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Author Diding, Suhandy ♦ Meinilwita, Yulia
Source Directory of Open Access Journals (DOAJ)
Content type Text
Publisher EDP Sciences
File Format PDF
Date Created 2018-09-17
Copyright Year ©2018
Language English ♦ French
Subject Domain (in LCC) TA1-2040
Subject Keyword Engineering (General) ♦ Technology ♦ Civil engineering (General)
Abstract 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 (R2) = 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.
ISSN 2261236X
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2018-01-01
e-ISSN 2261236X
Journal MATEC Web of Conferences
Volume Number 197
Starting Page 09002


Source: Directory of Open Access Journals (DOAJ)