Analysis Of Aromatic Profile And Application On Product Quality Authentification Of Tea(Camellia Sinensis)

Tea (Camellia sinensis) is one kind of famous beverages in people’s daily life, and is favored for its healthy benefits and pleasant flavor. Recently, the quality authentication of agricultural products is gaining more and more attentions from the government, producers and consumers. And characterization of quality grade, traceability of geographic origin, detection of additives and identification of economic adulteration are curial issues of quality authentication of agricultural products. It is desired to develop fast, robust and objective methods for quality authentication of tea products.Aroma is one of the key sensory factors for quality evaluation of tea. The analysis of tea aromatic profile enables the understanding of tea aroma during brewing. Besides, aromatic profile might contain relevant fingerprints for product quality authentication. In this study, aromatic profile of tea was analyzed by headspace solid phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). The changes of aromatic profile during brewing were investigated. Combined with chemometric methods, such as principal component analysis (PCA), partial least square (PLS), hierarchical cluster analysis (HCA) and linear discriminant analysis (S-LDA), relevant aromatic fingerprints were characterized so as to make objective and robust authentication of tea products. The main results are listed as follows:1. Application of retention index on volatile compound indentification of teaStandard mixture of n-alkanes and n-alkanes in analyte assay were applied respectively to determine the retention index (RI) of tea volatiles. The linear correlation coefficients of retention time with carbon number of the two methods were both above0.99, indicating quite good reliability for determine RI. With the applying of RI, the correct identification rate of the volatiles increased from46.67%to74.67%. Meanwhile, retention index enabled effective identification of the isomers contained in tea volatiles, greatly increased the identification accuracy. Data in relevant literatures were summarized to construct a RI database for HP-innowax column. The RI database could also improve the efficiency of compound identification using HP-innowax column.2. Study of change rules of tea volatile profile during brewingThis study compared the aromatic profiles of tea under different conditions, including four forms aroma during brewing (dry tea aroma, tea beverage aroma, tea infusion aroma and tea leaves remain aroma), aroma of different infusion times and aroma of different tea/water ratios. Apparent differences of volatile constitution could be observed for the four aroma forms. Most volatile compounds were detected in dry tea aroma, indicating that most complete features were kept in dry tea aroma. No volatile compound was generated in quantity during brewing process of tea. The compound volatilization was greatly affected by its solubility in water. The volatilizations of hydrocarbon compounds were significantly suppressed by tea beverage. The relative abundance of aldehydes decreased with infusion times, while that of most esters rose first and then fell with infusion times. The flowery aroma of oolong tea was unlikely contributed by terpenes and nerolidol. The variation of aroma intensity of oolong tea was caused by change of aroma constitution rather that the total amount of essential oil. The study of different tea/water ratios also confirmed the significant influence of solubility on compound volatilization. The relative abundance of hydrocarbons increased with tea/water ratio, while some volatiles (like benzyl alcohol and phenyl ethanol) were refrained from volatilizing in tea infusion with the increasing of tea/water ratio.3. Volatile profile analysis and quality prediction of Longjing tea (Camellia sinensis) by HS-SPME/GC-MSThis study aimed to analyze the volatile profile of Longjing tea, and further develop an objective prediction model for aroma quality of Longjing tea based on potent odorants. A total of21Longjing samples were analyzed by headspace solid phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). Pearson’s linear correlation analysis and Partial Least Square (PLS) regression were applied to investigate the relationship between sensory aroma scores and the volatile compounds. Results showed that60volatile compounds could be commonly detected in this famous green tea, and terpenes and esters were two major groups characterized, representing33.89%and15.53%of the total peak area respectively. Ten compounds were determined to be significantly correlated with the perceived aroma quality of Longjing tea, especially linalool (0.701), nonanal (0.738),(Z)-3-hexenyl hexanoate (-0.785), and β-ionone (-0.763). On the base of these10compounds, a model (correlation coefficient of89.4%and cross-validated correlation coefficient of80.4%) was constructed to predict the aroma quality of Longjing tea. Summarily, this study provided a novel option for quality prediction of green tea based on HS-SPME/GC-MS technique.4. Discrimination of oolong tea (Camellia sinensis) varieties based on feature extraction and selection from aromatic profiles analyzed by HS-SPME/GC-MSThis study aimed to develop an objective and accurate analytical method to discriminate oolong tea varieties that easily causing adulteration by potential volatile compounds. A total of75oolong tea samples of five similar varieties (Tieguanyin, Benshan, Maoxie, Huangjingui and Jinguanyin) were analyzed by headspace solid phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). The relative content of26major volatile compounds varied significantly according to variety, combined with the results of hierarchical cluster analysis (HCA), indicating that the varietal differences of aromatic profile remain significant for tea cultivars with very close origin. Principal component analysis (PCA) of the aromatic profiles showed that the feature of variety dominated over the other features (like producing region and quality). By stepwise linear discriminant analysis (S-LDA),18volatiles with the best discriminating capacity were selected, and4discriminant functions (DFs) enabled simultaneously discrimination of the five oolong varieties with100%correct rate.5. A novel quality evaluation index and strategies to identify scenting quality of jasmine tea based on volatile profile analysisJasmine tea is a popular tea in daily consumption and beverage industry, and scenting quality and synthetic artificial oil are crucial issues of quality control for this tea. The volatile profiles of jasmine tea samples and flower concrete of Jasminum sambac were analyzed by headspace solid phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). Twenty-nine volatile compounds were detected as "common components" in well-scented jasmine teas and concrete of jasmine flowers. Potential correlation was discovered between the quality grade of jasmine tea and the ratio of the peak area percentage of a-farnesene,(Z)-3-hexenyl benzoate, methyl anthranilate, and indole to that of linalool. This ratio was denoted as "Jasmine Tea Flavor" index (JTF index), a novel index for quality evaluation of jasmine tea. JTF index, together with detecting of "common components" and abnormal peaks, could provide a good identification of well-scented, poor-scented, and not scented jasmine teas. Moreover, carrier compounds might be a clear evidence for identifying fake jasmine teas that were added with synthetic fragrance oil.