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Liu Panpan

Researcher at Hunan Agricultural University

Publications -  41
Citations -  127

Liu Panpan is an academic researcher from Hunan Agricultural University. The author has contributed to research in topics: Brick & Chemistry. The author has an hindex of 4, co-authored 41 publications receiving 63 citations.

Papers
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Journal ArticleDOI

Chemical profile changes during pile fermentation of Qingzhuan tea affect inhibition of α-amylase and lipase.

TL;DR: Qualitative analysis showed that amino acids and flavonoids might be responsible for the anti-obesity and anti-hyperglycemic effects of QZT.
Journal ArticleDOI

Comparing characteristic aroma components of bead-shaped green teas from different regions using headspace solid-phase microextraction and gas chromatography–mass spectrometry/olfactometry combined with chemometrics

TL;DR: In this article, the aroma components of bead-shaped green teas were compared through headspace solid phase microextraction (HS-SPME) and gas chromatography-mass spectrometry/olfactometry (GC-MS/O) coupled with chemometrics.
Journal ArticleDOI

Gut microbiota-mediated improvement of metabolic disorders by Qingzhuan tea in high fat diet-fed mice

TL;DR: The results demonstrate that QZT extract can significantly prevent body weight gain, fat accumulation, and also reduce serum levels of total cholesterol and triglycerides, which is accompanied by a decrease in Firmicutes-to-Bacteroids ratio and relative abundance of S24-7 and Ruminococcaceae.
Journal ArticleDOI

Metabolomics Provides A Novel Interpretation of the Changes in Main Compounds during Black Tea Processing through Different Drying Methods.

TL;DR: In this paper, the effect of hot roller (HR) drying and hot air (HA) drying on the sensory evaluation, chemical quality, antioxidant activity, and metabolic profile of Yihong Congou black tea processed from E’cha NO1.
Patent

Method for judging geographic information of fresh tea leaves by utilizing near infrared spectrum

TL;DR: In this article, a method for judging geographic information of fresh tea leaves by utilizing near infrared spectrum is presented, which comprises the following steps of establishing a prediction model by utilizing a near infrared spectra of the fresh tea leaf with different geographic information, and then judging the geographic information according to the established prediction model.