Chemical-instrumental-sensory traits and data mining for classifying dry-cured Iberian shoulders from pigs with different diets

  • Daniel CaballeroEmail author
  • María Asensio
  • Carlos Fernández
  • Raquel Reina
  • Juan García-Casco
  • Noelia Martín
  • Antonio Silva
Original Paper


Iberian pigs are an autochthonous porcine breed exclusively from the south western of Iberian Peninsula. In this study, the main objective was to classify dry-cured Iberian shoulders from pigs with different diets. Thus, morphology, physico-chemical and sensory parameters, fatty acid profile and volatile compounds were determined. From this data, two datasets were created, for training and validation purpose. Results on this study, firstly demonstrate the capability of data mining techniques to classify shoulder as function of their different diets by using different chemical-instrumental-sensory parameters. Different classification models were tested in the training datasets. After that, all classification models were performed in the validation datasets and the model of J48 decision tree and fatty acid profile reached the best results (Sensitivity and Specificity > 0.750). From this classification model, a software application was developed for determining the diet of the Iberian pigs. This application could be used for the meat industries and inspection agencies.


Decision trees Fatty acid profile Aromatic compounds Morphometric measurements Quality parameters 



Fatty acids


Mono-unsaturated fatty acids


Knowledge discovery in databases


Diet based on acorn and grass 100%


Diet based on acorn and grass 75% and feed 25%


Diet based on acorn and grass 50% and feed 50%


Diet based on acorn and grass 25% and feed 75%


Diet based on feed 100%


Gas chromatography flame ionisation detector


Solid phase micro extraction


Gas chromatography mass spectrometry






Thiobarbituric acid-reactive substance






Fatty acid methyl esters




Linear retention indexes


Area units


Waikato environment for knowledge analysis


Decision tree






True positive


True negative


False positive


False negative


Analysis of variance


Saturated fatty acids


Poly-unsaturated fatty acids


Lateral discrimination analysis


Random forest


K-nearest neighbours


Rules based systems


Artificial neural networks



Daniel Caballero thanks the “Junta de Extremadura” for the post-doctoral Grant (PO17017).


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Animal Source Foodstuffs Innovation Services (SiPA)University of ExtremaduraCáceresSpain
  2. 2.Chemometrics and Analytical Technology, Department of Food Science, Faculty of ScienceUniversity of CopenhagenFrederiksberg CDenmark
  3. 3.Departamento de Mejora Genética Animal, Instituto Nacional de Investigación Y Tecnología Agraria y Alimentaria (INIA)MadridSpain

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