%0 Journal Article
%T Application of artificial neural networks to determine the authentication of fattening diets of Iberian pigs according to their triacylglycerol profiles
%A Narv¨¢ez-Rivas
%A M.
%A Gallardo
%A E.
%A Jurado
%A J. M.
%A Viera-Alcaide
%A I.
%J Grasas y Aceites
%D 2013
%I Consejo Superior de Investigaciones Cient¨ªficas
%R 10.3989/gya.130112
%X The triacylglycerols in the subcutaneous fat from Iberian pigs reared on four different feeding types, Montanera, Recebo, extensive Cebo and intensive Cebo, have been determined by gas chromatography with a flame ionization detector. Analyses were performed in a column coated with a bonded stationary phase (50% phenyl-50% methylpolysiloxane) with hydrogen as the carrier gas. Lipids were extracted by melting the subcutaneous fat in a microwave oven and then filtering and dissolving it in hexane. A total amount of 2783 samples from several campaigns were considered. Using the triacylglycerols as chemical descriptors, a study on the discriminating power to differentiate samples according to the pig feeding type and system was performed. With this aim, pattern recognition techniques, such as linear discriminant analysis (LDA) and multilayer perceptron artificial neural networks (MLPANN), have been used. ANN performed better than LDA, with a mean prediction ability of approximately 97% in the differentiation of fattening diets such as Montanera, extensive Cebo and intensive Cebo. In the case of including the recebo fattening diet, the model presents a mean performance of 82%. The differentiation of fattening systems has also been achieved by means of ANN, with a mean performance of 96%. Se ha determinado mediante cromatograf¨ªa de gases con detector de ionizaci¨®n de llama los triglic¨¦ridos de la grasa subcut¨¢nea de cerdos ib¨¦ricos, cebados con cuatro tipos de alimentaci¨®n: montanera, recebo, cebo extensivo y cebo intensivo. Los an¨¢lisis se realizaron en una columna con una fase estacionaria ligada qu¨ªmicamente (50% fenil-50% metilpolisiloxano) usando hidr¨®geno como gas portador. La grasa subcut¨¢nea se extrajo por fusi¨®n en horno de microondas, posteriormente se filtr¨® y se disolvi¨® en hexano. Un total de 2.783 muestras de varias campa as fueron analizadas. Usando los triglic¨¦ridos como descriptores qu¨ªmicos se ha llevado a cabo un estudio sobre la capacidad de discriminaci¨®n de ¨¦stos para diferenciar el tipo y r¨¦gimen de alimentaci¨®n de los cerdos. A tal fin, se han empleado t¨¦cnicas de reconocimiento de patrones, tales como an¨¢lisis discriminante lineal (LDA) y redes neuronales artificiales de perceptores multicapa (ANN-MLP). Las ANN presentan mejores resultados que el LDA, con una capacidad de predicci¨®n media de aproximadamente 97% en la diferenciaci¨®n del tipo de alimentaci¨®n entre Montanera, Cebo extensivo y Cebo intensivo. Al incluir el recebo, el modelo presenta un rendimiento promedio de 82%. La diferenciaci¨®n del r¨¦gimen de cebado tambi¨¦n se ha lleva
%K Gas chromatography
%K Iberian pig
%K Neural networks
%K Pattern recognition
%K Subcutaneous fat
%K Triacylglycerols
%K Cerdo ib¨¦rico
%K Cromatograf¨ªa de gases
%K Grasa Subcut¨¢nea
%K Reconocimiento de patrones
%K Redes neuronales
%K Triglic¨¦ridos
%U http://grasasyaceites.revistas.csic.es/index.php/grasasyaceites/article/view/1417/1412