Evidence map›Paper›PMID 41622773›Full record

ArticleJournal of the science of food and agriculture2026

Exploring portable NIR spectroscopy in transmittance and reflectance modes for the authentication of Brazilian coffees with geographical indications.

Leticia Tessaro, Yhan da Silva Mutz, Mikaela Martins de Bem, Natália de Oliveira Souza, Cleiton Antônio Nunes

Abstract readEvaluation Study
In one paragraph

Article in Journal of the science of food and agriculture, 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. Review
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.

Leticia TessaroDepartment of Chemistry, Federal University of Lavras, Lavras, Brazil.ORCID https://orcid.org/0000-0002-5943-3535
Yhan da Silva MutzDepartment of Food Science, Federal University of Lavras, Lavras, Brazil.ORCID https://orcid.org/0000-0003-1256-8878
Mikaela Martins de BemDepartment of Chemistry, Federal University of Lavras, Lavras, Brazil.
Natália de Oliveira SouzaDepartment of Food Science, Federal University of Lavras, Lavras, Brazil.
Cleiton Antônio NunesDepartment of Food Science, Federal University of Lavras, Lavras, Brazil.

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico 130939/2024-2Conselho Nacional de Desenvolvimento Científico e Tecnológico 173330/2023-1Conselho Nacional de Desenvolvimento Científico e Tecnológico 305628/2022-4Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) [grants #173330/2023-1, #305628/2022-4, #130939/2024-2], Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) [grant #88887.821443/2023-00], and Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) [grants #2023/00474-4, #2021/06968-3].Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 88887.821443/2023-00Fundação de Amparo à Pesquisa do Estado de São Paulo 2021/06968-3Fundação de Amparo à Pesquisa do Estado de São Paulo 2023/00474-4
6 · The paper itself

Abstract

backgroundGeographical indications (GIs) certify the link between coffee origin and quality, enabling premium pricing and protecting producers. However, the high market value of GI coffees increases their vulnerability to fraud, underscoring the need for reliable and practical authentication methods. Portable near-infrared (NIR) spectroscopy represents a rapid and non-destructive alternative, but its capability to discriminate Brazilian GI coffees requires systematic assessment.

resultsThis study compared NIR transmittance spectra of aqueous coffee extracts with NIR reflectance spectra of the corresponding ground samples for the authentication of four Brazilian GIs from southeastern Brazil: Cerrado Mineiro, Mogiana Paulista, Mantiqueira de Minas, and Matas de Minas. Distinct spectral signatures were observed in the 900-1650 nm range. Data-driven soft independent modeling of class analogy (DD-SIMCA) was employed, resulting in excellent classification performance. Although both acquisition modes showed satisfactory performance during calibration and validation, reflectance consistently outperformed transmittance in the prediction of a test set, achieving accuracies ranging from 97% to 100%. The superior performance of reflectance-based models was attributed to the preservation of chemically informative features in the solid coffee matrix, including lipids and other compounds poorly extracted into water, whereas aqueous extracts were dominated by water absorption and exhibited greater intraclass variability.

conclusionPortable NIR spectroscopy, particularly in reflectance mode combined with DD-SIMCA, provides a fast, non-destructive, and highly reliable approach for authenticating Brazilian GI coffees. These findings highlight its potential as a practical tool to protect producers and consumers against fraud and to ensure the integrity of products bearing protected geographical indications. © 2026 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Indexed as

CoffeaCoffeeBrazilFood ContaminationSeedsSpectroscopy, Near-InfraredCoffeeauthenticationchemometricscoffee traceabilityDD‐SIMCAspectral fingerprints

Identifiers

PMID41622773
PMCPMC13067089

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LicenceCC BY
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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.