Comparative analysis of volatiles difference of Yunnan sun-dried Pu-erh green tea from different tea mountains: Jingmai and Wuliang mountain by chemical fingerprint similarity combined with principal component analysis and cluster analysis

Exploring aromatic components differences and composition regularity of 5 kinds of these 4 aroma types Phoenix Dancong tea based on GC-MS

Different aromatic components do indeed give different tea flavors. There is still little research on whether there is a certain regularity in the combination and content of aromatic components in different aroma types of Phoenix Dancong (PDC) tea. This potential regularity may be a key factor in unraveling the relationship between reproduction and evolution in PDC tea. Here, the 5 kinds of these 4 aroma types PDC tea (Zhuye, Tuofu, Jianghuaxiang, Juduo, Yashixiang) were used as research materials in this study, the headspace solid-phase microextraction combined with gas chromatography-mass spectrometry was used to analyze the aromatic components of these PDC teas. The results showed a total of 36 aromatic components identified in this study. When conducting cluster analysis, it was found that similarity degree arrangement sequence of 5 PDC teas was Juduo, Tuofu, Yashixiang, Zhuye and Jianghuaxiang. Among these aromatic components, the 7,9-Di-tert-butyl-1-oxaspiro(4,5)deca-6,9-diene-2,8-dione, the 2-Cyclopenten-1-one, 3-methyl-2-(2-pentenyl)-,(Z)-, the 2,4-Di-tert-butylphenol, the 3,7-dimethyl-1,5,7-Octatrien-3-ol, and the 2-Furanmethanol,5-ethenyltetrahydro-.alpha.,.alpha.,5-trimethyl-,cis- are common to 5 PDC teas. This study aims to elucidate the similarities in the aromatic components of 5 PDC teas, revealing the major aroma-endowed substances of various aroma, and providing theoretical reference for further exploring the relationship between aroma type discrimination, variety selection, and evolution of PDC teas.

Theogallin-to-Gallic-Acid Ratio as a Potential Biomarker of Pu-Erh Teas

There are two types of Pu-erh tea available on the world market: Raw and Ripe. It is not difficult to tell them apart if the Raw version is relatively young. Researchers have already developed various tools to identify Pu-erh teas. However, they are quite complicated and require advanced statistical analyses. In addition, they are characterized by different levels of accuracy. The aim of the work was to identify relationships or differences that would easily give specific results for identifying types of Pu-erh tea. The content of selected methylxanthines was determined by high-performance liquid chromatography (HPLC) on an Agilent 1200 chromatograph with a UV-VIS diode array detector. The total analysis time was 28 min. A combination of liquid chromatography and a triple quadrupole mass spectrophotometer was used to identify gallic acid and theogallin in the analyzed samples. A multivariate cluster analysis was used to compare the results for single samples, and its results were presented in horizontal hierarchical tree plots. The quantitative determination showed that theophylline is present only in Ripe Pu-erh teas. In addition, it was shown that the ratio of theogallin to gallic acid can be an effective tool to verify the authenticity of Pu-erh varieties.

Comparative analysis of Fenghuang Dancong, Tieguanyin, and Dahongpao teas using headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry and chemometric methods

Fenghuang Dancong, Tieguanyin, and Dahongpao teas are belonged to semi-fermented oolong teas and are famous for their unique aroma. However, reports regarding the systematic comparison, differentiation, and classification of the volatile components of these three types of oolong teas are lacking. In this study, we aimed to establish a method for distinguishing these three types of oolong teas. The volatile components in a total of 21 tea samples of these three types of oolong teas were extracted, determined, and identified by headspace solid-phase microextraction (HS-SPME) combined with gas chromatography-mass spectrometry (GC-MS). In addition, chemometric methods such as hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were used for distinguishing and classifying the three types of oolong teas on the basis of the similarities and differences in the volatile components. The results showed that 125 volatile components were extracted and identified from the three types of oolong teas, among which 53 volatile components overlapped among the samples. The results of HCA indicated that the samples of each of the three types of oolong teas could be placed in one category when the t value was 220. The results of PCA and OPLS-DA showed that the volatile components such as dehydrolinalool, linalool oxide II, linalool, α-farnesene, linalool oxide I, β-ocimene, nerolidol, cis-3-butyric acid folate, myrcene, and (Z)-hexanoic acid-3-hexenyl ester are the characteristic components, which can be used to distinguish the three types of oolong teas. We developed a simple, fast, and efficient method for distinguishing three types of oolong teas and provided a feasible technique for the identification of oolong tea types.

