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Article Abstract
A metabolomics technology for lipid profiling based on supercritical fluid chromatography (SFC) coupled with mass spectrometry (MS) was applied to analyze lipids of soybean. Principal component analysis (PCA) was used to discriminate twelve soybean cultivars according to their suitability for different processed foods such as natto, tofu, edamame, and nimame. By PCA assay, triacylglycerol (TAG) was found as the main variable for discrimination of soybean cultivars. Therefore, a high-throughput and high-resolution TAG profiling method by SFC/MS was developed to more effective discrimination. By investigating several columns, three Chromolith Performance RP-18e columns connected in series were chosen as the most effective column for TAG profiling. Diverse TAGs were separated effectively for 8 min without purification. Additionally, each TAG was identified successfully by the programmed cone voltage fragmentation even without MS/MS analysis and any standard sample.
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