Suhandy, Diding and Yulia, Meinilwita (2020) Unsupervised classification of three specialty coffees from Java based on principal component analysis and UV-visible spectroscopy. IOP Publishing, IOP Conf. Series: Earth and Environmental Science.

[img]
Preview
Text
Unsupervised_classification_of_three_specialty_cof.pdf

Download (1MB) | Preview
Official URL: https://iopscience.iop.org/article/10.1088/1755-13...

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 SindoroSumbing 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, SindoroSumbing 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: Other
Subjects: S Agriculture > S Agriculture (General)
Divisions: Fakultas Pertanian (FP) > Prodi Teknik Pertanian
Depositing User: Dr. Diding Suhandy
Date Deposited: 10 May 2021 01:24
Last Modified: 10 May 2021 01:24
URI: http://repository.lppm.unila.ac.id/id/eprint/30080

Actions (login required)

View Item View Item