Abstract
A novel analytical method using fast gas chromatography-surface acoustic wave detection (FGC-SAW) was employed to rapidly characterize blueberry volatile profiles according to genotypes and fruit maturity. Fourteen FGC-SAW peaks were observed and 11 peaks were tentatively identified in the 15 s chromatogram. Peak identifications were confirmed by matching retention index values with similar values from GC-MS analyses of the same samples. Eighty peaks were observed in the 40 min GC-MS analysis of identical samples. Principal component analysis (PCA) score plots of FGC-SAW and GC-MS data both differentiated blueberries according to genotype, maturity stage, and harvest date even though FGC-SAW PCA's used far fewer peak area values. PCA plots clearly separated 'FL02-40', 'Snowchaser', 'Jewel', and 'Primadonna' blueberry cultivars into four quarters using two-dimensional PCA projections. FGC-SAW was also successful in differentiating three berry maturity stages in PCA score plots for both 'Jewel' and 'Primadonna' cultivars. FGC-SAW is an effective technique for rapid analysis of major blueberry volatiles, but could not determine many mid- and low-level volatiles as they were often coeluted with higher concentration volatiles.
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