Evidence map›Paper›PMID 40238322›Full record

ReviewFoods (Basel, Switzerland)2025

Applications of Microextraction Technology for the Analysis of Alcoholic Beverages Quality: Current Perspectives and Future Directions.

Yue Qiu, Qi Deng, Yongqing Zhang, Baoguo Sun, Wenxian Li, Wei Dong, Xiaotao Sun

Abstract readReview
In one paragraph

Review in Foods (Basel, Switzerland), 2025. 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

7 authors.

Yue QiuBeijing Laboratory of Food Quality and Safety, Beijing Technology and Business University, Beijing 100048, China.
Qi DengBeijing Laboratory of Food Quality and Safety, Beijing Technology and Business University, Beijing 100048, China.
Yongqing ZhangBeijing Laboratory of Food Quality and Safety, Beijing Technology and Business University, Beijing 100048, China.
Baoguo SunBeijing Laboratory of Food Quality and Safety, Beijing Technology and Business University, Beijing 100048, China.
Wenxian LiBeijing Laboratory of Food Quality and Safety, Beijing Technology and Business University, Beijing 100048, China.
Wei DongBeijing Laboratory of Food Quality and Safety, Beijing Technology and Business University, Beijing 100048, China.ORCID 0000-0002-0360-4163
Xiaotao SunBeijing Laboratory of Food Quality and Safety, Beijing Technology and Business University, Beijing 100048, China.

Funding

National Key R&D Program of China 2022YFD2101205National Natural Science Foundation of China 32102122
6 · The paper itself

Abstract

Alcoholic beverages are loved by the majority of consumers because of their diverse characteristics and rich nutritional value; thus, ensuring their quality is necessary for maintaining the rapid development of the alcoholic beverage industry. Due to trace levels of various quality factors and the complexity of the beverage body matrix, pretreatment is usually required before analysis. Among the many pretreatment methods available, microextraction has attracted increasing attention because it aligns with the development direction of green chemistry. This review surveys advancements in microextraction techniques pertaining to three quality aspects in the most frequently consumed alcoholic beverages: baijiu and huangjiu (spirits) and wine and beer (fermented alcoholic drinks). Furthermore, new directions in their development are discussed.

Indexed as

alcoholic beveragesliquid-phase microextractionmicroextractionqualitysolid-phase microextraction

Identifiers

PMID40238322
PMCPMC11988442

What OpenQuestion 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 OpenQuestion graph.