Abstract
Highbush blueberries (Vaccinium corymbosum L.) are cultivated worldwide for their fruit with unique taste and potential health benefits. Blueray, Bluecrop, and Spartan are prominent among the various blueberry cultivars. We performed gas chromatography–mass spectrometry (GC–MS)-based metabolic profiling to differentiate the fruits of these three cultivars, and built an optimal partial least squares-discriminant analysis (PLS-DA) model to separate them. Amino acids, fatty acids, organic acids, phenolic compounds, and sugars were identified in the fruits. The optimized PLS-DA model for different cultivars of the fruits was obtained by selecting variables based on a variable importance in the projection (VIP) cut-off value of 1.0. Caffeic acid, aspartic acid, acetic acid, threonolactone, inositol, xylose, glucoside, linolenic acid, mannose, altrose, glycine alanine, and valine were found to be relevant and contributing compounds for differentiating cultivars. In addition, a hierarchical cluster analyses dendrogram pattern was correlated with the PLS-DA. This study suggested that GC–MS-based metabolic profiling coupled with multivariate statistical analysis could be used to differentiate the fruits of three major highbush blueberry cultivars.
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