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Advisor(s)
Abstract(s)
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.
Description
Keywords
Regression Multilayer perceptrons Multiple regression Meat quality Ensembles Data mining
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