Evidence map›Paper›PMID 39861551›Full record

ArticlePlants (Basel, Switzerland)2025

The Optimization of the Debittering Process and the Exploration of Bitter Metabolites of

Shuting Li, Yanfeng Xu, Xinyue Liu, Qizhen Su, Junyu Zhang, Xinran Zhang, Xinmiao Guo, Yanlong Zhang, Qingyu Zhang

Abstract read
In one paragraph

Article in Plants (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

What it found

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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.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Shuting LiCollege of Landscape Architecture and Arts, Northwest Agriculture and Forestry University, Yangling 712100, China.
Yanfeng XuCollege of Landscape Architecture and Arts, Northwest Agriculture and Forestry University, Yangling 712100, China.
Xinyue LiuCollege of Landscape Architecture and Arts, Northwest Agriculture and Forestry University, Yangling 712100, China.
Qizhen SuQinling National Botanical Garden, Xi'an 710061, China.
Junyu ZhangLongchi Peony Industry Co., Ltd., Heze 274000, China.
Xinran ZhangCollege of Landscape Architecture and Arts, Northwest Agriculture and Forestry University, Yangling 712100, China.
Xinmiao GuoCollege of Landscape Architecture and Arts, Northwest Agriculture and Forestry University, Yangling 712100, China.
Yanlong ZhangCollege of Landscape Architecture and Arts, Northwest Agriculture and Forestry University, Yangling 712100, China.ORCID 0000-0001-8931-2171
Qingyu ZhangCollege of Landscape Architecture and Arts, Northwest Agriculture and Forestry University, Yangling 712100, China.ORCID 0009-0002-0778-3231

Funding

Shaanxi Postdoctoral Research Project ,General Supported by China Postdoctoral Science Foundation,the Program for Shaanxi Natural Science Basic Research Plan Project Grant no. 2019M663845,2024JC-YBMS-166,2018BSHTDZZ91
6 · The paper itself

Abstract

Tree peony seeds, traditionally used for edible oil production, are rich in α-linolenic acid (ALA). However, little attention is paid to their development as a healthcare food due to their bitter and astringent taste. The aim of this study was to optimize the debittering process of peony seeds on the basis of maintaining nutritional value and to identify the compounds that cause the taste of bitterness. We first optimized the debittering process by orthogonal experiments which reduced the polyphenol content by 90.25%, and we measured the main nutritional value of fatty acid composition, indicating that the high content of ALA is not affected by debittering. Then, we identified and determined the types and content of polyphenols, the metabolites causing bitter taste, in the samples based on LC-ESI-QQQ-MS. Principal component analysis (PCA) and orthogonal partial least square discriminant analysis (OPLS-DA) were used to compare and analyze the seeds at different stages of debittering. Thirty-eight key metabolites were identified, of which paeoniflorin, taxifolin, alibiflorin, protocatechuic acid, benzoyl paeoniflorin, quercetin-

Indexed as

bitternessLC-ESI-QQQ-MSpolyphenolic metabolitestree peony seed

Identifiers

PMID39861551
PMCPMC11769413

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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.