Research On Aroma Compounds Of Maojian Teaand Maofeng Tea Based On Gas Chromatography-mass Spectrometryand Electronic Nose

Green tea is one of the most popular teas in China,which includes many different categories.Each green tea category has several sub-categories with different production areas.Some high-quality green teas planted in specific areas are labeled as products with geographical indications,which has high value.However,the green teas with the same categories are very similar in production technology,with extremely small differences in aroma.These slight differences coupled with an increasing number of sub-categories have complicated the fine-grained classification of green teas,which is more difficult than the normal classification of green teas.Therefore,it is of great significance to study on the aroma components of different green teas with geographical indications.In this research,an electronic nose(E-nose)was used to collect the volatile compounds in 12 types of green tea samples with geographical indications(including six types of Maofeng tea and six types of Maojian tea).A convolutional neural network backbone was proposed to automatically mine the volatile compounds information of the green tea samples.And a support vector machine(SVM)classifier was employed to achieve the fine-grained classification of the 12 green tea samples with high accuracy and strong robustness.In addition,the qualitative and quantitative results of the aroma components of different tea samples were obtained by using gas chromatography-mass spectrometry(GC-MS).The differences among different tea samples were explored by means of the GC-MS,which verified the effectiveness of the E-nose in the identification of different green teas with geographical indications.By using Partial Least Squares Regression(PLSR),the relationship between the sensor response values obtained from an electronic nose and the aroma component concentrations obtained from GC-MS analysis was analyzed.Strong correlations were observed between the sensors and aroma components,providing a theoretical foundation for further research on accurate quantification analysis based on electronic nose systems.