Amorphous and Co-Amorphous Olanzapine Stability in Formulations Intended for Wet Granulation and Pelletization

The preparation of amorphous and co-amorphous systems (CAMs) effectively addresses the solubility and bioavailability issues of poorly water-soluble chemical entities. However, stress conditions imposed during common pharmaceutical processing (e.g., tableting) may cause the recrystallization of the systems, warranting close stability monitoring throughout production. This work aimed at assessing the water and heat stability of amorphous olanzapine (OLZ) and OLZ-CAMs when subject to wet granulation and pelletization. Starting materials and products were characterized using calorimetry, diffractometry and spectroscopy, and their performance behavior was evaluated by dissolution testing. The results indicated that amorphous OLZ was reconverted back to a crystalline state after exposure to water and heat; conversely, OLZ-CAMs stabilized with saccharin (SAC), a sulfonic acid, did not show any significant loss of the amorphous content, confirming the higher stability of OLZ in the CAM. Besides resistance under the processing conditions of the dosage forms considered, OLZ-CAMs presented a higher solubility and dissolution rate than the respective crystalline counterpart. Furthermore, in situ co-amorphization of OLZ and SAC during granule production with high fractions of water unveils the possibility of reducing production steps and associated costs.

The Effect of Green Tea (Camellia sinensis) Leaf Powder on Growth Performance, Selected Hematological Indices, Carcass Characteristics and Meat Quality Parameters of Jumbo Quail

Green tea leaves contain a wide range of active bio-compounds that are essential for sustainable quail intensification; however, its feed value is not known for the Jumbo quail. Therefore, this study evaluated the effect of different levels of green tea leaf powder (GTLP) on physiological and meat quality parameters of the Jumbo quail. One-week-old chicks (n = 350; 56.1 ± 2.12 g live-weight) were evenly distributed to 35 replicate pens and reared on five experimental diets formulated as follows: a standard grower diet with zinc-bacitracin (PosCon), a standard grower diet without zinc-bacitracin (NegCon), and NegCon diet treated with 10 (GT10), 25 (GT25) and 50 g/kg (GT50) of GTLP. Weight gain linearly decreased in week 2 but increased in week 4, whereas feed conversion efficiency linearly declined in weeks 2 and 3 as GTLP levels increased. Overall feed intake, carcass yield, and caecum and colon weights showed a linear increase with GTLP levels. Hematological parameters fell within the normal ranges reported for healthy quail. The GT10 group showed larger liver weights than the PosCon and NegCon groups. It was concluded that dietary inclusion of GTLP enhances overall feed intake and carcass performance but not feed efficiency, hematological and meat quality parameters of Jumbo quail.

Rapid classification of commercial teas according to their origin and type using elemental content with X-ray fluorescence (XRF) spectroscopy

The authenticity of tea has become more important to the industry while the supply chains become complex. The quality and price of tea produced in different regions varies greatly. Currently, a rapid analytical method for testing the geographical origin of tea is missing. XRF is emerging as a screening technique for mineral and elemental analysis with applications in the traceability of foodstuffs, including tea. This study aims to develop a reliable multivariate classification model using XRF spectroscopy to obtain the mineral content. A total of 75 tea samples from tea producing countries throughout the world were analysed. After variable shortlisting, 18 elements were used to construct the multivariate models. Tea origin was determined by classifying the tea into 5 major geographical regions producing most of the global tea. PCA showed initial clustering in some regions, although the types of teas included in the study (black, green, white, herbal) showed no discrete cluster membership. The prediction power of each classification model developed was determined by using two multivariate classifiers, SIMCA and PLS-DA, against an independent validation set. The average overall correct classification rates of PLS-DA models were between 54-85% while the results of SIMCA models were between 70-84% resolving the poor clustering initially shown by PCA. This study demonstrated the potential of geographical origin of tea prediction using elemental contents of tea. Naturally, the classification can be linked not only to origin but to the type of tea as well.

