Short communicationRapid fingerprinting of grape volatile composition using secondary electrospray ionization orbitrap mass spectrometry: A preliminary study of grape ripening

- SESI-MS holds promise as a tool for rapid screening of grape volatiles.
- No sample preparation or concentration steps were necessary.
- Potential grape berry ripeness markers were detected.
- C13-norisoprenoids could be monitored with mini mass spectrometers in the future.

We present a rapid and sensitive method based on secondary electrospray ionization mass spectrometry (SESI-MS) for profiling volatile emissions from the intact berries of non-Muscat grape cultivars (Pinot Noir, Chardonnay and Sauvignon Blanc). The method does not require sample preparation or concentration steps. Grape volatiles were tentatively identified based on accurate mass, the related elemental composition and literature. Approximately 300 peaks were detected in positive ion mode, and fewer (70-100) in negative ion mode. We monitored changes in grape berry volatile composition during ripening to screen for potential ripeness markers and observed ten [M+H]+ peaks and two [M-H]- peaks that evolved in a significant linear trend (R2 ≥ 0.80, p < 0.05) for the combined data across all cultivars either increasing or decreasing in the final four weeks of ripening. Peaks assigned to C13-norisoprenoids and benzenoid derivatives have shown similar trends in previous studies using offline gas chromatography (GC) approaches. Principal components analysis showed that negative ion mode clearly separated each stage of grape ripeness, whilst positive ion mode only separated berries in the final stage, pre-harvest. From this preliminary study, we conclude that SESI-MS holds promise as a tool for rapid screening of grape volatiles. Some marker ions had no interfering peaks within a 1-Da window, such that they could be monitored with simple unit-resolution instruments in future studies. This implies that SESI-MS in combination with portable MS instrumentation has potential for field analysis where real-time analysis is key.

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