados.embrapa.br/oaiopendoar:2022-12-03T05:00:01Repositório de Dados de Pesquisa da EMBRAPA (Redape) - EMBRAPAfalsedoi:10.48432/1VJD45
dc.title.none.fl_str_mv Forage mass production in integrated, extensive and intensive livestock systems in the central region of the State of São Paulo (Massa de forragem em sistemas pecuários integrados, extensivos e intensivos na região central do Estado de São Paulo)
Forage mass data from field monitoring and estimation by spectral agrometeorological model
title Forage mass production in integrated, extensive and intensive livestock systems in the central region of the State of São Paulo (Massa de forragem em sistemas pecuários integrados, extensivos e intensivos na região central do Estado de São Paulo)
spellingShingle Forage mass production in integrated, extensive and intensive livestock systems in the central region of the State of São Paulo (Massa de forragem em sistemas pecuários integrados, extensivos e intensivos na região central do Estado de São Paulo)
Nogueira, Sandra Furlan
Agricultural Sciences
Earth and Environmental Sciences
Forage
Forragem
Forage mass
Satellite imagery
Safer agrometeorological model
Evapotranspiration
Remote sensing
Sensor remoto
Digital Agriculture
Agricultura digital
Agrometeorology
Agrometeorologia
Feeds
Methods
Activities
title_short Forage mass production in integrated, extensive and intensive livestock systems in the central region of the State of São Paulo (Massa de forragem em sistemas pecuários integrados, extensivos e intensivos na região central do Estado de São Paulo)
title_full Forage mass production in integrated, extensive and intensive livestock systems in the central region of the State of São Paulo (Massa de forragem em sistemas pecuários integrados, extensivos e intensivos na região central do Estado de São Paulo)
title_fullStr Forage mass production in integrated, extensive and intensive livestock systems in the central region of the State of São Paulo (Massa de forragem em sistemas pecuários integrados, extensivos e intensivos na região central do Estado de São Paulo)
title_full_unstemmed Forage mass production in integrated, extensive and intensive livestock systems in the central region of the State of São Paulo (Massa de forragem em sistemas pecuários integrados, extensivos e intensivos na região central do Estado de São Paulo)
title_sort Forage mass production in integrated, extensive and intensive livestock systems in the central region of the State of São Paulo (Massa de forragem em sistemas pecuários integrados, extensivos e intensivos na região central do Estado de São Paulo)
author Nogueira, Sandra Furlan
author_facet Nogueira, Sandra Furlan
Bayma-Silva, Gustavo
Grego, Célia Regina
Santos, Patrícia Menezes
Pezzopane, Jose Ricardo Macedo
author_role author
author2 Bayma-Silva, Gustavo
Grego, Célia Regina
Santos, Patrícia Menezes
Pezzopane, Jose Ricardo Macedo
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Nogueira, Sandra Furlan
Bayma-Silva, Gustavo
Grego, Célia Regina
Santos, Patrícia Menezes
Pezzopane, Jose Ricardo Macedo
dc.subject.none.fl_str_mv Agricultural Sciences
Earth and Environmental Sciences
Forage
Forragem
Forage mass
Satellite imagery
Safer agrometeorological model
Evapotranspiration
Remote sensing
Sensor remoto
Digital Agriculture
Agricultura digital
Agrometeorology
Agrometeorologia
Feeds
Methods
Activities
topic Agricultural Sciences
Earth and Environmental Sciences
Forage
Forragem
Forage mass
Satellite imagery
Safer agrometeorological model
Evapotranspiration
Remote sensing
Sensor remoto
Digital Agriculture
Agricultura digital
Agrometeorology
Agrometeorologia
Feeds
Methods
Activities
