| Autor: |
Silvia Parrini, Francesco Sirtori, Marjeta Čandek-Potokar, Rui Charneca, Alessandro Crovetti, Ivona Djurkin Kušec, Elena González Sanchez, Mercedes Maria Izquierdo Cebrian, Ana Haro Garcia, Danijel Karolyi, Benedicte Lebret, Alberto Ortiz, Nuria Panella-Riera, Matthias Petig, Preciosa Jesus da Costa Pires, David Tejerina, Violeta Razmaite, Chiara Aquilani, Riccardo Bozzi |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2045-2322 |
| DOI: |
10.1038/s41598-023-34996-x |
| Popis: |
Abstract 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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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