Data/hora: 09/06/2024 08:20:37

Provedor de dados: 	70	
País: 	Brazil	
Título: 	Determination of the influence of the variation of reducing and non-reducing sugars on coffee quality with use of artificial neural network	
Autores: 	Messias,José A. T.; Melo,Evandro de C.; Lacerda Filho,Adílio F. de; Braga,José L.; Cecon,Paulo R.	
Data: 	2012-04-01	
Ano: 	2012	
Palavras-chave: 	Coffee quality; Chemical analysis; Classification; Computer systems.	
Resumo: 	The present study aimed at evaluating the use of Artificial Neural Network to correlate the values resulting from chemical analyses of samples of coffee with the values of their sensory analyses. The coffee samples used were from the Coffea arabica L., cultivars Acaiá do Cerrado, Topázio, Acaiá 474-19 and Bourbon, collected in the southern region of the state of Minas Gerais. The chemical analyses were carried out for reducing and non-reducing sugars. The quality of the beverage was evaluated by sensory analysis. The Artificial Neural Network method used values from chemical analyses as input variables and values from sensory analysis as output values. The multiple linear regression of sensory analysis values, according to the values from chemical analyses, presented a determination coefficient of 0.3106, while the Artificial Neural Network achieved a level of 80.00% of success in the classification of values from the sensory analysis.	
Tipo: 	Info:eu-repo/semantics/article	
Idioma: 	Inglês	
Identificador: 	http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162012000200015	
Editor: 	Associação Brasileira de Engenharia Agrícola	
Relação: 	10.1590/S0100-69162012000200015	
Formato: 	text/html	
Fonte: 	Engenharia Agrícola  v.32 n.2 2012	
Fonte: 	info:eu-repo/semantics/openAccess