Data/hora: 12/06/2024 14:26:42

Provedor de dados: 	89	
País: 	Brazil	
Título: 	Relationship between color and tannin content in sorghum grain: application of image analysis and artificial neural network	
Autores: 	Sedghi,M; Golian,A; Soleimani-Roodi,P; Ahmadi,A; Aami-Azghadi,M.	
Data: 	2012-03-01	
Ano: 	2012	
Palavras-chave: 	Image analysis; Neural network model; Sorghum grain; Tannin.	
Resumo: 	The relationship between sorghum grain color and tannin content was reported in several references. In this study, 33 phenotypes of sorghum grain differing in seed characteristics were collected and analyzed by Folin-Ciocalteu method. A computer image analysis method was used to determine the color characteristics of all 33 sorghum phenotypes. Two methods of multiple linear regression and artificial neural network (ANN) models were developed to describe tannin content in sorghum grain from three input parameters of color characteristics. The goodness of fit of the models was tested using R², MS error, and bias. The computer image analysis technique was a suitable method to estimate tannin through sorghum grain color strength. Therefore, the color quality of the samples was described according three color parameters: L* (lightness), a* (redness - from green to red) and b* (blueness - from blue to yellow. The developed regression and ANN models showed a strong relationship between color and tannin content of samples. The goodness of fit (in terms of R²), which corresponds to training the ANN model, showed higher accuracy of prediction of ANN compared with the equation established by the regression method (0.96 vs. 0.88). The ANN models in term of MS error showed lower residuals distribution than that of regression model (0.002 vs. 0.006). The platform of computer image analysis technique and ANN-based model may be used to estimate the tannin content of sorghum.	
Tipo: 	Info:eu-repo/semantics/article	
Idioma: 	Inglês	
Identificador: 	http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-635X2012000100010	
Editor: 	Fundação APINCO de Ciência e Tecnologia Avícolas	
Relação: 	10.1590/S1516-635X2012000100010	
Formato: 	text/html	
Fonte: 	Brazilian Journal of Poultry Science  v.14 n.1 2012	
Fonte: 	info:eu-repo/semantics/openAccess