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  • 标题:Unsupervised classification of three specialty coffees from Java based on principal component analysis and UV-visible spectroscopy
  • 本地全文:下载
  • 作者:D Suhandy ; M Yulia
  • 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:10.1088/1755-1315/537/1/012034
  • 语种:English
  • 出版社:IOP Publishing
  • 摘要: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.
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