A rapid aroma quantification method: Colorimetric sensor-coupled multidimensional spectroscopy applied to black tea...

Area of Science:

• Analytical Chemistry
• Food Science
• Spectroscopy

Background:

• Black tea aroma significantly impacts quality, necessitating rapid evaluation for intelligent processing.
• Volatile organic compounds (VOCs) are crucial indicators of black tea aroma profiles.
• Existing methods for VOC detection may lack the speed required for real-time quality control.

Purpose of the Study:

• To develop a rapid quantitative detection method for key VOCs in black tea using a colorimetric sensor array and hyperspectral system.
• To establish predictive models for specific aroma compounds like linalool, benzeneacetaldehyde, hexanal, methyl salicylate, and geraniol.
• To elucidate the interaction mechanism between sensor array dyes and VOCs.

Main Methods:

• A simple colorimetric sensor array was coupled with a hyperspectral imaging system.
• Competitive Adaptive Reweighted Sampling (CARS) was employed for feature variable selection.
• Least-squares support vector machine (LS-SVM) models were developed for quantitative VOC prediction.
• Density functional theory (DFT) calculations were used to investigate dye-VOC interactions.

Main Results:

• The CARS-LS-SVM model demonstrated strong quantitative prediction capabilities for key VOCs.
• Correlation coefficients for predicting linalool, benzeneacetaldehyde, hexanal, methyl salicylate, and geraniol reached 0.89, 0.95, 0.88, 0.80, and 0.78, respectively.
• The study identified strong correlations between molecular orbital energy levels, dipole moments, intermolecular distances, and dye-VOC interactions.

Conclusions:

• The integrated colorimetric sensor array and hyperspectral system offer a promising approach for rapid and accurate aroma quality assessment of black tea.
• The developed models provide reliable quantitative predictions of key aroma-contributing VOCs.
• Understanding the molecular interaction mechanisms enhances the design and optimization of sensor arrays for aroma analysis.