Evidence map›Paper›PMID 38933883›Full record

ArticleFrontiers in nutrition2024

Traditional method of rhubarb processing optimized by combining flavor analysis with anthraquinone content determination.

Taotao Liu, Miao Yu, Yue Dai, Yongqing Xiao, Li Li

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 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

5 authors.

Taotao LiuInstitute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China.
Miao YuInstitute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China.
Yue DaiInstitute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China.
Yongqing XiaoInstitute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China.
Li LiInstitute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Rhubarb is a popular food that relieves constipation and aids with weight loss. The traditional method of preparation, includes steaming and sun-drying rhubarb nine times (SDR-9) to reduce its toxicity and increase efficacy. Methods: Flavor analysis includes odor analysis by gas chromatography-ion mobility spectrometry and taste characterization using an electronic tongue. Results: Odor analysis of the samples prepared through SDR-9 identified 61 volatile compounds, including aldehydes, esters, alcohols, ketones, acids, alkenes, and furans. Of these, 13 volatile components were the key substances associated with odor. This enabled the process to be divided into two stages: 1-5 times of steaming and sun-drying and 6-9 times. In the second stage, SDR-6 and SDR-9 were grouped together in terms of odor. Analysis using electronic tongue revealed that the most prominent taste was bitterness. A radar map indicated that the bitterness response was the highest for raw rhubarb, whereas that for processed (steamed and sun-dried) rhubarb decreased. Orthogonal partial least squares discriminant analysis (OPLS-DA) clustering results for SDR-6 and SDR-9 samples indicated that their tastes were similar. Anthraquinones were analyzed via high-performance liquid chromatography; moreover, analysis of the taste and components of the SDR samples revealed a significant correlation. Discussion: These results indicate that there are similarities between SDR-6 and SDR-9 in terms of smell, taste, and composition, indicating that the steaming and sun-drying cycles can be conducted six times instead of nine.

Indexed as

electronic tonguegas chromatography-ion mobility spectrometryhigh-performance liquid chromatographyrhubarbtaste flavor

Identifiers

PMID38933883
PMCPMC11199713

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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.