Abstract

This study aims to distinguish Indonesian cashew nuts’ geographical origin based on their elemental profiles and chemical composition. Nine elements and five chemical components of cashew nut samples were analyzed. The profiles of four micro-elements, Zn, Cu, Mn, Cr, and five macro elements, K, Ca, Mg, Fe, Na, of Indonesian cashew nuts were determined using Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES). Simultaneously, the chemical components of moisture, ash, total protein, total fat, and carbohydrate contents were measured using the AOAC standard. The combination of elemental profiles was then analyzed with a scatterplot matrix diagram and a multivariate statistical technique, Canonical Discriminant Analysis (CDA). Inter-region discrimination among four major Indonesian cashew nuts producers was achieved by applying CDA. Sodium (Na), calcium (Ca), potassium (K), manganese (Mn), zinc (Zn), and total protein were the best descriptors for cashew nuts origin. According to the findings, the most abundant element in cashew nuts is potassium (K), followed by magnesium (Mg), and calcium (Ca) (Ca). Fat is the most abundant chemical composition in cashew nuts at the same time. Potassium (K), magnesium (Mg), and calcium (Ca) concentrations showed major regional variations. On the other hand, zinc (Zn) and manganese (Mn) are two micro-elements that may help identify the origin of cashew nut samples. The use of a Canonical Discriminant Analysis scatters plot to visualize the origin of Indonesian cashew nut samples was less successful based on micro-element concentrations. The CDA scatter plot application based on macroelements, and the CDA scatter plot application based on a mixture of micro- and macro-elements produced better results than the CDA scatter plot application based on micro-elements. Furthermore, the best visual separation was achieved using a CDA scatter plot based on a combination of elemental profiles and protein concentration. For a complete characterization of cashew nuts, further research with a large number of samples is needed.

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