Suhandy, Diding and Yulia, Meinilwita (2020) Unsupervised classification of three specialty coffees from Java based on principal component analysis and UV-visible spectroscopy. In: International Conference on Science, Infrastructure Technology and Regional Development 2019 25-26 October 2019, South Lampung, Indonesia, 25-26 October 2019, South Lampung, Indonesia.

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Abstract

In this research, we investigated the feasibility of using UV-visible spectroscopy and chemometrics to classify three specialty coffees from Java Island: Java Preanger, Java Sindoro-Sumbing dan Java Ijen Raung. Total of 300 samples of Preanger, Sindoro-Sumbing and Ijen Raung ground roasted coffees were used as samples. Samples were extracted using hot distilled water and diluted. The spectral data was acquired using a UV-visible spectrometer in the range of 190-1100 nm. Unsupervised classification based on principal component analysis (PCA) was applied for original and modified spectral data. Using the original full spectrum of 190-1100 nm spectral data, the plot score of the first and second principal components (PC1xPC2) totally can explain 90% of data variance. It was difficult to separate the origin of Preanger, Sindoro-Sumbing and Ijen Raung using original full spectrum data. However, using modified spectral data in the range of 250-450 nm, the clear separation between Preanger, Sindoro-Sumbing and Ijen Raung was demonstrated. In conclusion, it was highly potential to use UV-visible spectroscopy and chemometrics to classify the specialty coffees from Java based on its origin.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	S Agriculture > S Agriculture (General)
Divisions:	Fakultas Pertanian (FP) > Prodi Teknik Pertanian
Depositing User:	Dr. Diding Suhandy
Date Deposited:	10 Nov 2020 08:32
Last Modified:	10 Nov 2020 08:32
URI:	http://repository.lppm.unila.ac.id/id/eprint/24840

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