Fraud investigation in commercial coffee by chromatography

Martins, Víctor de Carvalho; Godóy, Ronoel Luiz de Oliveira; Gouvêa, Ana Cristina Miranda Senna; Santiago, Manuela Cristina Pessanha de Araújo; Borguini, Renata Galhardo; Braga, Elaine Cristina de Oliveira; Pacheco, Sidney; Nascimento, Luzimar da Silva de Mattos do

doi:10.1093/fqsafe/fyy017

Cited by 27 publications

(12 citation statements)

References 54 publications

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“…It is noteworthy that the present study allows the estimation of a wide range of contamination levels of coffee, from the absence of impurity to extreme values (70% of impurities). In the Brazilian domestic market, for example, coffees with up to 40% impurities are commercialized (Martins et al, 2018).…”

Section: Table 2 Pearson's Correlation Coefficients Between Descripto...mentioning

confidence: 99%

Estimation of percentage of impurities in coffee using a computer vision system

Costa

Silva

Barros

et al. 2022

Rev. bras. eng. agríc. ambient.

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The quality and price of coffee drinks can be affected by contamination with impurities during roasting and grinding. Methods that enable quality control of marketed products are important to meet the standards required by consumers and the industry. The purpose of this study was to estimate the percentage of impurities contained in coffee using textural and colorimetric descriptors obtained from digital images. Arabica coffee beans (Coffea arabica L.) at 100% purity were subjected to roasting and grinding processes, and the initially pure ground coffee was gradually contaminated with impurities. Digital images were collected from coffee samples with 0, 10, 30, 50, and 70% impurities. From the images, textural descriptors of the histograms (mean, standard deviation, entropy, uniformity, and third moment) and colorimetric descriptors (RGB color space and HSI color space) were obtained. The principal component regression (PCR) method was applied to the data group of textural and colorimetric descriptors for the development of linear models to estimate coffee impurities. The selected models for the textural descriptors data group and the colorimetric descriptors data group were composed of two and three principal components, respectively. The model from the colorimetric descriptors showed a greater capacity to estimate the percentage of impurities in coffee when compared to the model from the textural descriptors.

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Section: Table 2 Pearson's Correlation Coefficients Between Descripto...mentioning

confidence: 99%

Estimation of percentage of impurities in coffee using a computer vision system

Costa

Silva

Barros

et al. 2022

Rev. bras. eng. agríc. ambient.

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“…Originality and quality have become the most important aspects for the coffee industry where various factors can affect the final product (Martins et al, 2018;Oliveira et al, 2015). An important aspect with a negative impact on the coffee industry is the presence of fraud approaches, presented by offering coffee/coffee products with the addition of low-cost materials and the presence of defective beans or even low-quality coffees or beans from different geographical regions in comparison to "facts" stated on the product label.…”

Section: Originality and Declared Qualitymentioning

confidence: 99%

Sights to Authentication and Adulteration of the Coffee in Global Aspect

Čurlej¹,

Bobková²,

Zajác³

et al. 2021

J microb biotech food sci

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Coffee presents a valuable food product for several reasons, covering areas like a source of health benefits substances for the human body, brain energizing/stimulating product and its social aspect raising from coffee consumption. This study aims to summarise the most common practices used in coffee adulteration and the methods focused to confirm the authenticity of the coffee, the quality, and price determinants according to a place of origin and/or selection between Robusta versus Arabica coffee beans. Nowadays, several scientific approaches are used for this purpose, based on chemical or molecular analysis. Literature and the data presented in this article were collected from studies published in scientific journals. On the other hand, the article introduces how to protect customer\s rights in the global coffee trade.

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“…These markers decreased during roasting process. All the identified compounds grouped in Tables 2 and 3 had been previously described in coffee samples in the literature [25,26,[30][31][32][33].…”

Section: Metabolite Identification Of Coffee Roasting Processmentioning

confidence: 99%

Untargeted HILIC-MS-Based Metabolomics Approach to Evaluate Coffee Roasting Process: Contributing to an Integrated Metabolomics Multiplatform

et al. 2020

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An untargeted metabolomics strategy using hydrophilic interaction chromatography-mass spectrometry (HILIC-MS) was developed in this work enabling the study of the coffee roasting process. Green coffee beans and coffee beans submitted to three different roasting degrees (light, medium, and strong) were analyzed. Chromatographic separation was carried out using water containing 10 mM ammonium formate with 0.2 % formic acid (mobile phase A) and acetonitrile containing 10 mM ammonium formate with 0.2 % formic acid (mobile phase B). A total of 93 molecular features were considered from which 31 were chosen as the most statistically significant using variable in the projection values. 13 metabolites were tentatively identified as potential biomarkers of the coffee roasting process using this metabolomic platform. Results obtained in this work were complementary to those achieved using orthogonal techniques such as reversed-phase liquid chromatography-mass spectrometry (RPLC-MS) and capillary electrophoresis-mass spectrometry (CE-MS) since only one metabolite was found to be common between HILIC-MS and RPLC-MS platforms (caffeoylshikimic acid isomer) and other between HILIC-MS and CE-MS platforms (choline). On the basis of these results, an untargeted metabolomics multiplatform is proposed in this work based on the integration of the three orthogonal techniques as a powerful tool to expand the coverage of the roasted coffee metabolome.

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Fraud investigation in commercial coffee by chromatography

Cited by 27 publications

References 54 publications

Estimation of percentage of impurities in coffee using a computer vision system

Estimation of percentage of impurities in coffee using a computer vision system

Sights to Authentication and Adulteration of the Coffee in Global Aspect

Untargeted HILIC-MS-Based Metabolomics Approach to Evaluate Coffee Roasting Process: Contributing to an Integrated Metabolomics Multiplatform

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