Practical application

Wholesalers and retailers need a rapid and robust screening tool to confirm the origin and type of tea they sell to consumers. X-Ray fluorescence spectroscopy proved a good technique for achieving this in commercial teas sourced worldwide. Building on multivariate models, broad classification was accomplished both in terms of origin (Asian vs non-Asian) and in tea type with zero sample preparation and low cost of analysis.

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Investigated if elemental content (XRF) can indicate origin of commercial teas.

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Only 18 elements were selected for analysis based on their repeatability performance.

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Multivariate classification was used to classify in five or two global regions.

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Asian vs non-Asian classification reached 85% correct prediction rate.

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Classification linked not only with origin but with type of tea as well.

Comparison of volatile profiles and bioactive components of sun-dried Pu-erh tea leaves from ancient tea plants on Bulang Mountain measured by GC-MS and HPLC

To explore the volatile profiles and the contents of ten bioactive components (polyphenols and caffeine) of sun-dried Pu-erh tea leaves from ancient tea plants on Bulang Mountain, 17 samples of three tea varieties were analyzed by headspace-solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) and high-performance liquid chromatography (HPLC). A total of 75 volatile components were tentatively identified. Laomaner (LME), Laobanzhang (LBZ), and other teas on Bulang Mountain (BL) contained 70, 53, and 71 volatile compounds, respectively. Among the volatile compounds, alcohols (30.2%-45.8%), hydrocarbons (13.7%-17.5%), and ketones (12.4%-23.4%) were qualitatively the most dominant volatile compounds in the different tea varieties. The average content of polyphenol was highest in LME (102.1 mg/g), followed by BL (98.7 mg/g) and LBZ (88.0 mg/g), while caffeine showed the opposite trend, 27.3 mg/g in LME, 33.5 mg/g in BL, and 38.1 mg/g in LBZ. Principal component analysis applied to both the volatile compounds and ten bioactive components showed a poor separation of samples according to varieties, while partial least squares-discriminant analysis (PLS-DA) showed satisfactory discrimination. Thirty-four volatile components and five bioactive compounds were selected as major discriminators (variable importance in projection (VIP) >1) among the tea varieties. These results suggest that chromatographic data combined with multivariate analysis could provide a useful technique to characterize and distinguish the sun-dried Pu-erh tea leaves from ancient tea varieties on Bulang Mountain.

Quality consistency evaluation of Kudiezi Injection based on multivariate statistical analysis of the multidimensional chromatographic fingerprint

Traditional Chinese Medicine Injection (TCMI) was restricted due to the batch-to-batch variability caused by the variable compositions of botanical raw materials and complexities of the current manufacturing process. To evaluate and control the quality of Kudiezi Injection (KDZI), a comprehensive and practical method based on multidimensional chromatographic fingerprint associated with multivariate statistical analysis was proposed. The multidimensional chromatographic fingerprint was established by integrating three kinds of chromatographic fingerprints, including High Performance Liquid Chromatography-Ultraviolet spectrum (HPLC-UV), Gas Chromatography-Mass Spectrometer (GC-MS) and High performance ion-exchange chromatography (HPIEC), which were used to detect flavones, nucleosides, organic acids, amino acids and saccharides in KDZI. In addition, four main multivariate statistical analyses were compared to assess the batch-to-batch consistency of samples. Results showed that the cosine method, which has been widely used in the quality evaluation of TCM, failed to distinguish the differences among batches based on neither chromatographic peaks' area nor contents information. t-test and Bayes' theorem could reveal the content difference among batches, while hierarchical clustering analysis could differentiate KDZI batches, and Luteolin-7-O-β-D-glucuronopyranoside, Tau, Ser, guanine and allose were the main indicators. In conclusion, multidimensional chromatographic fingerprints could reflect the quality information of KDZI comprehensively and hierarchical clustering analysis was suitable to identify the differences among batches. This could provide an integrated method for consistency evaluation of TCMI, process improvement of TCMI and solving similar problems in TCMI.

