Evidence map›Paper›PMID 33282238›Full record

ArticleFood science & nutrition2020

Nondestructive monitoring of polyphenols and caffeine during green tea processing using Vis-NIR spectroscopy.

Alireza Sanaeifar, Xinyao Huang, Mengyuan Chen, Zhangfeng Zhao, Yifan Ji, Xiaoli Li, Yong He, Yi Zhu, Xi Chen, Xinxin Yu

Abstract read
In one paragraph

Article in Food science & nutrition, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Alireza SanaeifarCollege of Biosystems Engineering and Food Science Zhejiang University Hangzhou China.ORCID https://orcid.org/0000-0002-4582-7963
Xinyao HuangCollege of Biosystems Engineering and Food Science Zhejiang University Hangzhou China.
Mengyuan ChenCollege of Biosystems Engineering and Food Science Zhejiang University Hangzhou China.
Zhangfeng ZhaoCollege of Mechanical Engineering Zhejiang University of Technology Hangzhou China.
Yifan JiCollege of Biosystems Engineering and Food Science Zhejiang University Hangzhou China.
Xiaoli LiCollege of Biosystems Engineering and Food Science Zhejiang University Hangzhou China.ORCID https://orcid.org/0000-0001-9689-9054
Yong HeCollege of Biosystems Engineering and Food Science Zhejiang University Hangzhou China.
Yi ZhuCollege of Biosystems Engineering and Food Science Zhejiang University Hangzhou China.
Xi ChenCollege of Biosystems Engineering and Food Science Zhejiang University Hangzhou China.
Xinxin YuCollege of Biosystems Engineering and Food Science Zhejiang University Hangzhou China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Increasing consumption of green tea is attributed to the beneficial effects of its constituents, especially polyphenols, on human health, which can be varied during leaf processing. Processing technology has the most important effect on green tea quality. This study investigated the system dynamics of eight catechins, gallic acid, and caffeine in the processing of two varieties of tea, from fresh leaves to finished tea. It was found that complex biochemical changes can occur through hydrolysis under different humidity and heating conditions during the tea processing. This process had a significant effect on catechin composition in the finished tea. The potential application of visible and near-infrared (Vis-NIR) spectroscopy for fast monitoring polyphenol and caffeine contents in tea leaves during the processing procedure has been investigated. It was found that a combination of PCA (principal component analysis) and Vis-NIR spectroscopy can successfully classify the two varieties of tea samples and the five tea processing procedures, while quantitative determination of the constituents was realized by combined regression analysis and Vis-NIR spectra. Furthermore, successive projections algorithm (SPA) was proposed to extract and optimize spectral variables that reflected the molecular characteristics of the constituents for the development of determination models. Modeling results showed that the models had good predictability and robustness based on the extracted spectral characteristics. The coefficients of determination for all calibration sets and prediction sets were higher than 0.862 and 0.834, respectively, which indicated high capability of Vis-NIR spectroscopy for the determination of the constituents during the leaf processing. Meanwhile, this analytical method could quickly monitor quality characteristics and provide feedback for real-time controlling of tea processing machines. Furthermore, the study on complex biochemical changes that occurred during the tea processing would provide a theoretical basis for improving the content of quality components and effective controlling processes.

Indexed as

caffeinegreen tealeaf processingpolyphenolsquantification modelvisible and near‐infrared (Vis‐NIR) spectroscopy

Identifiers

PMID33282238
PMCPMC7684591

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.