期刊名称：IOP Conference Series: Earth and Environmental Science
印刷版ISSN：1755-1307
电子版ISSN：1755-1315
出版年度：2020
卷号：537
期号：1
DOI：10.1088/1755-1315/537/1/012035
语种：English
出版社：IOP Publishing
摘要：Coffee is one of the important agricultural products in Indonesia. In this present work, we evaluate the potential application of UV-visible spectroscopy and principal component analysis (PCA) to discriminate Lampung robusta coffee with different fermentation. Total of 300 samples was used with three fermentation conditions: 100 samples belong to F0 or ORI (no fermentation), 100 samples belong to F2 (fermented 2 days using special microbial fermentation), and 100 samples belong to F4 (fermented 4 days using special microbial fermentation). A hot distilled water was used to extract the coffee samples. The extraction procedure including dilution was performed based on several previous reported studies. The spectral data acquisition was done by using a UV-visible spectrometer in the range of 190-1100 nm (full-spectrum) with 1 nm of interval. The result showed that using an unsupervised classification of principal component analysis (PCA) using modified spectral data of standard normal variate (SNV) and moving average, the samples can be well clustered into three different groups of fermentation. Our results highlight the potential of UV-visible spectroscopy combined with chemometrics as a green and relatively fast analytical method to discriminate Lampung robusta coffee based on fermentation.
