Evidence map›Paper›PMID 42354164›Full record

ReviewFoods (Basel, Switzerland)2026

Mass Spectrometry-Based Lipidomics in Coffee: Linking Lipid Transformation to Flavor Formation and Quality Control.

Yanbing Wang, Xiaoyuan Wang, Ping Du, Xiaogang Liu

Abstract readReview
In one paragraph

Review in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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

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

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

4 authors.

Yanbing WangFaculty of Modern Agricultural Engineering, Kunming University of Science and Technology, Kunming 650500, China.ORCID 0000-0001-5051-3988
Xiaoyuan WangHorticulture Research Institute, Yunnan Academy of Agricultural Sciences, Kunming 650205, China.
Ping DuResearch Center for Analysis and Measurement, Kunming University of Science and Technology, Kunming 652094, China.
Xiaogang LiuFaculty of Modern Agricultural Engineering, Kunming University of Science and Technology, Kunming 650500, China.ORCID 0000-0002-6004-0712

Funding

Yunnan Province Science and Technology Department yfgrc202537; 202301AS070030; 202403AP140038; 202403AK140026
6 · The paper itself

Abstract

Mass spectrometry-based lipidomics has created new opportunities to investigate the role of lipids in coffee quality formation and stability across the production chain. Coffee lipids contribute to flavor precursor formation, aroma release, mouthfeel, and storage behavior, but their molecular remodeling during maturation, processing, roasting, and storage remains insufficiently integrated. This review summarizes recent progress in lipidomics methodologies relevant to coffee research, with emphasis on sample preparation, mass spectrometry platforms, data analysis, and the strengths and limitations of current lipid annotation strategies. It further examines how lipid profiles change during bean maturation, how they differ among coffee species and varieties, and how they are reshaped by postharvest processing, roasting, and storage. However, it is important to note that most of these associations are currently correlational rather than causal; direct evidence linking specific lipid species to particular sensory attributes remains limited. Existing studies suggest that lipid composition, rather than total lipid content alone, is more informative for understanding coffee quality differences and for identifying candidate markers associated with origin, processing method, roasting degree, and storage conditions. In particular, alterations in glycerolipids, glycerophospholipids, fatty acids, diterpenes, and other minor lipid constituents are increasingly associated with lipid oxidation, thermal degradation, and flavor-related transformations in coffee. However, current evidence is still limited by incomplete structural annotation, isomeric ambiguity, platform dependence, and the frequent gap between statistical discrimination and mechanistic validation. Future work integrating high-resolution mass spectrometry, ion mobility, targeted quantification, stable isotope tracing, sensory analysis, and multi-omics approaches will be essential to improve marker reliability and to clarify the functional roles of coffee lipids. Overall, lipidomics provides a promising framework for linking molecular composition with coffee quality control, traceability, and process optimization, although substantial work is still needed to establish mechanistic links to flavor formation.

Indexed as

aroma formationcoffeeflavor formationlipidomicsroastingstorage stability

Identifiers

PMID42354164
PMCPMC13297800

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.