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International Journal of Food Science
Volume 2017, Article ID 6274178, 7 pages
https://doi.org/10.1155/2017/6274178
Research Article

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

1Laboratory of Bioprocess and Postharvest Engineering, Department of Agricultural Engineering, The University of Lampung, Jl. Soemantri Brojonegoro No. 1, Gedong Meneng, Bandar Lampung, Lampung 35145, Indonesia
2Department of Agricultural Technology, Lampung State Polytechnic, Jl. Soekarno Hatta No. 10, Rajabasa, Bandar Lampung, Lampung, Indonesia

Correspondence should be addressed to Diding Suhandy; di.ca.alinu.pf@ydnahgus.gnidid

Received 18 January 2017; Revised 12 June 2017; Accepted 18 July 2017; Published 20 August 2017

Academic Editor: Thierry Thomas-Danguin

Copyright © 2017 Diding Suhandy and Meinilwita Yulia. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Diding Suhandy and Meinilwita Yulia, “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, Article ID 6274178, 7 pages, 2017. https://doi.org/10.1155/2017/6274178.