description The forage mass is information of great importance in the management of pastures and animals in productive systems. Unfortunately, there are still no well-established and well-founded methodologies for the estimation of forage mass values ​​on a large scale, which allow its wide adoption in livestock systems and improve decision-making and management processes. In this database, we present three spreadsheets with information on the availability of forage mass in three different livestock systems: integration crop-livestock, extensive and intensive. Heights and masses (dry and fresh) are measurements taken in the field and estimates are made using the SAFER algorithm. Methods and data collection and estimates for the project study areas are described in Bayma et al. (2019) and Nogueira et al. (2021). The spreadsheet "Forage_Mass_Data_LIV_FUT" has six tabs: 1) "Sampling_points_ICLS" tab with a high resolution image of the evaluated Integrated crop-livestock systems (5 and 6) and the data sampling points (A01 to A50); 2) "Forrage_Mass_ICLS" tab is composed of columns with the following information: Sampiling data (January 2018 to November 2019), Livestock system (ICL), ICL System Repetition (repetitions 5 and 6 of the ICL System), Paddock number (6 paddocks in each repetition - from 1 to 6), Rotation management (paddocks can be in Grazing, pre-grazing, post-grazing or Grass growth), Sampling points (A01 to A50), Latitude, Longitude, Grass height (mean of 5 heights per point - in cm), Total Dry Mass (kg ha-1), Dry Green Mass (kg ha-1), Total Fresh Mass (kg ha-1), Fresh Green Mass (kg ha-1), Fresh Dead Mass (kg ha-1), Fresh Green Mass Estimation by Safer Model (kg ha-1 day-1), Forage growing days in rotation cycle and Forage growth days and Fresh Green Mass Estimation by Safer Model (kg ha-1 month-1); 3) "Sampling_points_Extensive" tab with a high resolution image of the extensive livestock systems evaluated (7 and 8) and the data sampling points (B01 to B40); 4) "Forage_Mass_Extensive" tab is composed of columns with the following information: Sampiling data (January 2018 to November 2019), Livestock system (Extensive), Extensive System Repetition (repetitions 7 and 8 of the Extensive System), Sampling points (B01 to B40), Latitude, Longitude, Grass height (mean of 5 heights per point - in cm), Total Dry Mass (kg ha-1), Dry Green Mass (kg ha-1), Total Fresh Mass (kg ha-1), Fresh Green Mass (kg ha-1), Fresh Dead Mass (kg ha-1), Fresh Green Mass Estimation by Safer Model (kg ha-1 day-1), Forage growing days in rotation cycle and Forage growth days and Fresh Green Mass Estimation by Safer Model (kg ha-1 month-1); 5) "Sampling_points_Intensive" tab with a high resolution image of the Intensive livestock systems evaluated (9 and 10) and the data collection points (C01 to C45) and 6) "Forage_Mass_Intensive" tab is composed of columns with the following information : Sampiling data (January 2018 to November 2019), Livestock system (Intensive), Intensive System Repetition (repetitions 9 and 10 of the Intensive System), Paddock number (6 paddocks in each repetition - from 1 to 6), Rotation management (paddocks can be in Grazing, pre-grazing, post-grazing or Grass growth), Sampling points (C01 to C45), Latitude, Longitude, Grass height (mean of 5 heights per point - in cm), Total Dry Mass (kg ha-1), Dry Green Mass (kg ha-1), Total Fresh Mass (kg ha-1), Fresh Green Mass (kg ha-1), Fresh Dead Mass (kg ha-1), Fresh Green Mass Estimation by Safer Model (kg ha-1 day-1), Forage growing days in rotation cycle and Forage growth days and Fresh Green Mass Estimation by Safer Model (kg ha-1 month-1).
publishDate 2022
dc.date.issued.fl_str_mv 2022-03-25
dc.type.openaire.fl_str_mv info:eu-repo/semantics/dataset
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.none.fl_str_mv info:eu-repo/semantics/dataset
format dataset
status_str publishedVersion
dc.identifier.url.fl_str_mv https://doi.org/10.48432/1VJD45
url https://doi.org/10.48432/1VJD45
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
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eu_rights_str_mv openAccess
rights_invalid_str_mv https://www.redape.dados.embrapa.br/licenses/embrapa-by-nc-4.0.xhtml
dc.format.none.fl_str_mv Dataset
dc.publisher.none.fl_str_mv Redape
publisher.none.fl_str_mv Redape
dc.source.none.fl_str_mv reponame:Repositório de Dados de Pesquisa da EMBRAPA (Redape)
instname:EMBRAPA
instacron:EMBRAPA
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instacron_str EMBRAPA
institution EMBRAPA
reponame_str Repositório de Dados de Pesquisa da EMBRAPA (Redape)
collection Repositório de Dados de Pesquisa da EMBRAPA (Redape)
repository.name.fl_str_mv Repositório de Dados de Pesquisa da EMBRAPA (Redape) - EMBRAPA
repository.mail.fl_str_mv
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