Characterization and discrimination of selected China's domestic pork using an LC-MS-based lipidomics approach

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<0.05) to differentiate Tibetan, Jilin and Sanmenxia pork meat. The current data set will facilitate a better understanding of the nutritional values of the investigated pork and can be expanded to a larger sample size for lipid marker validation. Our findings demonstrate that lipidomic analysis together with multivariate statistics is a promising approach for the differentiation of China's domestic pork.