Prediction of fatty acid composition in intact and minced fat of European autochthonous pigs breeds by near infrared spectroscopy
2023
Parrini, Silvia | Sirtori, Francesco | Čandek-Potokar, Marjeta | Charneca, Rui | Crovetti, Alessandro | Kušec, Ivona Djurkin | González Sanchez, Elena | Izquierdo Cebrian, Mercedes Maria | Garcia, Ana Haro | Karolyi, Danijel | Lebret, Benedicte | Ortiz, Alberto | Panella-Riera, Nuria | Petig, Matthias | Jesus da Costa Pires, Preciosa | Tejerina, David | Razmaite, Violeta | Aquilani, Chiara | Bozzi, Riccardo | Indústries Alimentàries | Qualitat i Tecnologia Alimentària
The fatty acids profile has been playing a decisive role in recent years, thanks to technological, sensory and health demands from producers and consumers. The application of NIRS technique on fat tissues, could lead to more efficient, practical, and economical in the quality control. The study aim was to assess the accuracy of Fourier Transformed Near Infrared Spectroscopy technique to determine fatty acids composition in fat of 12 European local pig breeds. A total of 439 spectra of backfat were collected both in intact and minced tissue and then were analyzed using gas chromatographic analysis. Predictive equations were developed using the 80% of samples for the calibration, followed by full cross validation, and the remaining 20% for the external validation test. NIRS analysis of minced samples allowed a better response for fatty acid families, n6 PUFA, it is promising both for n3 PUFA quantification and for the screening (high, low value) of the major fatty acids. Intact fat prediction, although with a lower predictive ability, seems suitable for PUFA and n6 PUFA while for other families allows only a discrimination between high and low values.
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