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 | Acesso ao texto completo restrito à biblioteca da Embrapa Pecuária Sudeste. Para informações adicionais entre em contato com cppse.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Pecuária Sudeste. |
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Data corrente: |
26/07/2022 |
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Data da última atualização: |
05/08/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
SANTOS, M. L. dos; SANTOS, P. M.; BOOTE, K. J.; PEQUENO, D. N. L.; BARIONI, L. G.; CUADRA, S. V.; HOOGENBOOM, G. |
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Afiliação: |
MARIELY LOPES DOS SANTOS, ESALQ/USP, University of Florida; PATRICIA MENEZES SANTOS, CPPSE; KENNETH JAY BOOTE, UNIVERSITY OF FLORIDA; DIEGO NOLETO LUZ PEQUENO, INTERNATIONAL MAIZE AND WHEAT IMPROVEMENT CENTER; LUIS GUSTAVO BARIONI, CNPTIA; SANTIAGO VIANNA CUADRA, CNPTIA; GERRIT HOOGENBOOM, University of Florida. |
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Título: |
Applying the CROPGRO Perennial Forage Model for long-term estimates of Marandu palisadegrass production in livestock management scenarios in Brazil. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Field Crops Research, v. 286, 108629, Oct. 2022. |
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Páginas: |
16 p. |
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DOI: |
https://doi.org/10.1016/j.fcr.2022.108629 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract. The use of long-term forage production simulation is important to studies of strategic scenarios, yield-gap predictions and production risk analysis. However, forage models have only been tested using short period data. Therefore, this study aimed to apply the CROPGRO Perennial Forage Model (CROPGRO-PFM), a mechanistic model from Decision Support System for Agrotechnology Transfer (DSSAT) platform, to simulate long-term forage production of Marandu palisadegrass {Urochloa brizantha (Hochst. ex A. Rich.) R.D. Webster [syn. Brachiaria brizantha (Hochst. ex A. Rich.) Stapf]} in different locations of Central Brazil, under different fertilization levels. We chose nine locations distributed in Amazon, Cerrado, and Atlantic Forest Biomes to simulate Marandu palisadegrass production over 36 years (1980?2016). The simulations were carried out using prior calibrations for DSSAT?s CROPGRO-PFM and, as a reference point of growth and herbage simulation, model results were initially contrasted against an agrometeorological model, the Integrated Agrometeorological Model (IAM), to check the consistency between these two different models. Then the CROPGRO-PFM was applied to simulated scenarios represented three beef cattle livestock production systems: (1) Potential production water-not-limiting and highly fertilized, (2) rainfed with high N fertilization, and (3) rainfed with low N maintenance fertilization. In general, the long-term simulations of annual forage production and seasonality were similar for the CROPGRO-PFM and IAM models. As expected for the Central Brazil region, historical averages of monthly herbage accumulation rate of potential yield scenarios were relatively constant throughout the year, declining in the winter period for most locations due to mild temperature reduction and decline of solar radiation. In general, rainfed scenarios simulations showed a seasonal cycle following the rainfall pattern, with reduction in growth rates in the dry season. During the winter season climate is the major limiting growth factor, simulated growth rates were low and similar regardless of N fertilization. Although the CROPGRO-PFM presented consistent results for long term grazing systems, further model changes, calibration, and validations are recommended to improve the process-based model as well as the knowledge about these systems. MenosAbstract. The use of long-term forage production simulation is important to studies of strategic scenarios, yield-gap predictions and production risk analysis. However, forage models have only been tested using short period data. Therefore, this study aimed to apply the CROPGRO Perennial Forage Model (CROPGRO-PFM), a mechanistic model from Decision Support System for Agrotechnology Transfer (DSSAT) platform, to simulate long-term forage production of Marandu palisadegrass {Urochloa brizantha (Hochst. ex A. Rich.) R.D. Webster [syn. Brachiaria brizantha (Hochst. ex A. Rich.) Stapf]} in different locations of Central Brazil, under different fertilization levels. We chose nine locations distributed in Amazon, Cerrado, and