The Potential of UV-Visible Spectroscopy and Chemometrics for Determination of Geographic Origin of Three Specialty Coffees in Indonesia

被引:1
|
作者
Suhandy, Diding [1 ]
Yulia, Meinilwita [2 ]
机构
[1] Univ Lampung, Fac Agr, Dept Agr Engn, Lab Bioproc & Postharvest Engn,SRG, Jalan Prof Dr Soemantri 10, Brojonegoro 35145, Bandar Lampung, Indonesia
[2] Lampung State Polytech, Dept Agr Technol, Jalan Soekarno Hatta 10, Rajabasa 35141, Bandar Lampung, Indonesia
来源
8TH ANNUAL BASIC SCIENCE INTERNATIONAL CONFERENCE: COVERAGE OF BASIC SCIENCES TOWARD THE WORLD'S SUSTAINABILITY CHALLANGES | 2018年 / 2021卷
关键词
Coffee; geographic origin; partial least squares discriminant analysis; UV-visible spectroscopy; FOOD AUTHENTICITY; ADULTERATION; DISCRIMINATION;
D O I
10.1063/1.5062745
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The growing global trading market for specialty coffee increases the need for better coffee quality evaluation methods. Several Arabica coffees in Indonesia have high commercial value. For this reason, the development of analytical methods with high sensitivity and accuracy for detection of its adulteration was important. This research evaluated the potential of UV-visible spectroscopy and partial least squares discriminant analysis (PLS-DA) for determining the geographic origin of three specialty coffees (Gayo, Kintamani and Wamena) in Indonesia. In this research, 296 coffee samples from three different origins (Gayo, Kintamani and Wamena) were used. All coffee samples were ground using a home-coffee-grinder. We sieved all coffee samples through a nest of US standard sieves (mesh number of 40) on a Meinzer II sieve shaker for 10 minutes to obtain a particle size of 420 mu m. All samples were extracted with distilled water and then filtered. For each sample, 3 mL of extracted sample then was pipetted into 10 mm cuvettes for spectral data acquisition. The spectral data were acquired using a Genesys 10s UV-visible spectrometer in the range of 190-1100 nm. A PLS-DA classification model was estimated to classify the origin of specialty coffees by their UVvisible spectra. The best PLS-DA model accurately classified the specialty coffee samples of the prediction sample set with prediction ability of 100% of correct classification for Gayo, Kintamani and Wamena, respectively. The results demonstrate that UV-visible spectroscopy coupled with PLS-DA provides a sensitive and accurate analytical method to distinguish ground roasted coffee samples geographically.
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页数:6
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