Evidence map›Paper›PMID 35056707›Full record

ArticleMolecules (Basel, Switzerland)2022

NIRS and Aquaphotomics Trace Robusta-to-Arabica Ratio in Liquid Coffee Blends.

Balkis Aouadi, Flora Vitalis, Zsanett Bodor, John-Lewis Zinia Zaukuu, Istvan Kertesz, Zoltan Kovacs

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Thermal Contaminants in Coffee Induced by Roasting: A Review.International journal of environmental research and public health · 2023
    Review
  2. 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

6 authors.

Balkis AouadiDepartment of Measurements and Process Control, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences, 14-16. Somlói Street, H-1118 Budapest, Hungary.ORCID 0000-0003-3997-397X
Flora VitalisDepartment of Measurements and Process Control, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences, 14-16. Somlói Street, H-1118 Budapest, Hungary.ORCID 0000-0002-4198-2202
Zsanett BodorDepartment of Measurements and Process Control, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences, 14-16. Somlói Street, H-1118 Budapest, Hungary.ORCID 0000-0002-1577-2973
John-Lewis Zinia ZaukuuDepartment of Food Science and Technology, Kwame Nkrumah University of Science and Technology (KNUST), Kumasi 00233, Ghana.ORCID 0000-0002-2058-4416
Istvan KerteszDepartment of Measurements and Process Control, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences, 14-16. Somlói Street, H-1118 Budapest, Hungary.ORCID 0000-0001-8336-865X
Zoltan KovacsDepartment of Measurements and Process Control, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences, 14-16. Somlói Street, H-1118 Budapest, Hungary.ORCID 0000-0003-0641-8830

Funding

European Union and co-financed by the European Regional Development Fund and the Hungarian Government GINOP-2.2.1-18-2020-00025European Union and co-financed by the European Social Fund EFOP-3.6.3-VEKOP-16-2017-00005Thematic Excellence Program awarded by the Ministry for Innovation and Technology NKFIH-831-10/2019
6 · The paper itself

Abstract

Coffee is both a vastly consumed beverage and a chemically complex matrix. For a long time, an arduous chemical analysis was necessary to resolve coffee authentication issues. Despite their demonstrated efficacy, such techniques tend to rely on reference methods or resort to elaborate extraction steps. Near infrared spectroscopy (NIRS) and the aquaphotomics approach, on the other hand, reportedly offer a rapid, reliable, and holistic compositional overview of varying analytes but with little focus on low concentration mixtures of Robusta-to-Arabica coffee. Our study aimed for a comparative assessment of ground coffee adulteration using NIRS and liquid coffee adulteration using the aquaphotomics approach. The aim was to demonstrate the potential of monitoring ground and liquid coffee quality as they are commercially the most available coffee forms. Chemometrics spectra analysis proved capable of distinguishing between the studied samples and efficiently estimating the added Robusta concentrations. An accuracy of 100% was obtained for the varietal discrimination of pure Arabica and Robusta, both in ground and liquid form. Robusta-to-Arabica ratio was predicted with R

Indexed as

CoffeaCoffeeSpectroscopy, Near-InfraredCoffeeaquagramsauthenticationchemometricscoffeeNIRSPCAPCA-LDAPLSR

Identifiers

PMID35056707
PMCPMC8780874

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Registered trials

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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.