Atlantic Forest Biomes to simulate Marandu palisadegrass production over 36 years (1980?2016). The simulations were carried out using prior calibrations for DSSAT?s CROPGRO-PFM and, as a reference point of growth and herbage simulation, model results were initially contrasted against an agrometeorological model, the Integrated Agrometeorological Model (IAM), to check the consistency between these two different models. Then the CROPGRO-PFM was applied to simulated scenarios represented three beef cattle livestock production systems: (1) Potential production water-not-limiting and highly fertilized, (2) rainfed with high N fertilization, and (3) rainfed with low N maintenance fertilization. In general, the long-term simulations of annual forage production and se... Mostrar Tudo |
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Palavras-Chave: |
Growth; Herbage production; Modelagem; Produção de ervas; Simulação de produção de forragem. |
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Thesagro: |
Crescimento; Gado de Corte; Modelo de Simulação; Simulação. |
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Thesaurus Nal: |
Beef cattle; Models; Simulation models; Urochloa brizantha. |
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Categoria do assunto: |
--
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 03510naa a2200373 a 4500
001 2145272
005 2022-08-05
008 2022 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.fcr.2022.108629$2DOI
100 1 $aSANTOS, M. L. dos
245 $aApplying the CROPGRO Perennial Forage Model for long-term estimates of Marandu palisadegrass production in livestock management scenarios in Brazil.$h[electronic resource]
260 $c2022
300 $a16 p.
520 $aAbstract. The use of long-term forage production simulation is important to studies of strategic scenarios, yield-gap predictions and production risk analysis. However, forage models have only been tested using short period data. Therefore, this study aimed to apply the CROPGRO Perennial Forage Model (CROPGRO-PFM), a mechanistic model from Decision Support System for Agrotechnology Transfer (DSSAT) platform, to simulate long-term forage production of Marandu palisadegrass {Urochloa brizantha (Hochst. ex A. Rich.) R.D. Webster [syn. Brachiaria brizantha (Hochst. ex A. Rich.) Stapf]} in different locations of Central Brazil, under different fertilization levels. We chose nine locations distributed in Amazon, Cerrado, and Atlantic Forest Biomes to simulate Marandu palisadegrass production over 36 years (1980?2016). The simulations were carried out using prior calibrations for DSSAT?s CROPGRO-PFM and, as a reference point of growth and herbage simulation, model results were initially contrasted against an agrometeorological model, the Integrated Agrometeorological Model (IAM), to check the consistency between these two different models. Then the CROPGRO-PFM was applied to simulated scenarios represented three beef cattle livestock production systems: (1) Potential production water-not-limiting and highly fertilized, (2) rainfed with high N fertilization, and (3) rainfed with low N maintenance fertilization. In general, the long-term simulations of annual forage production and seasonality were similar for the CROPGRO-PFM and IAM models. As expected for the Central Brazil region, historical averages of monthly herbage accumulation rate of potential yield scenarios were relatively constant throughout the year, declining in the winter period for most locations due to mild temperature reduction and decline of solar radiation. In general, rainfed scenarios simulations showed a seasonal cycle following the rainfall pattern, with reduction in growth rates in the dry season. During the winter season climate is the major limiting growth factor, simulated growth rates were low and similar regardless of N fertilization. Although the CROPGRO-PFM presented consistent results for long term grazing systems, further model changes, calibration, and validations are recommended to improve the process-based model as well as the knowledge about these systems.
650 $aBeef cattle
650 $aModels
650 $aSimulation models
650 $aUrochloa brizantha
650 $aCrescimento
650 $aGado de Corte
650 $aModelo de Simulação
650 $aSimulação
653 $aGrowth
653 $aHerbage production
653 $aModelagem
653 $aProdução de ervas
653 $aSimulação de produção de forragem
700 1 $aSANTOS, P. M.
700 1 $aBOOTE, K. J.
700 1 $aPEQUENO, D. N. L.
700 1 $aBARIONI, L. G.
700 1 $aCUADRA, S. V.
700 1 $aHOOGENBOOM, G.
773 $tField Crops Research$gv. 286, 108629, Oct. 2022.
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