ArticleRSC advances2021
Chemical characterization of Wuyi rock tea with different roasting degrees and their discrimination based on volatile profiles.
Article in RSC advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed, 49 citations in OpenAlex.
- Comprehensive elucidation of volatile, phenolic, and organic acid profiles in Turkish mallow (Malva sylvestris L.) petal herbal tea: impact of diverse brewing conditions.Journal of the science of food and agriculture · 2026Article
- Sensomics-based characterization of cinnamon-like aroma inFood chemistry: X · 2026Article
- Combined metabolomics and electronic tongue technology elucidated the mechanisms of regulation of color-taste characteristics of Huangqin (Food chemistry: X · 2025Article
- Machine learning based on metabolomics to discriminate Wuyi rock tea production areas and "rock flavor" substances.Food chemistry: X · 2025Article
- Comprehensive characterization of volatile compounds in Iranian black teas using chemometric analysis of GC-MS fingerprints.Food chemistry: X · 2024Article
- Differences in the Quality Components of Wuyi Rock Tea and Huizhou Rock Tea.Foods (Basel, Switzerland) · 2024Article
- Influences ofFoods (Basel, Switzerland) · 2024Article
- Exploring aromatic components differences and composition regularity of 5 kinds of these 4 aroma types Phoenix Dancong tea based on GC-MS.Scientific reports · 2024Article
- Characterization of the Key Aroma Compounds in Dong Ding Oolong Tea by Application of the Sensomics Approach.Foods (Basel, Switzerland) · 2023Article
- Widely targeted metabolomics analysis of different Wuyi Shuixian teas and association with taste attributes.Heliyon · 2023Article
- Aroma characteristics of Wuyi rock tea prepared from 16 different tea plant varieties.Food chemistry: X · 2023Article
- Metabolomics integrated with machine learning to discriminate the geographic origin of Rougui Wuyi rock tea.NPJ science of food · 2023Article
- Widely targeted metabolomics analysis reveals the formation of nonvolatile flavor qualities during oolong tea manufacturing: a case study of Jinguanyin.Frontiers in nutrition · 2023Article
- Characterization of the Key Aroma Compounds in Different Aroma Types of Chinese Yellow Tea.Foods (Basel, Switzerland) · 2022Article
- Insights into Characteristic Volatiles in Wuyi Rock Teas with Different Cultivars by Chemometrics and Gas Chromatography Olfactometry/Mass Spectrometry.Foods (Basel, Switzerland) · 2022Article
- Non-Targeted Metabolomics Analysis Revealed the Characteristic Non-Volatile and Volatile Metabolites in theFoods (Basel, Switzerland) · 2022Article
- Characterization of key aroma compounds and relationship between aroma compounds and sensory attributes in different aroma types of Fu brick tea.Food chemistry: X · 2022Article
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Wuyi rock tea is a typical and famous oolong tea in China and roasting is an important manufacturing procedure for its flavor formation. This work aimed to explore the effect of roasting on non-volatiles and volatiles of 12 Wuyi rock tea samples at three roasting levels (low, moderate and sufficient), made from four tea cultivars (Shuixian, Qizhong, Dahongpao, Rougui). Results show that different roasting had not caused significant difference on contents of soluble solids, total polyphenols, flavonoids, soluble sugar, thearubigins and theabrownins, while it slightly regulated caffeine, proteins and theaflavins, and remarkably reduced catechins and free amino acids. The ratio of polyphenol content/amino acid content, a negative-correlated indicator of fresh and brisk taste, significantly increased with the increase of roasting degree. High-level roasting not only decreased the fresh and brisk taste of the tea infusion, but also reduced the amount of bioactive ingredients including catechins and theanine. A total of 315 volatiles were detected and analyzed with OPLS-DA and HCA methods, in which 99 volatiles were found with variable importance in the projection (VIP) values greater than 1.00. Tea samples at different roasting degrees were successfully separated by this model of roasting-level discrimination. 'Naphthalene, 1,2,3,4-tetrahydro-1,6,8-trimethyl-', '1,1,5-trimethyl-1,2-dihydronaphthalene', '
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