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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 Pecuária Sudeste. |
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Data corrente: |
12/12/2012 |
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Data da última atualização: |
16/02/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
ARAUJO, L. C.; SANTOS, P. M.; RODRIGUEZ, D.; PEZZOPANE, J. R. M.; OLIVEIRA, P. P. A.; CRUZ, P. G. |
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Afiliação: |
LEANDRO C. ARAUJO, ZOOTECNIA EALQ/PIRACICABA; PATRICIA MENEZES SANTOS, CPPSE; DANIEL RODRIGUEZ, Univ. of Queensland; JOSE RICARDO MACEDO PEZZOPANE, CPPSE; PATRICIA PERONDI ANCHAO OLIVEIRA, CPPSE; PEDRO G. CRUZ, ESALQ/PIRACICABA. |
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Título: |
Simulating Guinea Grass production: empirical and mechanistic approaches. |
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Ano de publicação: |
2013 |
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Fonte/Imprenta: |
Agronomy Journal, v. 105, n. 1, 2013. |
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Páginas: |
p. 61-69. |
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DOI: |
https://doi.org/10.2134/agronj2012.0245 |
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Idioma: |
Inglês |
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Conteúdo: |
Tropical grasses are economically important for cattle production in Brazil and accurate simulation models for tropical pastures can benefit forage researchers and farm managers improve tropical forage production systems. This research calibrated and validated four modeling approaches of contrasting complexity to simulate mass production of Guineagrass (Panicum maximum Jacq. cv. ?Mombaça?). The models included three empirical agro-climatic models [i.e. a cumulative degree-day (DDi), a photo-thermal-units (PUi), and a climatic growth index (CGIi)]; and a bio-physical simulation model i.e. APSIM-Growth. Data sets for calibration and independent validation included records of frequent above-ground dry matter production over the 2005-2006 and 2010-2011 growing seasons from three trials. All models performed well during calibration (R2 = 0.78 - 0.86; and coefficient of variation = 26 - 32.1%). During model validation the R2 varied between 0.69 and 0.78; the agreement index was between 0.88 and 0.93; the coefficient of variation between 37.6 and 50.2%; and the mean bias error between 6 and 470 kg ha-1. Even though all models were in agreement between simulated and observed results, APSIM-Growth was able to simulate Guineagrass production across a broader climate range, soils and management (i.e. nitrogen fertilization) conditions. |
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Palavras-Chave: |
Guinegrass production; Tropical pasture. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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Marc: |
LEADER 02021naa a2200229 a 4500
001 1942184
005 2023-02-16
008 2013 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.2134/agronj2012.0245$2DOI
100 1 $aARAUJO, L. C.
245 $aSimulating Guinea Grass production$bempirical and mechanistic approaches.$h[electronic resource]
260 $c2013
300 $ap. 61-69.
520 $aTropical grasses are economically important for cattle production in Brazil and accurate simulation models for tropical pastures can benefit forage researchers and farm managers improve tropical forage production systems. This research calibrated and validated four modeling approaches of contrasting complexity to simulate mass production of Guineagrass (Panicum maximum Jacq. cv. ?Mombaça?). The models included three empirical agro-climatic models [i.e. a cumulative degree-day (DDi), a photo-thermal-units (PUi), and a climatic growth index (CGIi)]; and a bio-physical simulation model i.e. APSIM-Growth. Data sets for calibration and independent validation included records of frequent above-ground dry matter production over the 2005-2006 and 2010-2011 growing seasons from three trials. All models performed well during calibration (R2 = 0.78 - 0.86; and coefficient of variation = 26 - 32.1%). During model validation the R2 varied between 0.69 and 0.78; the agreement index was between 0.88 and 0.93; the coefficient of variation between 37.6 and 50.2%; and the mean bias error between 6 and 470 kg ha-1. Even though all models were in agreement between simulated and observed results, APSIM-Growth was able to simulate Guineagrass production across a broader climate range, soils and management (i.e. nitrogen fertilization) conditions.
653 $aGuinegrass production
653 $aTropical pasture
700 1 $aSANTOS, P. M.
700 1 $aRODRIGUEZ, D.
700 1 $aPEZZOPANE, J. R. M.
700 1 $aOLIVEIRA, P. P. A.
700 1 $aCRUZ, P. G.
773 $tAgronomy Journal$gv. 105, n. 1, 2013.
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Registro original: |
Embrapa Pecuária Sudeste (CPPSE) |
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Biblioteca |
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Cutter |
Registro |
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URL |
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Registro Completo
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Biblioteca(s): |
Embrapa Meio Ambiente. |
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Data corrente: |
12/01/2009 |
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Data da última atualização: |
31/08/2016 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
BETTIOL, W.; PINTO, Z. V. |
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Afiliação: |
WAGNER BETTIOL, CNPMA; ZAYAME VEGETTE PINTO, FCA-UNESP. |
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Título: |
Control of Fusarium in Chrysanthemum with sewage sludge, biofertilizer, hydrolyzed fish, chitosan and Trichoderma. |
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Ano de publicação: |
2008 |
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Fonte/Imprenta: |
In: MEETING OF THE WORKING GROUP "BIOLOGICAL CONTROL OF FUNGAL AND BACTERIAL PLANT PATHOGENS", 10., 2008, Interlaken. Molecular tools for understanding and improving biocontrol: abstract book. Interlaken: IOBC-WPRS, 2008. p.50. |
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Idioma: |
Inglês |
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Palavras-Chave: |
Controle alternativo. |
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Thesagro: |
Adubo de esgoto; Biofertilizante; Crisântemo; Fusariose; Lodo residual. |
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Categoria do assunto: |
H Saúde e Patologia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/146984/1/2008RA-085.pdf
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Marc: |
LEADER 00768nam a2200181 a 4500
001 1016185
005 2016-08-31
008 2008 bl uuuu u00u1 u #d
100 1 $aBETTIOL, W.
245 $aControl of Fusarium in Chrysanthemum with sewage sludge, biofertilizer, hydrolyzed fish, chitosan and Trichoderma.$h[electronic resource]
260 $aIn: MEETING OF THE WORKING GROUP "BIOLOGICAL CONTROL OF FUNGAL AND BACTERIAL PLANT PATHOGENS", 10., 2008, Interlaken. Molecular tools for understanding and improving biocontrol: abstract book. Interlaken: IOBC-WPRS, 2008. p.50.$c2008
650 $aAdubo de esgoto
650 $aBiofertilizante
650 $aCrisântemo
650 $aFusariose
650 $aLodo residual
653 $aControle alternativo
700 1 $aPINTO, Z. V.
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Embrapa Meio Ambiente (CNPMA) |
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