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Characterization and discrimination of selected China's domestic pork using an LC-MS-based lipidomics approach
- Source :
- Food Control. 100:305-314
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- A lipidomics study using liquid chromatography-tandem mass spectrometry and multivariate statistics was conducted in this work to discriminate raw pork meat. A total of 1180 lipid species were identified in the studied pork samples. Four, three and eight lipids were determined as potential discriminatory markers for the five cuts (shoulder, rump, loin, shank and belly) of Tibetan, Jilin and Sanmenxia black pigs, respectively. Distinct lipidomic fingerprints of Tibetan, Jilin and Sanmenxia pork were obtained and they were clearly separated into three clusters by partial least squares discriminant analysis (PLS-DA). The developed PLS-DA model (R2X = 0.603, R2Y = 0.861 and Q2 = 0.752) enables a 91.1% correct classification of pork samples. One-hundred variables, including 61 glycerolipids, 17 glycerophospholipids, 4 sterol lipids, 2 sphingolipids, 3 polyketides, 7 fatty acyls and 6 prenol lipids, were found to have high potential (variable importance in projection value > 1, p-value
- Subjects :
- Multivariate statistics
Rump
010401 analytical chemistry
04 agricultural and veterinary sciences
Glycerophospholipids
Biology
Loin
040401 food science
01 natural sciences
Sterol
0104 chemical sciences
0404 agricultural biotechnology
Liquid chromatography–mass spectrometry
Lipidomics
Partial least squares regression
Food science
Food Science
Biotechnology
Subjects
Details
- ISSN :
- 09567135
- Volume :
- 100
- Database :
- OpenAIRE
- Journal :
- Food Control
- Accession number :
- edsair.doi...........1e092b6fdbf643b87a2a25b0fdfb95cd
- Full Text :
- https://doi.org/10.1016/j.foodcont.2019.02.001