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  • 标题:Fatty Acid Profile of Lipid Fractions of Mangalitza (Sus scrofa domesticus) from Northern Romania: A GC-MS-PCA Approach
  • 本地全文:下载
  • 作者:Cornelia Petroman ; Gabriela Popescu ; Raymond-Nandy Szakal
  • 期刊名称:Foods
  • 电子版ISSN:2304-8158
  • 出版年度:2021
  • 卷号:10
  • 期号:2
  • 页码:242
  • DOI:10.3390/foods10020242
  • 出版社:MDPI Publishing
  • 摘要:Mangalitza pig (Sus scrofa domesticus) becomes more popular in European countries. The goal of this study was to evaluate the fatty acid profile of the raw and thermally processed Mangalitza hard fat from Northern Romania. For the first time, the gas chromatography-mass spectrometry-Principal component analysis technique (GC-MS-PCA)—was applied to evaluate the dissimilarity of Mangalitza lipid fractions. Three specific layers of the hard fat of Mangalitza from Northern Romania were subjected to thermal treatment at 130 °C for 30 min. Derivatized samples were analyzed by GC-MS. The highest relative content was obtained for oleic acid (methyl ester) in all hard fat layers (36.1–42.4%), while palmitic acid was found at a half (21.3–24.1%). Vaccenic or elaidic acids (trans) were found at important concentrations of 0.3–4.1% and confirmed by Fourier-transform infrared spectroscopy. These concentrations are consistently higher in thermally processed top and middle lipid layers, even at double values. The GC-MS-PCA coupled technique allows us to classify the unprocessed and processed Mangalitza hard fat specific layers, especially through the relative concentrations of vaccenic/elaidic, palmitic, and stearic acids. Further studies are needed in order to evaluate the level of degradation of various animal fats by the GC-MS-PCA technique.
  • 关键词:fatty acid profile; lipid fractions; Mangalitza; Sus scrofa domesticus ; aldehyde degradation compounds; gas chromatography—mass spectrometry; principal component analysis; GC-MS-PCA coupled technique fatty acid profile ; lipid fractions ; Mangalitza ; Sus scrofa domesticus ; aldehyde degradation compounds ; gas chromatography—mass spectrometry ; principal component analysis ; GC-MS-PCA coupled technique
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