Quantitation of Smoke Taint Markers in Wine using the Triple Quad LCMS-8050
Applications | 2022 | ShimadzuInstrumentation
Wildfires are increasing in frequency and intensity worldwide, leading to the uptake of smoke‐derived phenolic compounds by grapevines. These volatile phenols undergo glycosylation inside the grape, creating nonvolatile markers that evade sensory detection until fermentation releases the bound compounds, imparting undesirable “smoke taint” aromas in wine.
This work aimed to develop and validate a rapid, sensitive method for quantifying two key smoke taint markers—guaiacol rutinoside and 4-methylguaiacol rutinoside—in white and red wines. Four wine samples (two white, two red) were analyzed using matrix‐matched calibration to determine native concentrations and assess method accuracy across representative matrices.
The analysis employed a Shimadzu LC-40 Nexera HPLC system coupled to an LCMS-8050 triple quadrupole mass spectrometer with an electrospray ionization (ESI) source. Chromatographic separation was achieved on a reversed‐phase column at 40 °C with gradient elution over 15 minutes. Key MS parameters included a drying gas flow of 10 L/min, a heat block at 400 °C, and multiple reaction monitoring transitions of 464.2→147.1 for 4-methylguaiacol rutinoside and 450.2→147.0 for guaiacol rutinoside.
Matrix-matched calibration curves were generated in White Wine A and Red Wine A, covering 0.5–100 ng/mL (4-methylguaiacol rutinoside) and 0.5–113.2 ng/mL (guaiacol rutinoside). All curves exhibited excellent linearity (R2>0.999) and accuracy between 80–120%. Native concentrations of both markers in the four test wines were quantified, with Red Wine A containing 13.2 ng/mL guaiacol rutinoside. Spike-recovery experiments in White Wine B and Red Wine B confirmed method precision, yielding 92–115% accuracy.
Advancements may include automated sample preparation to increase throughput, expansion to additional glycoside markers, and integration with high‐resolution mass spectrometry for broader profiling of smoke‐derived compounds. Coupling this approach with non‐targeted screening could further enhance early detection and mitigation strategies in the vineyard.
A validated LCMS-8050 triple quadrupole method permits accurate, high‐throughput quantitation of guaiacol and 4-methylguaiacol rutinosides in wine. With linear calibration, strong sensitivity, and reliable recoveries, it supports effective monitoring of smoke taint across wine production stages.
LC/MS, LC/MS/MS, LC/QQQ
IndustriesFood & Agriculture
ManufacturerShimadzu
Summary
Importance of the topic
Wildfires are increasing in frequency and intensity worldwide, leading to the uptake of smoke‐derived phenolic compounds by grapevines. These volatile phenols undergo glycosylation inside the grape, creating nonvolatile markers that evade sensory detection until fermentation releases the bound compounds, imparting undesirable “smoke taint” aromas in wine.
Objectives and Study Overview
This work aimed to develop and validate a rapid, sensitive method for quantifying two key smoke taint markers—guaiacol rutinoside and 4-methylguaiacol rutinoside—in white and red wines. Four wine samples (two white, two red) were analyzed using matrix‐matched calibration to determine native concentrations and assess method accuracy across representative matrices.
Used Instrumentation
The analysis employed a Shimadzu LC-40 Nexera HPLC system coupled to an LCMS-8050 triple quadrupole mass spectrometer with an electrospray ionization (ESI) source. Chromatographic separation was achieved on a reversed‐phase column at 40 °C with gradient elution over 15 minutes. Key MS parameters included a drying gas flow of 10 L/min, a heat block at 400 °C, and multiple reaction monitoring transitions of 464.2→147.1 for 4-methylguaiacol rutinoside and 450.2→147.0 for guaiacol rutinoside.
Main Results and Discussion
Matrix-matched calibration curves were generated in White Wine A and Red Wine A, covering 0.5–100 ng/mL (4-methylguaiacol rutinoside) and 0.5–113.2 ng/mL (guaiacol rutinoside). All curves exhibited excellent linearity (R2>0.999) and accuracy between 80–120%. Native concentrations of both markers in the four test wines were quantified, with Red Wine A containing 13.2 ng/mL guaiacol rutinoside. Spike-recovery experiments in White Wine B and Red Wine B confirmed method precision, yielding 92–115% accuracy.
