Discrimination of several Indonesian specialty coffees using Fluorescence Spectroscopy combined with SIMCA method

Suhandy, Diding; Yulia, Meinilwita

doi:10.1088/1757-899x/334/1/012059

Cited by 24 publications

(24 citation statements)

References 12 publications

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“…The spectral acquisition was done on aqueous coffee samples. For this, a procedure for coffee sieving and extraction was performed based on previous researches [13][14][15][16][17].…”

Section: Coffee Samplesmentioning

confidence: 99%

Identification of fresh and expired ground roasted robusta coffee using UV-visible spectroscopy and chemometrics

Yulia

Suhandy

2018

MATEC Web Conf.

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The freshness of ground roasted coffee escapes extremely fast. For this reason, the evaluation of conservation state of ground roasted coffee must be taken into account for acceptability of coffee. Unfortunately, it is difficult to discriminate the fresh and expired ground roasted coffee physically by our naked eyes. Thus, it is desired to develop an analytical method to evaluate the fresh and expired ground roasted coffee using reliable methods. The objective of this research was to evaluate the potential of UVvisible spectroscopy and chemometrics method for classification of fresh and expired ground roasted robusta coffee. A number of 200 samples of robusta fresh coffee and 200 samples of robusta expired coffee was used. The spectral data were pre-treated using standard normal variate (SNV), moving average smoothing (window: 9) and Savitzky-Golay 2 nd derivative (order: 2; window: 11). The analysis data was done statistically using multivariate chemometric techniques, including principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA) in the spectral range of 230-400 nm. PCA with PC1 = 94% and PC2 = 4% showed clear clustering of samples (p ⩽ 0.05). UV-visible spectroscopy with SIMCA analysis allowed to classify between fresh and expired ground roasted robusta coffee with a correct classification rate of 100%.

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“…The spectral acquisition was done on aqueous coffee samples. For this, a procedure for coffee sieving and extraction was performed based on previous researches [13][14][15][16][17].…”

Section: Coffee Samplesmentioning

confidence: 99%

Identification of fresh and expired ground roasted robusta coffee using UV-visible spectroscopy and chemometrics

Yulia

Suhandy

2018

MATEC Web Conf.

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“…In previous studies, UV-visible spectroscopy has been used to discriminate ground roasted pure peaberry coffee and pure normal coffee [4], to discriminate ground roasted civet and non-civet coffee [5], and to quantify the degree of adulteration in ground roasted civet coffee [6]. Discrimination of several Indonesian specialty coffees has been investigated using Fluorescence spectroscopy [7] and NIR spectroscopy [8]. However, to the best of our knowledge, there is no any report on the use of UV-visible spectroscopy for discrimination ground roasted Gayo Wine and Gayo normal coffee.…”

Section: Introductionmentioning

confidence: 99%

The classification of arabica gayo wine coffee using UV-visible spectroscopy and PCA-DA method

Suhandy¹,

Yulia

2018

MATEC Web Conf.

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The unique processing of Arabica Gayo Wine coffee produces special attributes to the beverage and could increase its value. However, it is important to prove the authenticity of Arabica Gayo Wine coffee using reliable methods. The objective of this study was to evaluate the potential of UV-visible spectroscopy and principal component analysis-discriminant analysis (PCA-DA) method for classification of ground roasted Arabica Gayo Wine coffee. A number of 200 samples of Arabica Gayo Wine coffee and 200 samples of Arabica Gayo normal (not Wine) coffee was used. The spectral data obtained in the UV-visible region were analyzed using PCA-DA with standard normal variate (SNV) and followed by Savitzky-Golay smoothing with different number of smoothing point (NSP). The results showed that the best PCA-DA model was obtained with NSP = 23 with coefficient of determination for calibration (R 2 ) = 0.99, root mean square error of calibration (RMSEC) = 0.005692 and root mean square error of validation (RMSEV) = 0.006112. Using this model, a good classification between Gayo Wine and Gayo normal in prediction step was achieved with 100% accuracy, sensitivity and specificity. Thus, the proposed method can be used for the evaluation of authenticity of ground roasted Arabica Gayo Wine coffee.

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“…Some studies applied spectroscopy, that deals with the analysis of how light acts towards a given object [9], in discrimination of civet coffee. Suhandy and Yulia [10] used chosen fluorescence spectra and the SIMCA method to differentiate the two coffee varieties in terms of specificity and sensitivity values. On the other hand, another study utilized UV-Visible spectroscopy combined with various chemometrics methods [11] in which produced a 100 % satisfaction in civet coffee classification.…”

Section: Introductionmentioning

confidence: 99%

“…Specialty coffee is restricted in supply because of special flavor and high price relative to regular coffee. The spectroscopic approach used for coffee authentication is most often paired with the strength of methods involving pattern recognition [10]. Most used in various plant studies for its two-dimensional aspect [13].…”

Section: Introductionmentioning

confidence: 99%

Discrimination of civet coffee using visible spectroscopy

Adier

Reyes

Arboleda

2020

Jurnal Teknologi dan Sistem Komputer

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Civet coffee is considered as highly marketable and rare. This specialty coffee has a special flavor and higher price relative to regular coffee, and it is restricted in supply. Establishing a straightforward and efficient approach to distinguish Civet coffee for quality; likewise, consumer protection is fundamental. This study utilized visible spectroscopy as a non-destructive and quick technique to obtain the absorbance, ranging from 450 nm to 650 nm, of the civet coffee and non-civet coffee samples. Overall, 160 samples were analyzed, and the total spectra accumulated was 960. The data gathered from the first 120 samples were fed to the classification learner application and were used as a training data set. The remaining samples were used for testing the classification algorithm. The study shows that civet coffee bean samples have lower absorbance values in visible spectra than non-civet coffee bean samples. The process yields 96.7 % to 100 % classification scores for quadratic discriminant analysis and logistic regression. Among the two classification algorithms, logistic regression generated the fastest training time of 14.050 seconds. The application of visible spectroscopy combined with data mining algorithms is effective in discriminating civet coffee from non-civet coffee.

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Discrimination of several Indonesian specialty coffees using Fluorescence Spectroscopy combined with SIMCA method

Cited by 24 publications

References 12 publications

Identification of fresh and expired ground roasted robusta coffee using UV-visible spectroscopy and chemometrics

Identification of fresh and expired ground roasted robusta coffee using UV-visible spectroscopy and chemometrics

The classification of arabica gayo wine coffee using UV-visible spectroscopy and PCA-DA method

Discrimination of civet coffee using visible spectroscopy

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