Consistent aroma characteristics are important for tea products. However, understanding the formation of tea aroma flavor and correspondingly proposing applicable protocols to control tea quality and consistency remain major challenges. Oolong tea is one of the most popular teas with a distinct flavor. Generally, oolong tea is processed with the leaves of tea trees belonging to different subspecies and grown in significantly different regions. In this study, Yunnan and Fujian oolong teas, green tea, black tea, and Pu-erh tea were collected from major tea estates across China. Their sensory evaluation, main water-soluble and volatile compounds were identified and measured. The sensory evaluation, total polysaccharide, caffeine, and catechin content of Yunnan oolong tea was found to be different from that of Fujian oolong tea, a result suggesting that the kinds of tea leaves used in Yunnan and Fujian oolong teas were naturally different. However, according to their aroma compounds, principal component analysis (PCA) and cluster analysis (CA) of the volatile compounds showed that the two types of oolong teas were similar and cannot be clearly distinguished from each other; they are also different from green, black, and Pu-erh teas, a result indicating that the same oolong tea processing technology applied to different tea leaves results in consistent aroma characteristics. The PCA analysis results also indicated that benzylalcohol, indole, safranal, linalool oxides, β-ionone, and hexadecanoic acid methyl ester highly contributed to the distinct aroma of oolong tea compared with the other three types of teas. This study proved that the use of the same processing technology on two kinds of tea leaves resulted in a highly consistent tea aroma.
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http://dx.doi.org/10.1186/s40064-016-2229-y | DOI Listing |
Food Chem Toxicol
January 2025
European Union Reference Laboratory for Pesticide Residues in Fruit & Vegetables, University of Almeria, Agrifood Campus of International Excellence (ceiA3), Ctra. Sacramento S/N°, La Cañada de San Urbano, 04120, Almería, Spain.
This study aimed to determine 9,10-anthraquinone (AQ) levels in Indonesian tea products from different manufacturers and assess the AQ's associated health risks. AQ levels increased significantly during withering and drying stages, using pinewood as a heat source. Generally, black tea was highly contaminated by AQ followed by green tea, oolong tea, and white tea.
View Article and Find Full Text PDFFoods
December 2024
Institute of Digital Agriculture, Fujian Academy of Agricultural Sciences, Fuzhou 350003, China.
Anxi Tieguanyin belongs to the oolong tea category and is one of the top ten most famous teas in China. In this study, hyperspectral imaging (HSI) technology was combined with chemometric methods to achieve the rapid determination of free amino acid and tea polyphenol contents in Tieguanyin tea. Here, the spectral data of Tieguanyin tea samples of four quality grades were obtained via visible near-infrared hyperspectroscopy in the range of 400-1000 nm, and the free amino acid and tea polyphenol contents of the samples were detected.
View Article and Find Full Text PDFJ Food Drug Anal
December 2024
Tea and Beverage Research Station (TBRS), No.324, Chung-Hsing RD., Yangmei, Taoyuan City 326011, Taiwan, R.O.C.
Taiwanese oolong tea is renowned for its excellent quality and enjoys a prestigious reputation both domestically and internationally. In recent years, there has been an issue with imported Taiwanese-style oolong tea being sold as genuine Taiwanese oolong tea, which has adversely affected the brand value of Taiwanese oolong tea. In this study, samples of domestic oolong tea (Taiwanese oolong tea) and Taiwanese-style oolong tea produced abroad (including China, Vietnam, Indonesia, Thailand, etc.
View Article and Find Full Text PDFInt J Radiat Biol
January 2025
Department of Pharmaceutical Sciences, Beijing Institute of Radiation Medicine, Beijing, China.
Purpose: Ionizing radiation (IR) could induce damage such as DNA damage and oxidative stress. Natural products, like tea, have been demonstrated potential in mitigating these damages. However, the lack of efficient and rapid screening methods for natural products hinders their widespread application.
View Article and Find Full Text PDFJ Sci Food Agric
December 2024
School of Food and Biological Engineering, Jiangsu University, Jiangsu, People's Republic of China.
Background: Accurate tea blending assessment and sample matching are critical in the tea production process. Traditional methods face efficiency and accuracy challenges, which can be addressed by advances in computer vision and deep learning. This study developed an efficient and non-destructive method for fast tea grading classification, blending ratio evaluation, and sample matching.
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