Traceability of Philippine coffee quality competition green coffee beans by multi-elemental analysis using portable x-ray fluorescence analyzer
As the Philippines’ climatic and geographical profiles favors the cultivation of coffee, there is an increase in different fraudulence activities that concerns the geographical origin of the coffee beans. To be able to establish and maintain the authenticity of Philippine Coffee, multi-elemental ana...
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| Main Authors: | , |
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| Format: | text |
| Language: | English |
| Published: |
Animo Repository
2022
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| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/etdb_chem/15 https://animorepository.dlsu.edu.ph/context/etdb_chem/article/1017/viewcontent/2022_Alora_Francisco_Traceability_of_Philippine_Coffee_Full_text.pdf |
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| Institution: | De La Salle University |
| Language: | English |
| Summary: | As the Philippines’ climatic and geographical profiles favors the cultivation of coffee, there is an increase in different fraudulence activities that concerns the geographical origin of the coffee beans. To be able to establish and maintain the authenticity of Philippine Coffee, multi-elemental analysis utilizing portable X-ray Fluorescence (pXRF) Analyzer was used as an analytical technique in treating 56 green coffee samples from the Philippine Quality Coffee Competition (PCQC) wherein 19 of the green coffee samples are Robusta variety and the remaining 37 of the samples are Arabica variety. The included regions in the PCQC samples are Region 1, Region 2, Region 6, Region 9, Region 10, Region 11, Region 12, Region 13, and Cordillera Administrative Region (CAR). The samples were oven dried, pulverized, and then pelletized before analyzing using the Bruker S1 Titan pXRF. In the analysis of PCQC green coffee beans, 26 elements were detected namely Al, Cr, Mn, P, Pd, K, Zn, S, Cu, Rb, Mg, Sr, Cl, Au, Ba, Bi, Ce, Hg, Th, Tl, and U. The samples from the pXRF analyses were treated using R and RStudio wherein Random Forest is generated to be able to classify the obtained data with respect to their varietal and regional classification. Based on the models that are generated by the software, the accuracy for the model of varietal classification is 98.81% while the model for the region classification gained 83.93% accuracy. Thus, it is evident that the multi-elemental analysis can be used as a classification tool in identifying and authenticating the geographical location of green coffee beans in the Philippines. |
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