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

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...

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Bibliographic Details
Published in:International journal of food science 2017, Vol.2017 (2017), p.1-7
Main Authors: Suhandy, Diding, Yulia, Meinilwita
Format: Article
Language:English
Subjects:
Authenticity
Calibration
Coffee
Coffee industry
Data analysis
Engineering
Food science
Fourier transforms
Manures
Methods
Particle size
Preprocessing
Soil sciences
Spectra
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Summary: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.
ISSN:2356-7015
2314-5765
2314-5765
DOI:10.1155/2017/6274178