Data/hora: 26/05/2024 18:07:55

Biblioteca(s): 	Embrapa Pecuária Sudeste.	
Data corrente: 	28/11/2013	
Data da última atualização: 	10/03/2023	
Autoria: 	PEZZOPANE, J. R. M.; CRUZ, P. G. da; SANTOS, P. M.; BOSI, C.; ARAUJO, L. C. de.	
Afiliação: 	JOSE RICARDO MACEDO PEZZOPANE, CPPSE; PEDRO GOMES DA CRUZ, Federal Institute of Education, Science and Technology Goiano; PATRICIA MENEZES SANTOS, CPPSE; CRISTIAM BOSI, Luiz de Queiroz, College of Agriculture, University of São Paulo; LEANDRO COELHO DE ARAUJO, Universidade Estadual Paulista.	
Título: 	Simple agrometeorological models for estimating Guineagrass yield in Southeast Brazil.	
Ano de publicação: 	2014	
Fonte/Imprenta: 	International Journal of Biometeorology, v. 58, p. 1479-1487, 2014.	
DOI: 	10.1007/s00484-013-0751-y	
Idioma: 	Inglês	
Conteúdo: 	The objective of this work was to develop and evaluate agrometeorological models to simulate the production of Guineagrass. For this purpose, we used forage yield from 54 growing periods between December 2004 ? January 2007 and April 2010? March 2012 in irrigated and non-irrigated pastures in São Carlos, São Paulo state, Brazil (latitude 21°57'42'' S, longitude 47°50'28'' W and altitude 860 m). Initially we performed linear regressions between the agrometeorological variables and the average dry matter accumulation rate for irrigated conditions. Then we determined the effect of soil water availability on the relative forage yield considering irrigated and non-irrigated pastures, bymeans of segmented linearregressionamong water balance and relative production variables (dry matter accumulation rates with and without irrigation). The models generated were evaluated with independent data related to 21 growing periods without irrigation in the same location, from eight growing periods in 2000 and 13 growing periods between December 2004 ? January 2007 and April 2010 ? March 2012. The results obtained show the satisfactory predictive capacity of the agrometeorological models under irrigated conditions based on univariate regression (mean temperature, minimum temperature and potential evapotranspiration or degreedays) or multivariate regression. The response of irrigation on production was well correlated with the climatological water balance variables (ratio between actual and potential evapotranspiration or between actual and maximum soil water storage). The models that performed best for estimating Guineagrass yield without irrigation were based on minimum temperature corrected by relative soil water storage, determined by the ratio between the actual soil water storage and the soil water holding capacity.irrigation in the same location, in 2000, 2010 and 2011. The results obtained show the satisfactory predictive capacity of the agrometeorological models under irrigated conditions based on univariate regression (mean temperature, potential evapotranspiration or degree-days) or multivariate regression. The response of irrigation on production was well correlated with the climatological water balance variables (ratio between actual and potential evapotranspiration or between actual and maximum soil water storage). The models that performed best for estimating Guineagrass yield without irrigation were based on degree-days corrected by the water deficit factor.	
Palavras-Chave: 	Degre day; Modelling.	
Thesagro: 	Panicum Maximum.	
Thesaurus Nal: 	air temperature; water balance.	
Categoria do assunto: 	F Plantas e Produtos de Origem Vegetal	
Registro original: 	Embrapa Pecuária Sudeste (CPPSE)	
Exemplares: 	CPPSE - (22214-1) - UPC - AP - DD - PROCI-2013.00180 - PEZ - 2013.00180 - DIS