Green Tea Screening Using the ACQUITY RDa Detector

Applications | 2021 | WatersInstrumentation
LC/TOF, LC/HRMS, LC/MS
Industries
Food & Agriculture
Manufacturer
Waters

Significance of the Topic


Green tea is valued for its health-promoting phenolic compounds, especially catechins with antioxidant and anti-inflammatory properties. Reliable, high-throughput methods for profiling these bioactive constituents are essential for quality control, authenticity testing and safety assessment in the food and nutraceutical industries.

Objectives and Study Overview


This application note describes a rapid, accurate method for comprehensive screening of green tea extracts using the Waters ACQUITY RDa Detector, a compact benchtop time-of-flight LC-MS system. The study aims to demonstrate the system’s dynamic range, mass accuracy and workflow efficiency when combined with the waters_connect software and UNIFI application.

Methodology and Instrumentation


Sample Preparation:
  • Green tea extract diluted in 25:75 methanol:water, vortexed, sonicated and centrifuged to remove particulates
  • Catechin calibration standards prepared at 0.01–25 µg/mL in the same solvent mix

Liquid Chromatography:
  • ACQUITY UPLC I-Class with HSS T3 column (100×2.1 mm, 1.8 µm) at 40 °C
  • Gradient elution from 99% aqueous (0.1% formic acid) to 1% over 16 minutes
  • Flow rate 0.6 mL/min, injection volume 10 µL

Mass Spectrometry:
  • ACQUITY RDa Detector time-of-flight analyzer in full-scan mode (50–2000 m/z)
  • Dual ionization (positive and negative modes), scanning at 10 Hz
  • Capillary voltages 0.8 kV (neg) and 1.5 kV (pos); cone 30 V/40 V; fragmentation 60–120 V
  • SmartMS automatic calibration, tuning and lockmass

Data Processing:
  • waters_connect platform with UNIFI v1.9.12 for library searching, automated workflows and report generation

Main Results and Discussion


Compound Identification:
  • Screened against a 27-compound Camellia sinensis library
  • Positive mode: 23 matches (7 confirmed by standards, 16 putative)
  • Negative mode: 24 matches (7 confirmed, 17 putative)

Dynamic Range and Sensitivity:
  • Linear response across 0.1–250 ng on-column (2–3 orders of magnitude)
  • Signal-to-noise >400 at 1 ng; reproducibility %RSD <4.7%
  • Upper limit of quantification 100 ng; overloading observed above 250 ng

Matrix Variability:
  • Analysis at 0.8, 8.3 and 82.5 mg/mL total tea components
  • All catechins within dynamic range at typical level (8 mg/mL)
  • Robust detection across varying sample strengths

System Robustness:
  • Retention time drift <0.05 min over 12 h analysis
  • Mass accuracy within ±5 ppm (average ±0.9 ppm)
  • Peak area reproducibility average %RSD 2.2%

Benefits and Practical Applications


  • High-confidence compound identification via accurate mass, retention time and fragmentation
  • Comprehensive positive/negative polarity screening with extensive library support
  • Streamlined, unified data acquisition and processing workflow
  • Robust performance for purity checking, authenticity testing and contamination screening

Future Trends and Opportunities


Emerging directions include expanding spectral libraries for additional natural products, integrating advanced chemometric and machine learning tools for deeper sample profiling, and automating end-to-end workflows to accelerate decision-making in regulatory, QA/QC and research settings.

Conclusion


The Waters ACQUITY RDa Detector coupled with UNIFI provides a robust, accurate and high-throughput solution for green tea and natural product screening. Its broad dynamic range, mass accuracy and streamlined software platform make it ideal for labs requiring reliable profiling, quantification and authenticity testing.

Reference


1. Pinto G. et al. Quantification of Polyphenols and Metals in Chinese Tea Infusions by Mass Spectrometry. Foods 2020;9(6):835.
2. Forester S. & Lambert J. Antioxidant Effects of Green Tea. Mol Nutr Food Res. 2011;55(6):844–854.
3. Younes M. et al. EFSA Scientific Opinion on the Safety of Green Tea Catechins. EFSA J. 2018;16(4).

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