ArticlePloS one2018
Characterization of the volatile components in green tea by IRAE-HS-SPME/GC-MS combined with multivariate analysis.
Article in PloS one, 2018. 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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Who cites it
17 citing papers in PubMed.
- Volatile Organic Compounds in Teas: Identification, Extraction, Analysis, and Application of Tea Aroma.Foods (Basel, Switzerland) · 2025Review
- Effect of Blue Light Intensity During Spreading on the Aroma of Green Tea.Foods (Basel, Switzerland) · 2025Article
- The characterization of sensory properties, aroma profile and antioxidant capacity of noodles incorporated with asparagus tea ultra-micro powder.Food chemistry: X · 2025Article
- Analysis of the release pattern of floral aroma components of Rhus chinensis based on HS-SPME-GC-MS technique.PloS one · 2025Article
- Comprehensive characterization of volatile compounds in Iranian black teas using chemometric analysis of GC-MS fingerprints.Food chemistry: X · 2024Article
- The Light-Intensity-Affected Aroma Components of Green Tea during Leaf Spreading.Foods (Basel, Switzerland) · 2024Article
- Comparative Analysis of Metabolome and Transcriptome in Different Tissue Sites ofMolecules (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
- Influence of elongation and desaturation on chemosensory properties in acrylates and their corresponding 1-alken-3-ones.Analytical and bioanalytical chemistry · 2022Article
- HS-SPME/GC-MS Reveals the Season Effects on Volatile Compounds of Green Tea in High-Latitude Region.Foods (Basel, Switzerland) · 2022Article
- Effect ofFoods (Basel, Switzerland) · 2022Article
- Effects of Tea Powder on the Cooking Properties, Antioxidative Potential and Volatile Profiles of Dried Noodles.Foods (Basel, Switzerland) · 2022Article
- Volatile 1-octanol of tea (Camellia sinensis L.) fuels cell division and indole-3-acetic acid production in phylloplane isolate Pseudomonas sp. NEEL19.Scientific reports · 2021Article
- Endophytic fungus, Chaetomium globosum, associated with marine green alga, a new source of Chrysin.Scientific reports · 2020Article
- Analysis of the Volatile Components in Selaginella doederleinii by Headspace Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry.Molecules (Basel, Switzerland) · 2019Article
- Analysis of volatile compounds in fresh sturgeon with different preservation methods using electronic nose and gas chromatography/mass spectrometry.RSC advances · 2019Article
- Comparison of volatile components in fresh and driedFood science and biotechnology · 2019Article
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Authors and funding
6 authors.
Funding
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Abstract
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.
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