Tea classification and quality assessment using laser-induced fluorescence and chemometric evaluation

Area of Science:

• Analytical Chemistry
• Food Science
• Spectroscopy

Background:

• Chinese oolong and jasmine teas are popular worldwide.
• Objective tea classification and quality assessment are challenging.
• Traditional methods rely on sensory evaluation, which can be subjective.

Purpose of the Study:

• To develop and validate a chemometric model for classifying Chinese oolong teas.
• To evaluate the quality and grade of jasmine teas using fluorescence spectroscopy.
• To assess the potential of laser-induced fluorescence for practical tea analysis.

Main Methods:

• Laser-induced fluorescence (LIF) spectroscopy was employed.
• Singular Value Decomposition (SVD) described tea autofluorescence.
• Linear Discriminant Analysis (LDA) built a predictive chemometric model.
• Leave-one-out cross-validation was used for model evaluation.

Main Results:

• The chemometric model accurately classified four types of Chinese oolong teas.
• The model effectively estimated the grade of jasmine teas.
• High agreement was observed between the model's predictions and expert evaluations.
• Autofluorescence patterns differed significantly among oolong tea varieties.

Conclusions:

• Laser-induced fluorescence is a promising technique for objective tea classification.
• The developed chemometric model demonstrates practical applicability for tea quality assessment.
• This method offers a reliable alternative to subjective sensory evaluations in the tea industry.