TY - JOUR
T1 - Quantification of coffee blends for authentication of Asian palm civet coffee (Kopi Luwak) via metabolomics
T2 - A proof of concept
AU - Jumhawan, Udi
AU - Putri, Sastia Prama
AU - Yusianto,
AU - Bamba, Takeshi
AU - Fukusaki, Eiichiro
PY - 2016/7/1
Y1 - 2016/7/1
N2 - Asian palm civet coffee (Kopi Luwak), an animal-digested coffee with an exotic feature, carries a notorious reputation of being the rarest and most expensive coffee beverage in the world. Considering that illegal mixture of cheap coffee into civet coffee is a growing concern among consumers, we evaluated the use of metabolomics approach and orthogonal projection to latent structures (OPLS) prediction technique to quantify the degree of coffee adulteration. Two prediction sets, consisting of certified and commercial coffee, were made from a blend of civet and regular coffee with eleven mixing percentages. The prediction model exhibited accurate estimation of coffee blend percentage thus, successfully validating the prediction and quantification of the mixing composition of known-unknown samples. This work highlighted proof of concept of metabolomics application to predict degree of coffee adulteration by determining the civet coffee fraction in blends.
AB - Asian palm civet coffee (Kopi Luwak), an animal-digested coffee with an exotic feature, carries a notorious reputation of being the rarest and most expensive coffee beverage in the world. Considering that illegal mixture of cheap coffee into civet coffee is a growing concern among consumers, we evaluated the use of metabolomics approach and orthogonal projection to latent structures (OPLS) prediction technique to quantify the degree of coffee adulteration. Two prediction sets, consisting of certified and commercial coffee, were made from a blend of civet and regular coffee with eleven mixing percentages. The prediction model exhibited accurate estimation of coffee blend percentage thus, successfully validating the prediction and quantification of the mixing composition of known-unknown samples. This work highlighted proof of concept of metabolomics application to predict degree of coffee adulteration by determining the civet coffee fraction in blends.
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U2 - 10.1016/j.jbiosc.2015.12.008
DO - 10.1016/j.jbiosc.2015.12.008
M3 - Article
C2 - 26777237
AN - SCOPUS:84952933969
SN - 1389-1723
VL - 122
SP - 79
EP - 84
JO - Journal of Bioscience and Bioengineering
JF - Journal of Bioscience and Bioengineering
IS - 1
ER -