Abstract
Origin discrimination of sesame seeds is becoming one of the important factors for the sesame seed trade in Ethiopia as it influences the market price. This study was undertaken to construct accurate geographical origin discriminant models for Ethiopian sesame seeds using multi-element analysis and statistical tools. The concentration of 12 elements (Na, Mg, Cr, Mn, Fe, Cu, Co, Ni, Zn, Cd, As and Pb) were determined in 93 samples which were collected from three main sesame seed-producing regions in Ethiopia, Gondar, Humera and Wollega. According to a one-way analysis of variance (ANOVA), the concentration of 10 elements showing a significant difference (p < 0.05) was taken for statistical analysis using principal component analysis (PCA) and linear discriminant analysis (LDA). PCA showed some clustering of samples according to their respective origins. Then, the follow-up LDA resulted in a 100 % correct origin classification rate for all 93 sesame seed samples obtained from three regions in Ethiopia.
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