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| Hernández-Cruz,L.; Ramírez-Bribiesca,J.E.; Guerrero-Legarreta,M.I.; Hernández-Mendo,O.; Crosby-Galvan,M.M.; Hernández-Calva,L.M.. |
| Twenty hair (Pelibuey x Katadin x BlackBelly) and 20 wool (Rambouillet x Criollo) lambs were fattened in an intensive feeding system to reach 40kg body weight at ten months of age. The yield of lamb sides and back fat (51.9%, 2.5mm vs. 47.0%, 2.3mm) were greater in wool lambs. Meat pH was not different between phenotypes but meat temperature was higher during the first hours postmortem in wool lamb sides (27, 23, and 20, vs. 24, 20, and 17ºC). Protein content in meat from the neck (braquicephalic and esternocephalic muscles) and loin (Longissimus lumborum muscle) were higher in hair lambs (21.1 and 20.4 vs. 19.7 and 19.3 %), while moisture of the same muscles was higher in wool lambs (75.6 and 75.9 vs. 73.6 and 74.3%). Ash content was similar in both... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Lamb meat; Physicochemical characteristics; Fatty acids; Sensorial test. |
| Ano: 2009 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-09352009000200027 |
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| 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 |
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| 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 |
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