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| Registros recuperados : 38 | |
| 5. |  | BOOTE, K. J.; JONES, J. W.; HOOGENBOOM, G. Simulating growth and yield response of soybean to temperature and photoperiod. In: CONFERENCIA MUNDIAL DE INVESTIGACION EN SOJA, 4., 1989, Actas... Buenos Aires, A A soja, 1989, v. , p. 272-278, 1989.| Biblioteca(s): Embrapa Trigo. |
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| 18. | | JONES, P.; ALLEN JR, L. H.; JONES, J. W.; BOOTE, K. J.; CAMPBELL, W. J. Soybean canopy growth, photosynthesis, and transpiration responses to whole-season carbon dioxide enrichment. Agron. J., v. 76, n. 4, p. 633-637, 1984.| Biblioteca(s): Embrapa Agrobiologia. |
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| Registros recuperados : 38 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Semiárido. Para informações adicionais entre em contato com cpatsa.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Semiárido. |
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Data corrente: |
11/01/2018 |
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Data da última atualização: |
11/01/2018 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
SANTOS, R. D. dos; BOOTE, K. J.; SOLLENBERGER, L. E.; NEVES, A. L. A.; PEREIRA, L. G. R.; SCHERER, C. B.; GONÇALVES, L. C. |
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Afiliação: |
RAFAEL DANTAS DOS SANTOS, CPATSA; KENNETH J. BOOTE, University of Florida, Gainesville, FL; LYNN E. SOLLENBERGER, University of Florida, Gainesville, FL; ANDRE LUIS ALVES NEVES, CNPGL; LUIZ GUSTAVO RIBEIRO PEREIRA, CNPGL; CAROLINA B. SCHERER, UFMG; LUCIO C. GONÇALVES, UFMG. |
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Título: |
Simulated optimum sowing date for forage pearl millet cultivars in multilocation trials in Brazilian Semi-Arid region. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
Frontiers in Plant Science, v. 8, p. 1-11, 2017. |
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DOI: |
10.3389/fpls.2017.02074 |
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Idioma: |
Inglês |
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Conteúdo: |
Forage production is primarily limited by weather conditions under dryland production systems in Brazilian semi-arid regions, therefore sowing at the appropriate time is critical. The objectives of this study were to evaluate the CSM-CERES-Pearl Millet model from the DSSAT software suite for its ability to simulate growth, evelopment, and forage accumulation of pearl millet [Pennisetum glaucum (L.) R.] at three Brazilian semi-arid locations, and to use the model to study the impact of different sowing dates on pearl millet performance for forage. Four pearl millet cultivars were grown during the 2011 rainy season in field experiments conducted at three Brazilian semi-arid locations, under rainfed conditions. The genetic coefficients of the four pearl millet cultivars were calibrated for the model, and the model erformance was evaluated with experimental data. The model was run for 14 sowing dates using long-term historical weather data from three locations, to determine the optimum sowing window. Results showed that performance of the model was satisfactory as indicated by accurate simulation of crop phenology and forage accumulation against measured data. The optimum sowing window varied among locations depending on rainfall patterns, although showing the same trend for cultivars within the site. The best sowing windows were from 15 April to 15 May for the Bom Conselho location; 12 April to 02 May for Nossa Senhora da Gloria; and 17 April to 25 May for Sao Bento do Una. The model can be used as a tool to evaluate the effect of sowing date on forage pearl millet performance in Brazilian semi-arid conditions. MenosForage production is primarily limited by weather conditions under dryland production systems in Brazilian semi-arid regions, therefore sowing at the appropriate time is critical. The objectives of this study were to evaluate the CSM-CERES-Pearl Millet model from the DSSAT software suite for its ability to simulate growth, evelopment, and forage accumulation of pearl millet [Pennisetum glaucum (L.) R.] at three Brazilian semi-arid locations, and to use the model to study the impact of different sowing dates on pearl millet performance for forage. Four pearl millet cultivars were grown during the 2011 rainy season in field experiments conducted at three Brazilian semi-arid locations, under rainfed conditions. The genetic coefficients of the four pearl millet cultivars were calibrated for the model, and the model erformance was evaluated with experimental data. The model was run for 14 sowing dates using long-term historical weather data from three locations, to determine the optimum sowing window. Results showed that performance of the model was satisfactory as indicated by accurate simulation of crop phenology and forage accumulation against measured data. The optimum sowing window varied among locations depending on rainfall patterns, although showing the same trend for cultivars within the site. The best sowing windows were from 15 April to 15 May for the Bom Conselho location; 12 April to 02 May for Nossa Senhora da Gloria; and 17 April to 25 May for Sao Bento do Una. The... Mostrar Tudo |
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Palavras-Chave: |
Alimentação animal; Cultivars competition; Dry lands; DSSAT; Pasture; Rainfed agriculture. |
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Thesagro: |
Forragem; Mudança climática; Nutrição animal; Pastagem. |
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Thesaurus NAL: |
Climate change; Crop models. |
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Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
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Marc: |
LEADER 02655naa a2200349 a 4500
001 2085031
005 2018-01-11
008 2017 bl uuuu u00u1 u #d
024 7 $a10.3389/fpls.2017.02074$2DOI
100 1 $aSANTOS, R. D. dos
245 $aSimulated optimum sowing date for forage pearl millet cultivars in multilocation trials in Brazilian Semi-Arid region.$h[electronic resource]
260 $c2017
520 $aForage production is primarily limited by weather conditions under dryland production systems in Brazilian semi-arid regions, therefore sowing at the appropriate time is critical. The objectives of this study were to evaluate the CSM-CERES-Pearl Millet model from the DSSAT software suite for its ability to simulate growth, evelopment, and forage accumulation of pearl millet [Pennisetum glaucum (L.) R.] at three Brazilian semi-arid locations, and to use the model to study the impact of different sowing dates on pearl millet performance for forage. Four pearl millet cultivars were grown during the 2011 rainy season in field experiments conducted at three Brazilian semi-arid locations, under rainfed conditions. The genetic coefficients of the four pearl millet cultivars were calibrated for the model, and the model erformance was evaluated with experimental data. The model was run for 14 sowing dates using long-term historical weather data from three locations, to determine the optimum sowing window. Results showed that performance of the model was satisfactory as indicated by accurate simulation of crop phenology and forage accumulation against measured data. The optimum sowing window varied among locations depending on rainfall patterns, although showing the same trend for cultivars within the site. The best sowing windows were from 15 April to 15 May for the Bom Conselho location; 12 April to 02 May for Nossa Senhora da Gloria; and 17 April to 25 May for Sao Bento do Una. The model can be used as a tool to evaluate the effect of sowing date on forage pearl millet performance in Brazilian semi-arid conditions.
650 $aClimate change
650 $aCrop models
650 $aForragem
650 $aMudança climática
650 $aNutrição animal
650 $aPastagem
653 $aAlimentação animal
653 $aCultivars competition
653 $aDry lands
653 $aDSSAT
653 $aPasture
653 $aRainfed agriculture
700 1 $aBOOTE, K. J.
700 1 $aSOLLENBERGER, L. E.
700 1 $aNEVES, A. L. A.
700 1 $aPEREIRA, L. G. R.
700 1 $aSCHERER, C. B.
700 1 $aGONÇALVES, L. C.
773 $tFrontiers in Plant Science$gv. 8, p. 1-11, 2017.
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