Data/hora: 23/06/2024 01:15:03

Biblioteca(s): 	Embrapa Agricultura Digital.	
Data corrente: 	28/01/1999	
Data da última atualização: 	28/03/2019	
Autoria: 	COLSON, J.; WALLACH, D.; BOUNIOLS, A.; DENIS, J.-B.; JONES, J. W.	
Afiliação: 	JOSIANNE COLSON, INRA; DANIEL WALLACH, INRA; ANDRÉE BOUNIOLS, INRA; JEAN-BAPTISTE DENIS, INRA; JAMES W. JONES, University of Florida.	
Título: 	Mean squared error of yield prediction by SOYGRO.	
Ano de publicação: 	1995	
Fonte/Imprenta: 	Agronomy Journal, v. 87, n. 3, p. 397-402, May-June 1995.	
DOI: 	10.2134/agronj1995.00021962008700030002x	
Idioma: 	Inglês	
Conteúdo: 	Yield prediction is often one of the major intended uses of a crop simulation model. It is therefore important to evaluate how well a model performs as a predictor. The purpose of this study was to evaluate and analyze how well the SOYGRO model predicts soybean yield, using as a criterion the mean squared error of prediction (MSEP). The four target populations for prediction were irrigated or unirrigated plots at one location in France, for each of two varieties. The model parameters are estimated from the irrigated plots. The estimated MSEP values are on the order of I(t ha-1)2 for all the target populations. For comparison, we defined an AVERAGE model. This model uses the average observed irrigated yield for each cultivar as the predictor of unobserved yields. AVERAGE was a better predictor than SOYGRO for the irrigated populations, while SOYGRO was better for the unirrigated populations. It seems that SOYGRO has sufficient built-in biological realism to extrapolate more reasonably than the AVERAGE model from irrigated to unirrigated conditions; however, SOYGRO does not make as effective use of the data used for parameter estimation as does AVERAGE.	
Palavras-Chave: 	Crop modeling; Modelagem; SOYGRO model; Yield prediction.	
Categoria do assunto: 	--	
Registro original: 	Embrapa Agricultura Digital (CNPTIA)	
Exemplares: 	CNPTIA - (7583-1) - ADC - SP - PP -  -  - 1999.00017 - DES
CNPTIA - (7583-2) - ADC - AP - DD -  -  -  - DIS