Identification of adulteration in ground roasted coffees using UV–Vis spectroscopy and SPA-LDA

Souto, Urijatan Teixeira de Carvalho Polari; Barbosa, Mayara F.; Dantas, Hebertty Vieira; Pontes, Aline Santos de; Lyra, Wellington da Silva; Diniz, Paulo Henrique Gonçalves Dias; Araújo, Mário César Ugulino de; Silva, Edvan Cirino da

doi:10.1016/j.lwt.2015.04.003

Cited by 73 publications

(28 citation statements)

References 27 publications

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“…The several observed important wavelengths in this study are closely related to the absorbance of several important chemical compositions in roasting coffee. For example, the wavelength at 276 nm can be found both in x -loading and in regression coefficient plot and this wavelength is related to the absorbance of caffeine while wavelength at 320 nm is related to absorbance of caffeic acid [6]. The wavelengths at 246, 299, and 320 nm are closely related to the absorbance of chlorogenic acids (CGA) [31].…”

Section: Resultsmentioning

confidence: 99%

“…An aqueous extraction procedure of the coffee samples was performed as described by Souto et al [6] and Yulia and Suhandy [8]. First, 1.0 g of each sample was weighed and placed in a glass beaker.…”

Section: Methodsmentioning

confidence: 99%

“…In the previous study, Souto et al [6] reported the use of UV-Visible spectroscopy as a simple analytical method for the identification of adulterations in ground roasted coffees (due to the presence of husks and sticks). This UV-Vis based analytical method is one of the most common and inexpensive techniques used in routine analysis and it will be compatible with situation in Indonesia for further technology development.…”

Section: Introductionmentioning

confidence: 99%

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The Use of Partial Least Square Regression and Spectral Data in UV-Visible Region for Quantification of Adulteration in Indonesian Palm Civet Coffee

Suhandy

Yulia

2017

International Journal of Food Science

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Asian palm civet coffee or kopi luwak (Indonesian words for coffee and palm civet) is well known as the world's priciest and rarest coffee. To protect the authenticity of luwak coffee and protect consumer from luwak coffee adulteration, it is very important to develop a robust and simple method for determining the adulteration of luwak coffee. In this research, the use of UV-Visible spectra combined with PLSR was evaluated to establish rapid and simple methods for quantification of adulteration in luwak-arabica coffee blend. Several preprocessing methods were tested and the results show that most of the preprocessing spectra were effective in improving the quality of calibration models with the best PLS calibration model selected for Savitzky-Golay smoothing spectra which had the lowest RMSECV (0.039) and highest RPDcal value (4.64). Using this PLS model, a prediction for quantification of luwak content was calculated and resulted in satisfactory prediction performance with high both RPDp and RER values.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Use of Partial Least Square Regression and Spectral Data in UV-Visible Region for Quantification of Adulteration in Indonesian Palm Civet Coffee

Suhandy

Yulia

2017

International Journal of Food Science

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“…This spectral range is associated with n * electronic transition of caffeine, chlorogenic acids, and trigonelline molecules. 16 In next step, we used spectral data in the range of 250-450 nm for principal components analysis (PCA) and PLS-DA analysis.…”

Section: Development Of Pls-da Modelmentioning

confidence: 99%

“…The first wavelength is around 275 nm, which corresponds to the C=O chromophore absorbance of caffeine. 16 The second wavelength is 325 nm, and it corresponds to the absorbance of trigonelline and caffeic acid. 16 The third important wavelength is 350 nm, and it is close related to the absorbance of chlorogenic acid (CGA).…”

Section: Unsupervised Classification Using Principal Component Analysismentioning

confidence: 99%

The potential of UV-visible spectroscopy and chemometrics for determination of geographic origin of three specialty coffees in Indonesia

