Evidence map›Paper›PMID 40258936›Full record

ArticleScientific reports2025

Volatile organic compounds (VOCs) fingerprinting combined with complex network analysis as a forecasting tool for tracing the origin and genetic lineage of Arabica specialty coffees.

Cosimo Taiti, Gianna Vivaldo, Stefano Mancuso, Diego Comparini, Camilla Pandolfi

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

5 authors.

Cosimo TaitiDepartment of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, Viale Delle Idee 30, 50019, Sesto Fiorentino, Firenze, Italy.
Gianna VivaldoInstitute of Geosciences and Earth Resources (IGG), National Research Council of Italy (CNR), Via Moruzzi 1, 56124, Pisa, Italy. gianna.vivaldo@igg.cnr.it.
Stefano MancusoDepartment of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, Viale Delle Idee 30, 50019, Sesto Fiorentino, Firenze, Italy.
Diego CompariniDepartment of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, Viale Delle Idee 30, 50019, Sesto Fiorentino, Firenze, Italy.
Camilla PandolfiDepartment of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, Viale Delle Idee 30, 50019, Sesto Fiorentino, Firenze, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to the globalization of coffee trade, ensuring the safety and traceability of coffee has become a critical challenge, prompting global authorities to implement new traceability systems to enhance quality identification and protect consumers from fraud. Aroma is a crucial parameter in the evaluation and differentiation of coffees, influenced by factors such as genetics, origin, post harvesting process, roast level, and brewing method. This paper provides, for the first time, a comprehensive overview of the volatile fingerprints of specialty coffees, categorized by their respective quality levels. In particular, this study aimed to evaluate the potential of volatile compounds monitored through Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS) as objective, fast, reliable and repeatable tool for tracking the quality and genetic lineage of Arabica specialty coffees. The spectra of volatile organic compounds (VOCs) were acquired from 1132 coffee samples (both specialty and non-specialty) from various varieties, origins, and processing methods. Results clearly indicate that the volatile composition of specialty coffee is predominantly influenced by its genetic lineage. Arabica coffee species belonging to Bourbon, Typica, and Ethiopian landraces showed higher total VOCs emission, while varieties related to Robusta, which are related to the Canephora one, emit less. Finally, by employing a complex network analysis approach based on headspace VOC analysis, it was possible to accurately distinguish between different categories of specialty Arabica coffee. Notably, our analysis shows that the quality of specialty coffee is not linked to the number of VOCs emitted, but rather to the level emission of some pleasant aroma compounds. These findings open new perspectives for the development of aroma profiling techniques and demonstrate the unique aroma release characteristics of specialty coffees.

Indexed as

CoffeaCoffeeVolatile Organic CompoundsMass SpectrometryOdorantsCoffeeVolatile Organic CompoundsCoffee qualityCoffee specialtyCoffee traceabilityComplex network analysisVolatile organic compounds

Identifiers

PMID40258936
PMCPMC12012085

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.