Trait Selection for Assessing Beef Meat Quality Using Non-linear SVM

Part of Advances in Neural Information Processing Systems 17 (NIPS 2004)

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Juan Coz, Gustavo Bayón, Jorge Díez, Oscar Luaces, Antonio Bahamonde, Carlos Sañudo


In this paper we show that it is possible to model sensory impressions of consumers about beef meat. This is not a straightforward task; the reason is that when we are aiming to induce a function that maps object descriptions into ratings, we must consider that consumers' ratings are just a way to express their preferences about the products presented in the same testing session. Therefore, we had to use a special purpose SVM polynomial kernel. The training data set used collects the ratings of panels of experts and consumers; the meat was provided by 103 bovines of 7 Spanish breeds with different carcass weights and aging periods. Additionally, to gain insight into consumer preferences, we used feature subset selection tools. The result is that aging is the most important trait for improving consumers' appreciation of beef meat.