Benefits and Practical Applications
- The method provides rapid (<15 min) and robust quantitation of smoke taint markers in diverse wine matrices.
- Matrix-matched calibration ensures accurate determination of native and spiked analyte levels.
- High sensitivity supports regulatory compliance and quality control in wineries and testing laboratories.
Future Trends and Applications
Advancements may include automated sample preparation to increase throughput, expansion to additional glycoside markers, and integration with high‐resolution mass spectrometry for broader profiling of smoke‐derived compounds. Coupling this approach with non‐targeted screening could further enhance early detection and mitigation strategies in the vineyard.
Conclusion
A validated LCMS-8050 triple quadrupole method permits accurate, high‐throughput quantitation of guaiacol and 4-methylguaiacol rutinosides in wine. With linear calibration, strong sensitivity, and reliable recoveries, it supports effective monitoring of smoke taint across wine production stages.
Reference
- Shimadzu Scientific Instruments. Quantitation of Smoke Taint Markers in Wine using the Triple Quad LCMS-8050. Application Note SSI-LCMS-139. January 2022.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.
Similar PDF
A Predictive Compound Database Approach to the Tentative Identification and Semiquantitation of Volatile-Phenol Glycosides in Smoke‑Affected Grapes from Wildfires
2019|Agilent Technologies|Applications
Application Note Food Testing & Agriculture A Predictive Compound Database Approach to the Tentative Identification and Semiquantitation of Volatile-Phenol Glycosides in Smoke‑Affected Grapes from Wildfires Authors Andrew Caffrey, Larry Lerno, Arran Rumbaugh, Raul Girardello, Anita Oberholster, and Susan E. Ebeler,…
Key words
glycosides, glycosidespentose, pentosephenol, phenolsmoke, smokehexose, hexosesemiquantitation, semiquantitationvolatile, volatilecresol, cresolwinemaking, winemakingdeoxyhexose, deoxyhexosegrapes, grapesdjs, djsesi, esiapci, apciguaiacol
California and Oregon’s Complete Residual Pesticide Analysis using a Shimadzu LCMS 8060
2019|Shimadzu|Applications
Liquid Chromatography Mass Spectrometry SSI-LCMS-105 California and Oregon’s Complete Residual Pesticide Analysis using a Shimadzu LCMS8060 Summary: California and Oregon’s residual pesticide list for cannabis traditionally have been analyzed using both LCMS and GCMS because certain compounds do not ionize…
Key words
esi, esiapci, apcipesticide, pesticidecannabis, cannabisflower, flowerwere, wereionization, ionizationtemperature, temperaturecalifornia, californialcms, lcmsoregon, oregonresidual, residualeach, eachtested, testedanalyzed
Application Handbook Food, Beverages, Agriculture - Release 2
2012|Shimadzu|Guides
Application Handbook Food, Beverages, Agriculture Release 2 Food, Beverages and Agriculture Regarding food, water, beverages and agricultural cropland, the increasing world population is one of the biggest challenges of mankind. How can access be provided to sufficient and safe food…
Key words
news, newsanalysis, analysismeasurement, measurementfood, foodusing, usingsample, samplewater, waterwithout, withoutmrm, mrmacid, acidwere, wereflowrate, flowratemethod, methoddrinking, drinkingsfe
PFAS Analysis: Application Notebook
2020|Shimadzu|Guides
PFAS Analysis: Application Notebook Solutions for PFAS Analysis Application Notebook Per- and polyfluoroalkyl substances (PFAS) are currently of great public health and environmental concern. Because PFAS are ubiquitous and commonly used in materials routinely employed for chemical analysis, laboratories are…
Key words
pfas, pfaspfos, pfospfoa, pfoaetfosaa, etfosaamefosaa, mefosaapfda, pfdapftria, pftriapfuna, pfunapftrea, pftreapfdoa, pfdoapfbs, pfbspfhxa, pfhxapfhxs, pfhxspfhpa, pfhpapfna