Characterization of the volatile components in green tea by IRAE-HS-SPME/GC-MS combined with multivariate analysis

In the present work, a novel infrared-assisted extraction coupled to headspace solid-phase microextraction (IRAE-HS-SPME) followed by gas chromatography-mass spectrometry (GC-MS) was developed for rapid determination of the volatile components in green tea. The extraction parameters such as fiber type, sample amount, infrared power, extraction time, and infrared lamp distance were optimized by orthogonal experimental design. Under optimum conditions, a total of 82 volatile compounds in 21 green tea samples from different geographical origins were identified. Compared with classical water-bath heating, the proposed technique has remarkable advantages of considerably reducing the analytical time and high efficiency. In addition, an effective classification of green teas based on their volatile profiles was achieved by partial least square-discriminant analysis (PLS-DA) and hierarchical clustering analysis (HCA). Furthermore, the application of a dual criterion based on the variable importance in the projection (VIP) values of the PLS-DA models and on the category from one-way univariate analysis (ANOVA) allowed the identification of 12 potential volatile markers, which were considered to make the most important contribution to the discrimination of the samples. The results suggest that IRAE-HS-SPME/GC-MS technique combined with multivariate analysis offers a valuable tool to assess geographical traceability of different tea varieties.

DNA barcode and identification of the varieties and provenances of Taiwan's domestic and imported made teas using ribosomal internal transcribed spacer 2 sequences

The major aim of made tea identification is to identify the variety and provenance of the tea plant. The present experiment used 113 tea plants [Camellia sinensis (L.) O. Kuntze] housed at the Tea Research and Extension Substation, from which 113 internal transcribed spacer 2 (ITS2) fragments, 104 trnL intron, and 98 trnL-trnF intergenic sequence region DNA sequences were successfully sequenced. The similarity of the ITS2 nucleotide sequences between tea plants housed at the Tea Research and Extension Substation was 0.379–0.994. In this polymerase chain reaction-amplified noncoding region, no varieties possessed identical sequences. Compared with the trnL intron and trnL-trnF intergenic sequence fragments of chloroplast cpDNA, the proportion of ITS2 nucleotide sequence variation was large and is more suitable for establishing a DNA barcode database to identify tea plant varieties. After establishing the database, 30 imported teas and 35 domestic made teas were used in this model system to explore the feasibility of using ITS2 sequences to identify the varieties and provenances of made teas. A phylogenetic tree was constructed using ITS2 sequences with the unweighted pair group method with arithmetic mean, which indicated that the same variety of tea plant is likely to be successfully categorized into one cluster, but contamination from other tea plants was also detected. This result provides molecular evidence that the similarity between important tea varieties in Taiwan remains high. We suggest a direct, wide collection of made tea and original samples of tea plants to establish an ITS2 sequence molecular barcode identification database to identify the varieties and provenances of tea plants. The DNA barcode comparison method can satisfy the need for a rapid, low-cost, frontline differentiation of the large amount of made teas from Taiwan and abroad, and can provide molecular evidence of their varieties and provenances.

"Turn-off" fluorescent sensor for highly sensitive and specific simultaneous recognition of 29 famous green teas based on quantum dots combined with chemometrics

Fluorescent "turn-off" sensors based on water-soluble quantum dots (QDs) have drawn increasing attention owing to their unique properties such as high fluorescence quantum yields, chemical stability and low toxicity. In this work, a novel method based on the fluorescence "turn-off" model with water-soluble CdTe QDs as the fluorescent probes for differentiation of 29 different famous green teas is established. The fluorescence of the QDs can be quenched in different degrees in light of positions and intensities of the fluorescent peaks for the green teas. Subsequently, with aid of classic partial least square discriminant analysis (PLSDA), all the green teas can be discriminated with high sensitivity, specificity and a satisfactory recognition rate of 100% for training set and 98.3% for prediction set, respectively. Especially, the "turn-off" fluorescence PLSDA model based on second-order derivatives (2nd der) with reduced least complexity (LVs = 3) was the most effective one for modeling. Most importantly, we further demonstrated the established "turn-off" fluorescent sensor mode has several significant advantages and appealing properties over the conventional fluorescent method for large-class-number classification (LCNC) of green teas. This work is, to the best of our knowledge, the first report on the rapid and effective identification of so many kinds of famous green teas based on the "turn-off" model of QDs combined with chemometrics, which also implies other potential applications on complex LCNC classification system with weak fluorescence or even without fluorescence to achieve higher detective response and specificity.