| Abstract
| - The objective of this study was to demonstrate the feasibility of chemical profiling methods combinedwith multivariate methods to differentiate the geographical growing regions of pistachios (Pistachiavera). Elemental analysis (Ba, Be, Ca, Cu, Cr, K, Mg, Mn, Na, V, Fe, Co, Ni, Cu, Zn, Sr, Ti, Cd, andP) of pistachios samples was performed using inductively coupled plasma atomic emissionspectrometry. Analysis of inorganic anions and organic acids (selenite, bromate, fumarate, malate,selenate, pyruvate, acetate, phosphate, and ascorbate) of pistachio samples was performed usingcapillary electrophoresis. Bulk carbon and nitrogen isotope ratios were performed using stable isotopeMS. There were nearly 400 pistachio samples analyzed from the three major pistachio growingregions: Turkey, Iran, and California (United States). A computational evaluation of the trace elementdata sets was carried out using statistical pattern recognition methods including principal componentanalysis, canonical discriminant analysis, discriminant analysis, and neural network modeling. Severallinear discriminant function models classified the data sets with 95% or higher accuracy. We reportthe development of a method combining elemental analysis and classification techniques that maybe widely applied to the determination of the geographical origin of foods. Keywords: Geographic authenticity; canonical discriminant analysis; discriminant analysis; principalcomponent analysis; metals; anions; organic acids; isotope ratios; Pistachia vera; geographic origin
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