Rapid discrimination of the geographical origins of an oolong tea (anxi-tieguanyin) by near-infrared spectroscopy and partial least squares discriminant analysis. Yan Si-Min,Liu Jun-Ping,Xu Lu,Fu Xian-Shu,Cui Hai-Feng,Yun Zhen-Yu,Yu Xiao-Ping,Ye Zi-Hong Journal of analytical methods in chemistry This paper focuses on a rapid and nondestructive way to discriminate the geographical origin of Anxi-Tieguanyin tea by near-infrared (NIR) spectroscopy and chemometrics. 450 representative samples were collected from Anxi County, the original producing area of Tieguanyin tea, and another 120 Tieguanyin samples with similar appearance were collected from unprotected producing areas in China. All these samples were measured by NIR. The Stahel-Donoho estimates (SDE) outlyingness diagnosis was used to remove the outliers. Partial least squares discriminant analysis (PLSDA) was performed to develop a classification model and predict the authenticity of unknown objects. To improve the sensitivity and specificity of classification, the raw data was preprocessed to reduce unwanted spectral variations by standard normal variate (SNV) transformation, taking second-order derivatives (D2) spectra, and smoothing. As the best model, the sensitivity and specificity reached 0.931 and 1.000 with SNV spectra. Combination of NIR spectrometry and statistical model selection can provide an effective and rapid method to discriminate the geographical producing area of Anxi-Tieguanyin. 10.1155/2014/704971

Discrimination of oolong tea (Camellia sinensis) varieties based on feature extraction and selection from aromatic profiles analysed by HS-SPME/GC-MS. Lin Jie,Zhang Pan,Pan Zhiqiang,Xu Hairong,Luo Yaoping,Wang Xiaochang Food chemistry This 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 of 75 oolong tea samples of five similar varieties (Tieguanyin, Benshan, Maoxie, Huangjingui and Jinguanyin) were analysed by headspace solid phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). The relative content of 26 major 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), 18 volatiles with the best discriminating capacity were selected, and 4 discriminant functions (DFs) enabled simultaneously discrimination of the five oolong varieties with 100% correct rate. 10.1016/j.foodchem.2013.02.128

2-DE combined with two-layer feature selection accurately establishes the origin of oolong tea. Chien Han-Ju,Chu Yen-Wei,Chen Chi-Wei,Juang Yu-Min,Chien Min-Wei,Liu Chih-Wei,Wu Chia-Chang,Tzen Jason T C,Lai Chien-Chen Food chemistry Taiwan is known for its high quality oolong tea. Because of high consumer demand, some tea manufactures mix lower quality leaves with genuine Taiwan oolong tea in order to increase profits. Robust scientific methods are, therefore, needed to verify the origin and quality of tea leaves. In this study, we investigated whether two-dimensional gel electrophoresis (2-DE) and nanoscale liquid chromatography/tandem mass spectroscopy (nano-LC/MS/MS) coupled with a two-layer feature selection mechanism comprising information gain attribute evaluation (IGAE) and support vector machine feature selection (SVM-FS) are useful in identifying characteristic proteins that can be used as markers of the original source of oolong tea. Samples in this study included oolong tea leaves from 23 different sources. We found that our method had an accuracy of 95.5% in correctly identifying the origin of the leaves. Overall, our method is a novel approach for determining the origin of oolong tea leaves. 10.1016/j.foodchem.2016.05.043

Rapid and direct identification of the origin of white tea with proton transfer reaction time-of-flight mass spectrometry. Zhang Dandan,Wu Weihua,Qiu Xiaohong,Li Xiaojing,Zhao Feng,Ye Naixing Rapid communications in mass spectrometry : RCM RATIONALE:White tea has become very popular in recent years, but there has been no scientific identification of white tea from different origins. For product authentication and valorization, every kind of white tea must be marked with an indication of its origin. METHODS:Volatile profiles of white tea leaf samples from their main origins in China (Fuding City, Zhenghe City and Jianyang City) were analyzed using proton transfer reaction time-of-flight mass spectrometry (PTR-TOFMS). Tentative identifications of the volatile organic compounds (VOCs) were obtained by PTR-TOFMS of the headspace. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed to evaluate the differences among the various origins. RESULTS:Teas from different origins were shown to have characteristic VOCs and profiles. Thus, white teas from different origins could be separated by characterizing the volatile emissions from the dry tea leaves. The ability of the two classification models to use the volatile fingerprints in origin discrimination was investigated. CONCLUSIONS:Two classification models (PCA and OPLS-DA) were applied to the PTR-TOFMS data obtained from the VOCs of various white teas. The classification models were shown to be useful in identifying the origin of white tea samples, providing a reference for white tea identification. 10.1002/rcm.8830