Suhandy

Yulia²

2018

AIP Conference Proceedings

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The growing global trading market for specialty coffee increases the need for better coffee quality evaluation methods. Several Arabica coffees in Indonesia have high commercial value. For this reason, the development of analytical methods with high sensitivity and accuracy for detection of its adulteration was important. This research evaluated the potential of UV-visible spectroscopy and partial least squares discriminant analysis (PLS-DA) for determining the geographic origin of three specialty coffees (Gayo, Kintamani and Wamena) in Indonesia. In this research, 296 coffee samples from three different origins (Gayo, Kintamani and Wamena) were used. All coffee samples were ground using a home-coffee-grinder. We sieved all coffee samples through a nest of US standard sieves (mesh number of 40) on a Meinzer II sieve shaker for 10 minutes to obtain a particle size of 420 μm. All samples were extracted with distilled water and then filtered. For each sample, 3 mL of extracted sample then was pipetted into 10 mm cuvettes for spectral data acquisition. The spectral data were acquired using a Genesys 10s UV-visible spectrometer in the range of 190-1100 nm. A PLS-DA classification model was estimated to classify the origin of specialty coffees by their UVvisible spectra. The best PLS-DA model accurately classified the specialty coffee samples of the prediction sample set with prediction ability of 100% of correct classification for Gayo, Kintamani and Wamena, respectively. The results demonstrate that UV-visible spectroscopy coupled with PLS-DA provides a sensitive and accurate analytical method to distinguish ground roasted coffee samples geographically.

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Data fusion of fluorescence and UV spectroscopies improves the detection of cocoa butter adulteration

Dankowska

2017

Euro J Lipid Sci & Tech

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The fraudulent addition of cheaper plant oils to cocoa butter is a real issue for the chocolate industry. The potential of fluorescence and UV and data fusion of these spectroscopies for the detection of cocoa butter adulteration with cocoa butter equivalents (CBEs) is investigated here. Principal component regression (PCR) models have been used to calculate the level of adulteration. A classification model has been built with the help of the principal component analysis (PCA) and the linear discriminant analysis (LDA). The LDA analysis has been applied to fluorescence intensities and UV spectra of cocoa butter, cocoa butter equivalents, and their mixtures in order to examine classification ability. The best prediction ability of adulteration was obtained for PCR data fusion models with the lowest errors of calibration (RMSEC) and validation (RMSEV) of 3.7 and 4.7%. The best performance of the PCA‐LDA analysis has been observed for data fusion of fluorescence and UV intensities measurements at wavelength intervals of 10 and 30 nm. The LDA shows that data fusion can achieve 95.2% correct classifications (sensitivity) in the validation data set, while the corresponding results for individual spectroscopies range from 66.7–90.5%. The results demonstrate that fluorescence and UV spectroscopies complement each other, giving a synergistic effect for the detection of cocoa butter adulteration with cocoa butter equivalents. Practical applications: The aim of this research is to develop a quick and cheap method of discriminating between cocoa butter and cocoa butter equivalents. The obtained results are satisfactory for classification of genuine cocoa butter and cocoa butter equivalents and for detection of cocoa butter adulterations with cheaper cocoa butter equivalents. The method is an important technical support of public health against profit‐driven practices. Application of fluorescence and UV spectroscopies to the detection of cocoa butter adulteration with cocoa butter equivalent and the synergy between both spectroscopies are investigated. The best prediction ability of MLR models i obtained for the data fusion model with the errors of calibration and validation of 3.7 and 4.7%. Compared to individual spectroscopies, data fusion shows better discrimination ability of PCA‐LDA model with the highest classification accuracy equal 100.0 and 95.2% in the calibration and validation data sets. The results show that fluorescence and UV spectroscopies give a synergistic effect for the detection of cocoa butter adulteration.

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Identification of adulteration in ground roasted coffees using UV–Vis spectroscopy and SPA-LDA

Cited by 73 publications

References 27 publications

The Use of Partial Least Square Regression and Spectral Data in UV-Visible Region for Quantification of Adulteration in Indonesian Palm Civet Coffee

The Use of Partial Least Square Regression and Spectral Data in UV-Visible Region for Quantification of Adulteration in Indonesian Palm Civet Coffee

The potential of UV-visible spectroscopy and chemometrics for determination of geographic origin of three specialty coffees in Indonesia

Data fusion of fluorescence and UV spectroscopies improves the detection of cocoa butter adulteration

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