Regional and barangay traceability of Philippine green coffee beans through multi-elemental analysis using portable x-ray fluorescence and energy dispersive x-ray fluorescence
Along with the rise of cafe culture, the popularity of coffee has been increasing over the years. However, one consequence of such popularity is the increased occurrence of food fraud or the purposeful manipulation of food products. The study aimed to determine a method that is both accurate and eff...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | text |
| Language: | English |
| Published: |
Animo Repository
2024
|
| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/etdb_chem/49 https://animorepository.dlsu.edu.ph/context/etdb_chem/article/1057/viewcontent/2024_Menguito_Timoteo_Regional_and_Barangay_Traceability_of_Philippine_Green_Coffee_Bea.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | De La Salle University |
| Language: | English |
| Summary: | Along with the rise of cafe culture, the popularity of coffee has been increasing over the years. However, one consequence of such popularity is the increased occurrence of food fraud or the purposeful manipulation of food products. The study aimed to determine a method that is both accurate and efficient for tracing the regional and barangay origin of Philippine arabica green coffee beans using multi-elemental analysis by portable X-ray fluorescence (pXRF) and energy-dispersive X-ray fluorescence (ED-XRF). The data collected was analyzed using one-way ANOVA, Tukey’s HSD, and Random Forest models. The study analyzed 29 samples of C. arabica green coffee beans sourced from five different regions across the Philippines: Region II, Region X, Region XI, CAR, and BARMM. The study successfully developed models using both ED-XRF and pXRF data, achieving accurate classification of samples into their respective regions. It was found that manganese and potassium were significant elements for regional classification, while manganese alone was the most significant factor for barangay classification The constructed Random Forest models had 100% accuracy for both regional and barangay classifications. The study was also able to demonstrate the potential of multi-elemental analysis, which when accompanied with machine learning is a valuable tool for the traceability and authentication of Philippine arabica green coffee beans. |
|---|