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IJSTR >> Volume 8 - Issue 10, October 2019 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Applying LIBS-QCL Spectrum Coupled With Principal Component Analysis To Distinguish Gayo Arabica And Robusta Coffee

[Full Text]



Rina Harvina Suci, Zulfahrizal, Agus Arip Munawar



Non Destructive, Laser, Coffee, PCA, classification.



Laser Induced Breakdown Spectroscopy-Quantum Cascade Laser (LIBS-QCL) spectra acquisition for inorganic materials has been widely applied in various studies, but for the organic materials especially coffee has not been carried out. The objectives of this present study is to determine a spectral acquisition technique of LIBS-QCL for distinguishing Gyo Arabica and Gayo Robusta in the form of green beans, roasted beans, and coffee powder. Spectral data of coffee samples were acquired in wavelength range from 1000 to 2500 nm with co-added of 32 scans. Spectral data were enhanced by means of standard normal variation (SNV) and peak normalization (PN) algorithms. On the other hand, Principal Component Analysis (PCA) was applied in combination with LIBS spectrum as a method of data analysis and classification. The result showed that LIBS-QCL spectrum acquisition is quite good in the form of green beans. LIBS-QCL is able to distinguish the types of Arabica and Robusta coffee in the form of green beans and roasted beans, but coffee powder has not been able to be distinguished. The study also found several wavelength range intervals associated with coffee quality so that it can be used for further studies to develop coffee quality attributes prediction models.



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