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Enology – Enological Method Development Session
June 18, 2026 | 4:10 pm – 4:50 pm | Location: Grand Ballroom 100C
Research Reports
Moderator:
To be announced.
Speakers:
| 4:10 pm – 4:30 pm | Rapid Measurement of “Green” and “Moldy” Odorants in Grapes using Direct Analysis in Real Time Mass Spectrometry Zoe Scott, Cornell University, New York |
| 4:30 pm – 4:50 pm | High-Throughput Tannin Fragmentation Fingerprinting Links Chemistry to Astringency Yanxin Lin, The Pennsylvania State University, State College |
Zoe Scott* | Andre Kalenak | Gavin Sacks
Rapid Measurement of “Green” and “Moldy” Odorants in Grapes using Direct Analysis in Real Time Mass Spectrometry
Zoe Scott,* Andre Kalenak, and Gavin Sacks
*Cornell University Department of Food Science, 253 Stocking Hall, 411 Tower Road, Ithaca, NY, 14853, zzs2@cornell.edu
Reliable, rapid screening of underripe and mold‑associated off‑aromas is critical for informed harvest, sorting, and blending decisions in winemaking. The key contributors—trans‑2‑hexenol (“green, grassy”) and 1‑octen‑3‑ol (“mushroom”)—are routinely quantified using headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS‑SPME‑GC‑MS), the standard method for confirming these quality‑limiting compounds. However, GC‑MS cycle times of ~30 min/sample constrain throughput during harvest intake. To address this bottleneck, we developed a high‑speed workflow coupling solid‑phase mesh-enhanced sorption from headspace (SPMESH) extraction with direct analysis in real time tandem mass spectrometry (DART‑MS/MS). Because alcohols ionize inefficiently under DART conditions, in‑situ derivatization with hindered nitrogenous bases was employed to enhance ionization efficiency. To mitigate matrix effects and accommodate the nonvolatile nature of these bases, we evaluated both pre‑incubation (in‑well) and post‑incubation (mist‑applied) derivatization strategies. In aqueous model systems, trans‑2‑hexenol produced strong responses and 1‑octen‑3‑ol achieved limits of detection below sensory threshold, enabling differentiation at low concentrations. Saturated 1‑hexanol remained less responsive, as expected. Among screened reagents, pyridine and quinoline yielded the best sensitivity, while stronger or higher‑mass bases increased chemical background and elevated detection limits. Overall, post‑incubation application of hindered nitrogenous bases before SPMESH‑DART‑MS/MS provided <1 min/sample screening for trans‑2‑hexenol and 1‑octen‑3‑ol. This approach offers wineries and service laboratories a practical, high‑throughput complement to HS‑SPME‑GC‑MS during crush and for routine quality control.
Funding Support: New York State Wine and Grape Foundation, E&J Gallo Winery
Yanxin Lin | Helene Hopfer | Duncan Calvert | Ezekiel Warren | Misha Kwasniewski*
High-Throughput Tannin Fragmentation Fingerprinting Links Chemistry to Astringency
Yanxin Lin, Helene Hopfer, Duncan Calvert, Ezekiel Warren, and Misha Kwasniewski*
*Food Science Department, Penn State University, Penn State University, Rodney A. Erickson Food Science Building, State College, PA, 16803, mtk5407@psu.edu
Wine mouthfeel, especially astringency, is difficult to explain using conventional chemistry because phenolics are highly diverse and their sensory effects depend on molecular structure and interactions with the wine matrix and saliva. As a result, wines that appear similar by standard metrics (pH, titratable acidity, ethanol, and even total phenolics/tannin assays) can still elicit distinct sensory perceptions. To address these limitations, we related tannin fragmentation fingerprinting (TFF) data to sensory evaluation of California Cabernet Sauvignon wines. TFF is a family of liquid chromatography-tandem mass spectrometry methods that leverage electrospray in-source fragmentation to generate structurally informative fingerprints for condensed tannins (C-TFF), hydrolysable tannins (H-TFF), oxidation-derived adducts (O-TFF), and stilbenes (S-FF). The wines were intentionally selected to be “chemically narrow” by traditional measures and analyzed using the TFF workflow to obtain structure-resolved phenolic profiles. TFF data sets were integrated with spectrophotometric assays (SPA) and basic composition, then related to a projective-mapping sensory configuration via multivariate analyses. In PLS2 models, basic chemistry showed low predictive value for both sensory dimensions, particularly Dim2 (Q² = 0.029). SPA (bulk phenolics) captured variance primarily associated with condensed tannins and their derivatives, yielding good prediction for Dim1 (Q² = 0.664) but poor prediction for Dim2 (Q² = −0.588). In contrast, TFF showed the strongest correspondence with the sensory map, providing robust prediction for Dim1 (Q² = 0.711) and acceptable prediction for Dim2 (Q² = 0.368). Loading patterns indicated that O-TFF and C-TFF features dominated Dim1, while H-TFF and S-FF features contributed more strongly to Dim2. Overall, pairing TFF with projective mapping sensitively linked phenolic structure to astringency-related mouthfeel within a chemically narrow wine set, highlighting TFF as a stronger, more structure-informed framework than basic chemistry or bulk assays for connecting composition to perception.
Funding Support: United States Department of Agriculture (USDA) National Institute of Food and Agriculture (NIFA) Hatch Program, including project no. PEN04792 (accession no. 7002577) and project no. PEN04761 (accession no. 1025695) and the American Vineyard Foundation (AVF) 2025-2954
