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	Provedor de dados Ciênc. Tecnol. Aliment. (2) Autor WU,Wenbiao (2) ZHU,Lintao (2) Palavra-chave BP neural network (2) Gelling foods (2) Sensorial test (2) Texture profile (2) Tipo do documento Info:eu-repo/semantics/article (2) Ano 2020 (1) 2019 (1) País Brazil (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Artificial neural network for determining the hedonic score of texture of and distinguishing different grades of ham sausages Ciênc. Tecnol. Aliment. ZHU,Lintao; WU,Wenbiao. Abstract The preference of consumers of ham sausages is mainly determined on its texture. A method of determining hedonic score of texture and distinguishing different grades of ham sausages based on artificial neural network was established in this study. The topological texture of the artificial neural network was developed on the basis of analyzing the hardness, springiness, cohesiveness and adhesiveness measured by a texture analyzer and the hedonic score of texture measured by a sensorial test. The simulation result indicated that the hedonic score of texture predicted by the artificial neural network was well correlated with that obtained by the sensorial test and they were not significantly different from each other. Particularly, cluster analysis... Tipo: Info:eu-repo/semantics/article Palavras-chave: Texture profile; Sensorial test; BP neural network; Gelling foods. Ano: 2019 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612019005000317 Artificial neural network for determining the hedonic score of texture of and distinguishing different grades of ham sausages Ciênc. Tecnol. Aliment. ZHU,Lintao; WU,Wenbiao. Abstract The preference of consumers of ham sausages is mainly determined on its texture. A method of determining hedonic score of texture and distinguishing different grades of ham sausages based on artificial neural network was established in this study. The topological texture of the artificial neural network was developed on the basis of analyzing the hardness, springiness, cohesiveness and adhesiveness measured by a texture analyzer and the hedonic score of texture measured by a sensorial test. The simulation result indicated that the hedonic score of texture predicted by the artificial neural network was well correlated with that obtained by the sensorial test and they were not significantly different from each other. Particularly, cluster analysis... Tipo: Info:eu-repo/semantics/article Palavras-chave: Texture profile; Sensorial test; BP neural network; Gelling foods. Ano: 2020 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612020000100046 Registros recuperados: 2 Primeira ... 1 ... Última

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