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| 4. |  | SILVA, Y. F.; VALADARES, R. V.; DIAS, H. B.; CUADRA, S. V.; CAMPBELL, E. E.; LAMPARELLI, R. A. C.; MORO, E.; BATTISTI, R.; ALVES, M. R.; MAGALHÃES, P. S. G.; FIGUEIREDO, G. K. D. A. Intense pasture management in Brazil in an integrated crop-livestock system simulated by the DayCent model. Sustainability, v. 14, n. 6, p. 1-24, Mar. 2022. Article 3517.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 5. | | DIAS, H. B.; CUADRA, S. V.; FIGUEIREDO, G. K. D. A.; LAMPARELLI, R. A. C.; SILVA, L. E. A.; SILVA, Y. F. da; MORO, E.; ALVES, M. R.; MAGALHÃES, P. S. G. Modelling integrated crop-livestock systems: preliminary results from an agroecosystem model. In: WORLD CONGRESS ON INTEGRATED CROP-LIVESTOCK-FORESTRY SYSTEMS, 2., 2021. Proceedings reference. Brasília, DF: Embrapa, 2021. p. 782-787. WCCLF 2021. Evento online.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 6. | | REIS, A. A. dos; SILVA, B. C.; WERNER, J. P. S.; SILVA, Y. F.; ROCHA, J. V.; FIGUEIREDO, G. K. D. A.; ANTUNES, J. F. G.; ESQUERDO, J. C. D. M.; COUTINHO, A. C.; LAMPARELLI, R. A. C; MAGALHÃES, P. S. G. Exploring the potential of high-resolution PlanetScope imagery for pasture biomass estimation in an integrated crop-livestock system. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, v. 42-3, W12, p. 419-424, 2020. Publicado também em: IEEE LATIN AMERICAN GRSS; ISPRS REMOTE SENSING CONFERENCE, Santiago, 2020. Proceedings... [Piscataway]: IEEE, 2020. p. 675-680. LAGIRS 2020.| Biblioteca(s): Embrapa Agricultura Digital. |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
17/03/2022 |
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Data da última atualização: |
17/03/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
SILVA, Y. F.; VALADARES, R. V.; DIAS, H. B.; CUADRA, S. V.; CAMPBELL, E. E.; LAMPARELLI, R. A. C.; MORO, E.; BATTISTI, R.; ALVES, M. R.; MAGALHÃES, P. S. G.; FIGUEIREDO, G. K. D. A. |
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Afiliação: |
YANE FREITAS SILVA, FEAGRI/UNICAMP; RAFAEL VASCONCELOS VALADARES, NIPE/UNICAMP; HENRIQUE BORIOLO DIAS, NIPE/UNICAMP; SANTIAGO VIANNA CUADRA, CNPTIA; ELEANOR E. CAMPBELL, UNIVERSITY OF NEW HAMPSHIRE; RUBENS AUGUSTO CAMARGO LAMPARELLI, NIPE/UNICAMP; EDEMAR MORO, UNOESTE; RAFAEL BATTISTI, UFG; MARCELO R. ALVES, UNOESTE; PAULO S. G. MAGALHÃES, NIPE/UNICAMP; GLEYCE KELLY DANTAS ARAÚJO FIGUEIREDO, FEAGRI/UNICAMP. |
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Título: |
Intense pasture management in Brazil in an integrated crop-livestock system simulated by the DayCent model. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Sustainability, v. 14, n. 6, p. 1-24, Mar. 2022. |
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DOI: |
https://doi.org/10.3390/su14063517 |
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Idioma: |
Inglês |
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Notas: |
Article 3517. |
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Conteúdo: |
Abstract. Process-based models (PBM) are important tools for understanding the benefits of Integrated Crop-Livestock Systems (ICLS), such as increasing land productivity and improving environmental conditions. PBM can provide insights into the contribution of agricultural production to climate change and help identify potential greenhouse gas (GHG) mitigation and carbon sequestration options. Rehabilitation of degraded lands is a key strategy for achieving food security goals and can reduce the need for new agricultural land. This study focused on the calibration and validation of the DayCent PBM for a typical ICLS adopted in Brazil from 2018 to 2020. We also present the DayCent parametrization for two forage species (ruzigrass and millet) grown simultaneously, bringing some innovation in the modeling challenges. We used aboveground biomass to calibrate the model, randomly selecting data from 70% of the paddocks in the study area. The calibration obtained a coefficient of determination (R2) of 0.69 and a relative RMSE of 37.0%. During the validation, we used other variables (CO2 flux, grain biomass, and soil water content) measured in the ICLS and performed a double validation for plant growth to evaluate the robustness of the model in terms of generalization. R2 validations ranged from 0.61 to 0.73, and relative RMSE from 11.3 to 48.3%. Despite the complexity and diversity of ICLS results show that DayCent can be used to model ICLS, which is an important step for future regional analyses and large-scale evaluations of the impacts of ICLS. MenosAbstract. Process-based models (PBM) are