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LAMB MEAT TENDERNESS PREDICTION USING NEURAL NETWORKS AND SENSITIVITY ANALYSIS.pdf

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LAMB MEAT TENDERNESS PREDICTION USING NEURAL NETWORKS AND SENSITIVITY ANALYSIS

LAMB MEAT TENDERNESS PREDICTION USING NEURAL NETWORKS AND SENSITIVITY ANALYSIS ? Paulo Cortez Manuel Portelinha, Sandra Rodrigues, Vasco Cadavez, Alfredo Teixeira Departamento de Sistemas de Informac?a?o Escola Superior Agra?ria University of Minho Braganc?a Polytechnic Institute 4800-058 Guimara?es, PORTUGAL 5301-855 Braganc?a, PORTUGAL Email: pcortez@dsi.uminho.pt Emails: {mportelinha, srodrigues, vcadavez, teixeira}@ipb.pt KEYWORDS: Regression, Multilayer Perceptrons, Multiple Regression, Meat Quality, Ensembles, Data Mining. ABSTRACT The assessment of quality is a key factor for the meat indus- try, where the aim is to fulfill the consumer’s needs. In par- ticular, tenderness is considered the most important charac- teristic 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 mea- surements and a sensory panel. In both cases, the proposed solution outperformed other neural approaches and the Mul- tiple Regression method. 1. Introduction A top priority factor in the success of meat industry relies on the ability to deliver specialties that satisfy the consumer’s taste requirements. Although there are several factors that influence meat quality (e.g. juiciness or appearance), ten- derness is considered the most important attribute (Huffman et al., 1997). The ideal method for measuring tenderness should be accurate, fast, automated and noninvasive. In the past, two major approaches have been proposed (Arvanitoy- annis and Houwelingen-Koukaliaroglou, 2003): instrumen- tal and sensory analysis. The former is based in an objec- tive test, such as the Instron instrument, which measures the Warner-Bratzler Shear (WBS) force and is the most com- monly used device. On the other hand, sensory methods are based in subjective information