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Rapid Sensing of Key Quality Components in Black Tea Fermentation Using Electrical Characteristics Coupled to
Chunwang Dong1, Ting An1,2, Hongkai Zhu1
1Tea Research Institute, The Chinese Academy of Agricultural Sciences, Hangzhou, 310008, China.
Scientific Reports
|February 2, 2020
Summary
Electrical detection technology accurately predicts Congou black tea
Area of Science:
- Food Science
- Analytical Chemistry
- Biotechnology
Background:
- Congou black tea fermentation involves complex biochemical changes affecting quality.
- Traditional methods for assessing tea quality are often time-consuming and subjective.
- Electrical characteristic detection offers a potential non-destructive method for quality assessment.
Purpose of the Study:
- To develop quantitative prediction models for sensory score and key chemical components (theaflavins, thearubigins, theabrownins) of Congou black tea during fermentation.
- To investigate the variation of electrical parameters during fermentation.
- To optimize preprocessing and variable selection methods for improved model accuracy.
Main Methods:
- Utilized electrical characteristic detection technology on fermented Congou black tea samples.
- Applied Zero-mean normalization (Zscore) for data preprocessing and Monte Carlo uninformed variable elimination (MC UVE) combined with competitive adaptive reweighted sampling (CARS) for variable selection.
- Established quantitative prediction models using selected characteristic electrical parameters (loss factor D and reactance X).
Main Results:
- Electrical parameters showed regular variations with frequency and fermentation time, indicating increasing charge transfer hindrance.
- Zscore preprocessing significantly improved prediction set correlation coefficient (Rp) from 0.172 to 0.842.
- Optimized models achieved high Rp values for sensory score (0.924), theaflavin (0.811), thearubigin (0.85), and theabrownin (0.938), with good RPD values.
Conclusions:
- Electrical characteristic detection is a viable method for quantitative prediction of Congou black tea quality during fermentation.
- The developed models demonstrate good performance and reliability for assessing key fermentation quality indicators.
- This approach offers a rapid and non-destructive alternative for tea quality control.
