A case for Philippine cacao mineral factors as supporting evidence for geographic identification
Local commodities like cacao that are grown in specific regions are known to have distinct sensory profiles attributed to their origin. Hence, establishing a means to authenticate it is important in order to protect its integrity and the interests of consumers and producers. Using initial results ob...
Saved in:
| Main Authors: | , |
|---|---|
| 格式: | text |
| 語言: | English |
| 出版: |
Animo Repository
2022
|
| 主題: | |
| 在線閱讀: | https://animorepository.dlsu.edu.ph/etdb_chem/10 https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1012&context=etdb_chem |
| 標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
| 機構: | De La Salle University |
| 語言: | English |
| 總結: | Local commodities like cacao that are grown in specific regions are known to have distinct sensory profiles attributed to their origin. Hence, establishing a means to authenticate it is important in order to protect its integrity and the interests of consumers and producers. Using initial results obtained from portable X-ray Fluorescence (pXRF) analysis on seventeen (17) mixed varieties of Criollo, Forastero and Trinitario from an open call entry and three (3) regional samples of cacao beans participating in the Food Authenticity and Traceability (FAT) Program, a collaboration between the Department of Science and Technology - Philippine Nuclear Research Institute (DOST-PNRI), and the La Salle Food and Water Institute (LSFWI). The study investigated if geographic conditions such as temperature and humidity can influence the mineral composition of cacao, a determining factor in its flavor profile, using random forest algorithm (RF). RF was trained using a dataset of 5 selected elements (P, K, Ca, Mg, S) detected and their origin to group the mineral nutrient profiles into clusters. Evident differences were observed in the clustering of samples when factoring in temperature and humidity. This indicates that the two should be considered when verifying geographical origin given the mineral composition. Additional data on environmental parameters (e.g. pH, altitude, moisture level), soil chemistry, etc., could provide more insights on how other factors affect mineral composition, when coupled with additional statistical tools to account for the dissimilarities between samples and observe the effect of all environmental parameters and climatological data on mineral composition collectively. This can help with implementing more efficient regional farming practices and targeted interventions to improve cacao production and quality |
|---|