important tools for understanding the benefits of Integrated Crop-Livestock Systems (ICLS), such as increasing land productivity and improving environmental conditions. PBM can provide insights into the contribution of agricultural production to climate change and help identify potential greenhouse gas (GHG) mitigation and carbon sequestration options. Rehabilitation of degraded lands is a key strategy for achieving food security goals and can reduce the need for new agricultural land. This study focused on the calibration and validation of the DayCent PBM for a typical ICLS adopted in Brazil from 2018 to 2020. We also present the DayCent parametrization for two forage species (ruzigrass and millet) grown simultaneously, bringing some innovation in the modeling challenges. We used aboveground biomass to calibrate the model, randomly selecting data from 70% of the paddocks in the study area. The calibration obtained a coefficient of determination (R2) of 0.69 and a relative RMSE of 37.0%. During the validation, we used other variables (CO2 flux, grain biomass, and soil water content) measured in the ICLS and performed a double validation for plant growth to evaluate the robustness of the model in terms of generalization. R2 validations ranged from 0.61 to 0.73, and relative RMSE from 11.3 to 48.3%. Despite the complexity and diversity of ICLS results show that DayCent can be used to model ICLS, which is an important step for future reg... Mostrar Tudo |
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Palavras-Chave: |
Biogeochemical model; Integrated Crop-Livestock Systems; Manejo de pastagens; Mixed pasture; Modelo biogeoquímico; Pastagem tropical; Sistemas Integrados Lavoura-Pecuária; Tropical pasture. |
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Thesagro: |
Pastagem Mista; Soja; Solo Arenoso. |
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Thesaurus NAL: |
Sandy soils; Soybeans. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/232632/1/AP-Intense-Pasture-2022.pdf
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Marc: |
LEADER 02818naa a2200421 a 4500
001 2141004
005 2022-03-17
008 2022 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.3390/su14063517$2DOI
100 1 $aSILVA, Y. F.
245 $aIntense pasture management in Brazil in an integrated crop-livestock system simulated by the DayCent model.$h[electronic resource]
260 $c2022
500 $aArticle 3517.
520 $aAbstract. Process-based models (PBM) are important tools for understanding the benefits of Integrated Crop-Livestock Systems (ICLS), such as increasing land productivity and improving environmental conditions. PBM can provide insights into the contribution of agricultural production to climate change and help identify potential greenhouse gas (GHG) mitigation and carbon sequestration options. Rehabilitation of degraded lands is a key strategy for achieving food security goals and can reduce the need for new agricultural land. This study focused on the calibration and validation of the DayCent PBM for a typical ICLS adopted in Brazil from 2018 to 2020. We also present the DayCent parametrization for two forage species (ruzigrass and millet) grown simultaneously, bringing some innovation in the modeling challenges. We used aboveground biomass to calibrate the model, randomly selecting data from 70% of the paddocks in the study area. The calibration obtained a coefficient of determination (R2) of 0.69 and a relative RMSE of 37.0%. During the validation, we used other variables (CO2 flux, grain biomass, and soil water content) measured in the ICLS and performed a double validation for plant growth to evaluate the robustness of the model in terms of generalization. R2 validations ranged from 0.61 to 0.73, and relative RMSE from 11.3 to 48.3%. Despite the complexity and diversity of ICLS results show that DayCent can be used to model ICLS, which is an important step for future regional analyses and large-scale evaluations of the impacts of ICLS.
650 $aSandy soils
650 $aSoybeans
650 $aPastagem Mista
650 $aSoja
650 $aSolo Arenoso
653 $aBiogeochemical model
653 $aIntegrated Crop-Livestock Systems
653 $aManejo de pastagens
653 $aMixed pasture
653 $aModelo biogeoquímico
653 $aPastagem tropical
653 $aSistemas Integrados Lavoura-Pecuária
653 $aTropical pasture
700 1 $aVALADARES, R. V.
700 1 $aDIAS, H. B.
700 1 $aCUADRA, S. V.
700 1 $aCAMPBELL, E. E.
700 1 $aLAMPARELLI, R. A. C.
700 1 $aMORO, E.
700 1 $aBATTISTI, R.
700 1 $aALVES, M. R.
700 1 $aMAGALHÃES, P. S. G.
700 1 $aFIGUEIREDO, G. K. D. A.
773 $tSustainability$gv. 14, n. 6, p. 1-24, Mar. 2022.
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