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Title: Lamb meat tenderness prediction using neural networks and sensitivity analysis
Authors: Cortez, Paulo
Portelinha, Manuel
Rodrigues, Sandra
Cadavez, Vasco
Teixeira, A.
Keywords: Regression
Multilayer perceptrons
Multiple regression
Meat quality
Data mining
Issue Date: 2005
Publisher: Eurosis
Citation: Cortez, P.; Portelinha, M.; Rodrigues, Sandra; Cadavez, Vasco; Teixeira, Alfredo (2005) - Lamb meat tenderness prediction using neural networks and sensitivity analysis. In Proceedings of the 19 th European Simulation Multiconference - ESM'2005. Porto. p. 177-181
Abstract: The assessment of quality is a key factor for the meat industry, where the aim is to fulfill the consumer’s needs. In particular, tenderness is considered the most important characteristic affecting consumer perception of taste. In this paper, a Neural Network Ensemble, with feature selection based on a Sensitivity Analysis procedure, is proposed to predict lamb meat tenderness. This difficult real-world problem is defined in terms of two regression tasks, by using instrumental measurements and a sensory panel. In both cases, the proposed solution outperformed other neural approaches and the Multiple Regression method.
Appears in Collections:CA - Publicações em Proceedings Indexadas ao ISI/Scopus

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