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The aim of this study is to detect the percentages of adulteration of argan oil with sunflower oil by using the combination of a voltammetric e-tongue and an e-nose based on metal oxide semiconductor sensors and pattern recognition techniques. Data analysis is performed by three pattern recognition methods: principal component analysis (PCA), discriminant factor analysis (DFA), and support vector machines (SVMs). Excellent results were obtained in the differentiation between unadulterated and adulterated argan oil with sunflower one. To the best of our knowledge, this is the first attempt to demonstrate whether the combined e-nose and e-tongue technologies could be successfully applied to the detection of adulteration of argan oil.<\/jats:p>","DOI":"10.1155\/2014\/245831","type":"journal-article","created":{"date-parts":[[2014,8,19]],"date-time":"2014-08-19T17:10:06Z","timestamp":1408468206000},"page":"1-10","source":"Crossref","is-referenced-by-count":76,"title":["Detection of Adulteration in Argan Oil by Using an Electronic Nose and a Voltammetric Electronic Tongue"],"prefix":"10.1155","volume":"2014","author":[{"given":"Madiha","family":"Bougrini","sequence":"first","affiliation":[{"name":"Sensor Electronic and Instrumentation Group, Department of Physics, Faculty of Sciences, Moulay Isma\u00efl University, BP 11201, Zitoune, Meknes, Morocco"}]},{"given":"Khalid","family":"Tahri","sequence":"additional","affiliation":[{"name":"Sensor Electronic and Instrumentation Group, Department of Physics, Faculty of 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