| |
|
|
 | Acesso ao texto completo restrito à biblioteca da Embrapa Pecuária Sudeste. Para informações adicionais entre em contato com cppse.biblioteca@embrapa.br. |
|
Registro Completo |
|
Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Pecuária Sudeste. |
|
Data corrente: |
03/06/2024 |
|
Data da última atualização: |
20/08/2024 |
|
Tipo da produção científica: |
Artigo em Periódico Indexado |
|
Autoria: |
SANTOS, M. L. dos; SANTOS, P. M.; BARIONI, L. G.; PEREIRA, B. H.; CUADRA, S. V.; PEQUENO, D. N. L.; MARIN, F. R.; SOLLENBERGER, L. |
|
Afiliação: |
MARIELY LOPES DOS SANTOS, UNIVERSIDADE DE SÃO PAULO; PATRICIA MENEZES SANTOS, CPPSE; LUIS GUSTAVO BARIONI, CNPTIA; BRUNO HENRIQUE PEREIRA, FUNDAÇÃO ARTHUR BERNARDES; SANTIAGO VIANNA CUADRA, CNPTIA; DIEGO NOLETO LUZ PEQUENO, INTERNATIONAL MAIZE AND WHEAT IMPROVEMENT CENTER; FÁBIO RICARDO MARIN, UNIVERSIDADE DE SÃO PAULO; LYNN SOLLENBERGER, UNIVERSITY OF FLORIDA. |
|
Título: |
Yield gap analysis framework applied to pasture-based livestock systems in Central Brazil. |
|
Ano de publicação: |
2024 |
|
Fonte/Imprenta: |
Field Crops Research, v. 314, 109416, 2024. |
|
ISSN: |
0378-4290 |
|
DOI: |
https://doi.org/10.1016/j.fcr.2024.109416 |
|
Idioma: |
Inglês |
|
Conteúdo: |
Abstract: Context or problem: Yield gap analyses for livestock systems may utilize different approaches, including mathematical models based on pasture carrying capacity concepts. Protocols typically used to estimate pasture carrying capacity in Brazil do not consider adequately the seasonal variability of forage production, mismatching the estimates of demand and supply. Objective or research question: This study aimed to develop a protocol based on the concept of pasture carrying capacity for yield gap analysis of pasture-based beef cattle production systems on a regional scale and apply the protocol to estimate yield gap on pasture-based beef cattle systems in Central Brazil. Methods: The framework gathered techniques such as homogeneous climatic zones definition; systematization of primary data with weather and soil information to run the models; scenario definition and assumptions; adaptation of the forage model to run long-term simulations; use of a pasture carrying capacity model, which estimates maximum (carrying capacity of systems with variable stocking rate) and critical stocking rates (carrying capacity limited by seasonal and interannual variability of forage production); and the use of national agricultural census databases to estimate actual stocking rate and calculate yield gaps. The protocol was applied to pasture-based beef cattle production systems under different management scenarios in Central Brazil. Results: The maximum forage production and stocking rate increased with nitrogen fertilization and water availability. However, under cooler temperatures during winter months, forage production and critical stocking rates were less responsive to these factors. Mean yield gap for maximum stocking rate (difference between maximum and actual stocking rate) ranged from 5.81 to 5.12 animal units per hectare (AU ha−1) in the potential scenario, 4.18–2.9 AU ha−1 in the water-limited, and 2.73–1.43 AU ha−1 in the attainable scenario, while mean yield gap for critical stocking rate (difference between critical and actual stocking rate) varied from 5.44 AU ha−1 to 2.91 AU ha−1 in the potential scenario, 1.21–0 AU ha−1 in the water-limited, and 1.04–0 AU ha−1 in the attainable scenario. Conclusions: Yield gap analysis of pasture-based beef cattle systems can be performed using long-term forage production simulations coupled with a model based on cumulative forage deficits to determine stocking rate metrics. Implications or significance: The protocol allowed the identification and quantification of the gap size due to interaction of the main factors influencing forage production and pasture carrying capacity under several environmental and management conditions, and may be applied to support policy and investment decisions. MenosAbstract: Context or problem: Yield gap analyses for livestock systems may utilize different approaches, including mathematical models based on pasture carrying capacity concepts. Protocols typically used to estimate pasture carrying capacity in Brazil do not consider adequately the seasonal variability of forage production, mismatching the estimates of demand and supply. Objective or research question: This study aimed to develop a protocol based on the concept of pasture carrying capacity for yield gap analysis of pasture-based beef cattle production systems on a regional scale and apply the protocol to estimate yield gap on pasture-based beef cattle systems in Central Brazil. Methods: The framework gathered techniques such as homogeneous climatic zones definition; systematization of primary data with weather and soil information to run the models; scenario definition and assumptions; adaptation of the forage model to run long-term simulations; use of a pasture carrying capacity model, which estimates maximum (carrying capacity of systems with variable stocking rate) and critical stocking rates (carrying capacity limited by seasonal and interannual variability of forage production); and the use of national agricultural census databases to estimate actual stocking rate and calculate yield gaps. The protocol was applied to pasture-based beef cattle production systems under different management scenarios in Central Brazil. Results: The maximum forage production and stocking r... Mostrar Tudo |
