The Use of Partial Least Square Regression and Spectral Data in UV-Visible Region for Quantification of Adulteration in Indonesian Palm Civet Coffee
Joint Authors
Suhandy, Diding
Yulia, Meinilwita
Source
International Journal of Food Science
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-08-20
Country of Publication
Egypt
No. of Pages
7
Abstract EN
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.
American Psychological Association (APA)
Suhandy, Diding& Yulia, Meinilwita. 2017. The Use of Partial Least Square Regression and Spectral Data in UV-Visible Region for Quantification of Adulteration in Indonesian Palm Civet Coffee. International Journal of Food Science،Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1166925
Modern Language Association (MLA)
Suhandy, Diding& Yulia, Meinilwita. The Use of Partial Least Square Regression and Spectral Data in UV-Visible Region for Quantification of Adulteration in Indonesian Palm Civet Coffee. International Journal of Food Science No. 2017 (2017), pp.1-7.
https://search.emarefa.net/detail/BIM-1166925
American Medical Association (AMA)
Suhandy, Diding& Yulia, Meinilwita. The Use of Partial Least Square Regression and Spectral Data in UV-Visible Region for Quantification of Adulteration in Indonesian Palm Civet Coffee. International Journal of Food Science. 2017. Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1166925
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1166925