The shaking and standing processing improve the aroma quality of summer black tea.

Black teas harvested during the summer season usually have the defect of low aroma intensity, resulting in unacceptability from consumers. The shaking and standing (SS) process is key to the production of oolong tea and is believed to significantly improve the aroma quality. However, the specific effects of the shaking process on the aroma quality of black tea have not been elucidated. SSBT has a higher aroma intensity than BT, especially floral and sweet odors. By Aroma Extract Dilution Analysis (AEDA), 27 volatiles with flavor dilution factor (FD) above 8 were selected, of which 20 had odor activity values (OAV) values above 1; among them, 9 floral and sweet volatiles with high OAV were linalool (485 for BT, 918 for SSBT), (E)-ß-ionone (389, 699), geraniol (315, 493), ß-myrcene (25, 62), (E)-2-hexenal (2, 7), phenylacetaldehyde (44, 75), (Z)-3-hexenyl hexanoate (19, 41), 1-hexanol (9, 26), and 2-phenylethanol (2,3). Aroma reconstitution of these 20 volatiles showed reliable results of floral, sweet, fruity, and roasted odors, further validating the aroma and intensity profiles of the key odorants. Overall, our results reveal that the metabolite mechanism of the SS process improves the aroma quality of black tea, providing a theoretical basis and guiding measures for the production of high-aroma black tea.

Cost-effective colorimetric sensor for authentication of protected designation of origin (PDO) Longjing green tea.

Traceability and authentication of protected designation of origin (PDO) tea is an important prerequisite to safeguard its production and distribution system. Here, indicator displacement array (IDA) sensors consisting of natural anthocyanidins and edible metal ions were developed to authenticate PDO and non-PDO Longjing from different origins. Five IDA elements were selected for constructing sensors, achieved by an indicator displacement reaction after adding epigallocatechin gallate solution. The obtained sensors were subsequently used for real tea samples. Unsupervised algorithms were used for data exploration among PDO and non-PDO teas. The supervised support vector machine (SVM) model further achieved accurate authentication of PDO and non-PDO Longjing with a correct classification rate of 100% for the 26 validated samples. The developed IDA sensor thus achieves accurate authentication of PDO tea in a hazard-free and cost-efficient way, providing a useful tool for origin authentication of other agricultural products.

Revelation of volatile contributions in green teas with different aroma types by GC-MS and GC-IMS.

Aroma types of green teas associate with their commercial prices and consumer acceptance, mainly including floral-like (HX), chestnut-like (LX), and fresh (QX) aromas. However, the volatile differences and specificities in these aroma types are still unclear. Herein, Taiping Houkui green teas with HX, LX, and QX aromas were processed separately with the same fresh tea leaves. Ninety-four and seventy-eight volatiles were detected and identified by headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) and headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS), respectively. Candidate differential volatiles among the tea samples were determined by the variable importance in projection (VIP) of the partial least squares-discriminant analysis (PLS-DA) and were further confirmed by the relative odor activity value (ROAV) and odor description. The volatiles 1-hexanol, linalool oxide (furanoid), linalool, geraniol, (E)-ß-ionone, isoamyl acetate, and 2-methylpropanal enriched in HX and contributed to the floral-like aroma, while 3-methylbutanal, 2-ethyl-1-hexanol, indole, ß-damascone, and cedrol enriched in LX and contributed to the chestnut-like aroma. This study reveals the specificities and contributions of volatiles in green teas with different aromas, thus providing new insights into the molecular basis of different flavored teas, benefiting for their precision processing and targeted quality control.

Visual Monitoring of Fatty Acid Degradation during Green Tea Storage by Hyperspectral Imaging.

The reduction in freshness during green tea storage leads to a reduction in its commercial value and consumer acceptance, which is thought to be related to the oxidation of fatty acids. Here, we developed a novel and rapid method for the assessment of green tea freshness during storage. Hyperspectral images of green tea during storage were acquired, and fatty acid profiles were detected by GC-MS. Partial least squares (PLS) analysis was used to model the association of spectral data with fatty acid content. In addition, competitive adaptive reweighted sampling (CARS) was employed to select the characteristic wavelengths and thus simplify the model. The results show that the constructed CARS-PLS can achieve accurate prediction of saturated and unsaturated fatty acid content, with residual prediction deviation (RPD) values over 2. Ultimately, chemical imaging was used to visualize the distribution of fatty acids during storage, thus providing a fast and nondestructive method for green tea freshness evaluation.