Evidence map›Paper›PMID 41867951›Full record

ArticleFrontiers in chemistry2026

Analysis of volatile compounds in

Pengfei Yang, Lingqi Kong, Qiongbo Wang, Qiang Liu, Xiujin Duan, Chen Hu, Zhengbo Feng, Qi Yang, Huabo Jv

Abstract read
In one paragraph

Article in Frontiers in chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed.

  1. Article
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.

Pengfei YangCollege of Tobacco Science and Engineering, Zhengzhou University of Light Industry, Zhengzhou, Henan, China.
Lingqi KongCollege of Tobacco Science and Engineering, Zhengzhou University of Light Industry, Zhengzhou, Henan, China.
Qiongbo WangSchool of Public Health and Nutrition, Luohe Medical College, Luohe, Henan, China.
Qiang LiuTechnology Center, China Tobacco Henan Industrial Co., Ltd., Zhengzhou, Henan, China.
Xiujin DuanCollege of Tobacco Science and Engineering, Zhengzhou University of Light Industry, Zhengzhou, Henan, China.
Chen HuCollege of Tobacco Science and Engineering, Zhengzhou University of Light Industry, Zhengzhou, Henan, China.
Zhengbo FengCollege of Tobacco Science and Engineering, Zhengzhou University of Light Industry, Zhengzhou, Henan, China.
Qi YangTechnology Center, China Tobacco Henan Industrial Co., Ltd., Zhengzhou, Henan, China.
Huabo JvGansu Tobacco Quality Supervision & Test Station, China National Tobacco Corporation, Lanzhou, Gansu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: To investigate the impact of different processing methods on the volatile components in Methods: Headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry and electronic nose (E-Nose) analysis were employed to characterize volatiles of extracts obtained by ultrasound-assisted extraction (UAE), microwave-assisted extraction (MAE), and heated reflux extraction (HRE). Multidimensional assessment using aroma radar charts, orthogonal partial least squares-discriminant analysis (OPLS-DA), K-means clustering, and relative odor activity value (ROAV) revealed significant processing-dependent variations. Results and discussion: The results indicated that the fiber coated with DVB/CAR/PDMS had optimal extraction efficiency. A total of 46 compounds were identified, including eight alcohols, four aldehydes, one acid, 25 terpenes, seven ketones, and one heterocyclic compound. UAE and MAE had 36 and 38 compounds respectively, sharing similar compositional profiles but differing in concentrations, while HRE produced only 25 compounds Sensory evaluation and E-Nose results revealed differences in the aroma profiles of the extracts, with UAE and MAE extracts exhibiting intensified floral and sweet notes, whereas HRE displayed prominent green and spicy characteristics. K-means clustering categorized volatile evolution trends into four distinct subclasses. OPLS-DA identified 13 differential volatiles with variable importance in projection greater than 1, with ROAV analysis further selecting eight key markers, including (1R,7

Indexed as

Aglaia odorata flower extractsheadspace solid phase microextraction-gas chromatography-mass spectrometrymultivariate statistical analysisrelative odor activity valuevolatile components

Identifiers

PMID41867951
PMCPMC13003520

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.