2015 UDI JUMHAWAN

Title
Gas chromatography-based metabolomics for authenticity evaluation of Asian palm civet coffee (Kopi Luwak)
(ガスクロマトグラフィーに基づいたメタボロミクス技術によるコピ・ルアクの真偽判別法)

Abstract of Thesis
Considering that fraudulent adulterations are now commonly practiced in various consumer sectors, development of quality standards through labeling and composition regulations and routine evaluation protocol is needed. Asian palm civet coffee is a specialty coffee produced by its passage through the digestive part of Asian palm civet (Paradoxurus hermaphroditus). The rarity, exotic processing and unique flavor have contributed to its premium price. However, there is no reliable and standardized protocol to ensure the authenticity of civet coffee. This thesis emphasizes development of a protocol for authenticity evaluation of civet coffee, a world-renowned priciest coffee that has notoriously subjected to fraudulent adulteration and its routine application in industry.
In Chapter 1, general introduction regarding the utility of metabolomics in food science, civet coffee and research background are presented. In Chapter 2, development of standardized protocol through GC/MS-based multimarker profiling of 21 coffee beans (Coffea arabica and Coffea canephora) from different cultivation areas was demonstrated to explore significant changes in the metabolite profiles as discriminant markers for authentication of civet coffee. Employing multivariate analyses, a set of significant metabolites, mainly organic acids, was selected for further verification by evaluating their differentiating abilities against various commercial coffee products. In Chapter 3, first practical application was presented by developing rapid, reliable and cost-effective analysis via GC coupled with universal detector, flame ionization detector (FID), and metabolite fingerprinting for discrimination 37 commercial and non-commercial civet coffee extracts. GC/FID provided higher sensitivity over a similar range of detected compounds than GC/MS and could successfully reproduce quality prediction from GC/MS for differentiation of commercial civet coffee, regular coffee and coffee blend with 50 wt % civet coffee content without prior metabolite details. In order to prevent illegal mixture of cheap coffee into civet coffee, the proof-of-concept of the utility of metabolomics approach and orthogonal projection to latent structures (OPLS) prediction technique to quantify the degree of coffee adulteration was demonstrated in Chapter 4. The prediction model exhibited accurate estimation of mixing ratio of known-unknown coffee samples. At last, general conclusion and future perspective are elaborated.
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