Statistical model for classifying the feeding systems of Iberian pigs through Gas Chromatography (GC-FID) and Isotope Ratio Mass Spectrometry (GC-C-IRMS)

Authors

  • C. L. Delgado-Chavero ASICI
  • E. Zapata-Márquez ASICI
  • J. M. García-Casco Centro de I+D en Cerdo Ibérico – INIA
  • A. Paredes-Torronteras ASICI

DOI:

https://doi.org/10.3989/gya.130412

Keywords:

Fatty acids, Gas Chromatography, GCC- IRMS, Iberian pig, Isotope Ratio Mass Spectrometry, Subcutaneous fat

Abstract


In the present work we have analyzed a total of 734 subcutaneous fat samples from Iberian pigs with different feeding systems for fattening (“Bellota”, “Recebo”, “Campo” and “Cebo”) over three consecutive years, 2009-2011. Lipids were extracted from the subcutaneous fat on the rump, and after esterification, they were analyzed by Gas Chromatography (GC-FID) and Gas Chromatography- Combustion-Isotope Ratio Mass Spectrometry (GC-C-IRMS). Mean fatty acids and isotope ratios show that there are differences according to the year and feeding systems, two factors that should be taken into account when classifying the animals. The application of different prediction models based on Discriminant analysis has allowed us to establish a method for the classification of animals according to the feeding system type, with a correct percentage of 85% using three or four classification categories (Bellota, Recebo, Campo and/or Cebo) and 91% using only two categories, Cebo and Bellota. This model could provide the basis for appropriate classification of Iberian pigs according to their feeding regime.

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References

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Published

2013-06-30

How to Cite

1.
Delgado-Chavero CL, Zapata-Márquez E, García-Casco JM, Paredes-Torronteras A. Statistical model for classifying the feeding systems of Iberian pigs through Gas Chromatography (GC-FID) and Isotope Ratio Mass Spectrometry (GC-C-IRMS). Grasas aceites [Internet]. 2013Jun.30 [cited 2024Mar.28];64(2):157-65. Available from: https://grasasyaceites.revistas.csic.es/index.php/grasasyaceites/article/view/1420

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Research

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