Predicting the storage time of green tea by myricetin based on surface-enhanced Raman spectroscopy

Area of Science:

• Analytical Chemistry
• Food Science
• Spectroscopy

Background:

• Green tea quality rapidly declines due to polyphenol oxidation and degradation during storage.
• Accurate and efficient methods are needed to assess green tea's storage time and quality.
• Myricetin is a key polyphenol affected by storage conditions.

Purpose of the Study:

• To develop a rapid Surface-enhanced Raman spectroscopy (SERS) strategy for predicting green tea quality changes during storage.
• To identify characteristic Raman peaks indicative of storage duration.
• To establish a correlation between myricetin concentration and green tea's storage time.

Main Methods:

• Acquisition of Raman spectra from green tea samples stored over different periods (2015-2020) using SERS with silver nanoparticles.
• Development of a Principal Component Analysis-Support Vector Machine (PCA-SVM) model for predicting storage time.
• Identification and analysis of characteristic Raman peaks, specifically focusing on the peak at 730 cm⁻¹ attributed to myricetin.

Main Results:

• The PCA-SVM model achieved a high prediction accuracy of 97.22% for the storage time of green tea.
• The Raman peak at 730 cm⁻¹, corresponding to myricetin, was identified as a characteristic marker.
• This myricetin peak showed a linear positive correlation with prolonged storage time and myricetin concentration.

Conclusions:

• SERS offers a convenient and fast method for assessing green tea quality by predicting storage time.
• Myricetin concentration, quantifiable via SERS, serves as a reliable indicator for determining green tea's storage duration.
• This approach facilitates rapid quality control and identification of myricetin levels in stored green tea.