ArticleFoods (Basel, Switzerland)2025
Development of Pretreatment Approaches for Authentic Representation of Tea Infusion Aroma.
Article in Foods (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Linking Tea Aroma Chemistry to Quality Grades via a Single MOS Gas Sensor: Classical Machine Learning vs. Deep Learning.Sensors (Basel, Switzerland) · 2026Article
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7 authors.
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Abstract
Appropriate aroma extraction methods are crucial prerequisites for accurately and objectively characterizing the authentic aroma profile of samples. Purified water and ionized water were used as brewing water, and the effects of different tea-to-water ratios, extraction temperatures, and extraction times on the aroma authenticity and component enrichment of tea infusions were compared. The conditions of a tea-to-water ratio of 1 g:10 mL, extraction at 30 °C for 30 or 45 min were identified as the optimal parameter range, which could maximize the enrichment of aroma while maintaining fidelity. The cosine value of the aroma attribute scores between the optimal parameter set and the control group (tea brewed at 1 g:10 mL ratio for 4 min) exceeded 0.979, and the correlation coefficient surpassed 0.828. Test evaluation results indicate the method had good reproducibility and effectively highlighted the differential impacts of ionic content in brewing water on tea aroma constituents. This approach effectively solved the problem of sensory distortion caused by conventional high-temperature and long-duration extraction, enabling precise analysis of how water quality authentically influences tea infusion aroma characteristics.
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