Discrimination of civet and non-civet coffee by linear discriminant analysis (LDA), partial least squares (PLS-DA), and orthogonal projection to latent structures (OPLS-DA)
Date of Publication
2015
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Statistics Major in Actuarial Science
Subject Categories
Statistics and Probability
College
College of Science
Department/Unit
Mathematics and Statistics
Thesis Adviser
Rechel G. Arcilla
Abstract/Summary
One of the issues faced by coffee traders and consumers is the widespread availability of adulterated civet coffee (kopi luwak) in the market. To address this problem, the industry needs a way to discriminate between civet and non-civet coffee. Metabolomics data consisting of 24 coffee beans were subjected to linear discriminant analysis (LDA), partial least squares – discriminant analysis (PLS-DA), and orthogonal projection to latent structures – discriminant analysis (OPLS-DA). LDA identified isonicotinic acid, 3-hydroxybenzoic acid, arbutin, and propane-1,3-diol NIST as discriminant markers. On the other hand, PLS-DA described three factors highly represented by: (1) sugars and organic acids (2) aroma acids and (3) taste acids as responsible for successful class separation. Lastly, OPLS-DA showed that isonicotinic acid, 5-aminovaleric acid, beta-glutamic acid, pentitol, and urea were the most significant in discriminating the data. All the fitted models yielded 0 misclassification rates. The LDA model exhibited an R2 of 88.56%, while the OPLS-DA and PLS-DA models demonstrated R2Y of 87.9%. Unlike LDA, PLS-DA is not governed by a set of assumptions. The PLS-DA model was also evaluated with a higher Q2 (62.6%) than that of the OPLS-DA model Q2 (51.5%). Hence, among the three discriminant analyses, PLS-DA is the recommended analysis tool for discriminating between civet and non-civet coffee samples.
Abstract Format
html
Language
English
Format
Electronic
Accession Number
CDTU021097
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Physical Description
1 computer disc ; 4 3/4 in.
Keywords
Coffee--Classification; Discriminant analysis
Recommended Citation
Datinginoo, M. R., & Losañes, C. L. (2015). Discrimination of civet and non-civet coffee by linear discriminant analysis (LDA), partial least squares (PLS-DA), and orthogonal projection to latent structures (OPLS-DA). Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/14901
Embargo Period
5-12-2021