Combining Multi-Element Analysis with Statistical Modeling for Tracing the Origin of Green Coffee Beans from Amhara Region, Ethiopia
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Characterization of coffee terroirs is important to determine authenticity and provide confidence for consumers to select the right product. In this regard, Amhara Region, which is located at the northwestern part of Ethiopia, produces various local coffee types with distinct cup qualities. The coffees are, however, not yet registered with certification marks or trademarks for indications of their geographical origins. This study was aimed at developing analytical methodology useful to determine the geographical origin of green coffee beans produced in Amhara Region based on multi-element analysis combined with multivariate statistical techniques. For this, a total of 120 samples of green coffee beans, collected from four major cultivating zones (West Gojjam, East Gojjam, Awi, and Bahir Dar Especial Zones) were analyzed for K, Mg, Ca, Mn, Fe, Cu, Fe, Co, Ni, Zn, Si, Cr, Cd, and Pb using inductively coupled plasma–optical emission spectroscopy. The elemental analysis data were subjected to principal component analysis (PCA) and linear discriminant analysis (LDA). PCA was used to explore the natural groupings of samples and the discriminatory ability of elements. Accordingly, the elements K, Mg, Ca, and Na were found to be the main discriminators among samples. LDA provided a model to classify the coffee samples based on their production zones with an accuracy of 94.2% and prediction ability of 93.4%. Thus, the elemental composition of green coffee beans can be used as a chemical descriptor in the authentication of coffee produced in Amhara Region.
KeywordsAmhara Region Green coffee beans Metals Geographical origin Linear discriminate analysis Principal component analysis
This work was supported by the Ministry of Science and Technology of Ethiopia (3rd round, 2017) for the project title: “Enhancing the Quality and Market Share of the Underutilized Coffee of Amhara Region Through Chemical Analysis, Postharvest Loss Reduction and Mapping for Authentication (Branding)”. The authors are also thankful to Bahir Dar University for the laboratory facilities and the Amhara Region’s Bureau of Agriculture for its logistic support. Furthermore, Mr. Lakachew Emiru from the Amhara Bureau of Agriculture is also acknowledged for his guidance during sample collection.
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they have no conflict of interest.
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