|
Palavras-Chave: |
Framework; Grazing risk; Modelagem. |
|
Thesagro: |
Capacidade de Suporte; Gado de Corte; Pastejo; Risco; Taxa de Lotação. |
|
Thesaurus Nal: |
Beef cattle; Carrying capacity; Grazing; Pastures; Risk; Stocking rate. |
|
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
|
Marc: |
LEADER 03903naa a2200397 a 4500
001 2164629
005 2024-08-20
008 2024 bl uuuu u00u1 u #d
022 $a0378-4290
024 7 $ahttps://doi.org/10.1016/j.fcr.2024.109416$2DOI
100 1 $aSANTOS, M. L. dos
245 $aYield gap analysis framework applied to pasture-based livestock systems in Central Brazil.$h[electronic resource]
260 $c2024
520 $aAbstract: Context or problem: Yield gap analyses for livestock systems may utilize different approaches, including mathematical models based on pasture carrying capacity concepts. Protocols typically used to estimate pasture carrying capacity in Brazil do not consider adequately the seasonal variability of forage production, mismatching the estimates of demand and supply. Objective or research question: This study aimed to develop a protocol based on the concept of pasture carrying capacity for yield gap analysis of pasture-based beef cattle production systems on a regional scale and apply the protocol to estimate yield gap on pasture-based beef cattle systems in Central Brazil. Methods: The framework gathered techniques such as homogeneous climatic zones definition; systematization of primary data with weather and soil information to run the models; scenario definition and assumptions; adaptation of the forage model to run long-term simulations; use of a pasture carrying capacity model, which estimates maximum (carrying capacity of systems with variable stocking rate) and critical stocking rates (carrying capacity limited by seasonal and interannual variability of forage production); and the use of national agricultural census databases to estimate actual stocking rate and calculate yield gaps. The protocol was applied to pasture-based beef cattle production systems under different management scenarios in Central Brazil. Results: The maximum forage production and stocking rate increased with nitrogen fertilization and water availability. However, under cooler temperatures during winter months, forage production and critical stocking rates were less responsive to these factors. Mean yield gap for maximum stocking rate (difference between maximum and actual stocking rate) ranged from 5.81 to 5.12 animal units per hectare (AU ha−1) in the potential scenario, 4.18–2.9 AU ha−1 in the water-limited, and 2.73–1.43 AU ha−1 in the attainable scenario, while mean yield gap for critical stocking rate (difference between critical and actual stocking rate) varied from 5.44 AU ha−1 to 2.91 AU ha−1 in the potential scenario, 1.21–0 AU ha−1 in the water-limited, and 1.04–0 AU ha−1 in the attainable scenario. Conclusions: Yield gap analysis of pasture-based beef cattle systems can be performed using long-term forage production simulations coupled with a model based on cumulative forage deficits to determine stocking rate metrics. Implications or significance: The protocol allowed the identification and quantification of the gap size due to interaction of the main factors influencing forage production and pasture carrying capacity under several environmental and management conditions, and may be applied to support policy and investment decisions.
650 $aBeef cattle
650 $aCarrying capacity
650 $aGrazing
650 $aPastures
650 $aRisk
650 $aStocking rate
650 $aCapacidade de Suporte
650 $aGado de Corte
650 $aPastejo
650 $aRisco
650 $aTaxa de Lotação
653 $aFramework
653 $aGrazing risk
653 $aModelagem
700 1 $aSANTOS, P. M.
700 1 $aBARIONI, L. G.
700 1 $aPEREIRA, B. H.
700 1 $aCUADRA, S. V.
700 1 $aPEQUENO, D. N. L.
700 1 $aMARIN, F. R.
700 1 $aSOLLENBERGER, L.
773 $tField Crops Research$gv. 314, 109416, 2024.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Pecuária Sudeste (CPPSE) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
|
|
|
| Registros recuperados : 1 | |
| 1. |  | CAMARGO, L. M. P. C. de A.; MARTINS, J. F. da S.; SCHMIDT, N. C.; CAMARGO, O. B. A.; TOLEDO, N. M. P. de. Levantamento de insetos em algumas variedades de arroz. In: REUNIÃO NACIONAL DE PESQUISA DE ARROZ, 3., 1987, Goiânia. Anais... Goiânia: EMBRAPA-CNPAF, 1991. p. 367-420. (EMBRAPA-CNPAF. Documentos, 25).| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Arroz e Feijão. |
|    |
| Registros recuperados : 1 | |
|
| Nenhum registro encontrado para a expressão de busca informada. |
|
|
