Multivariate screening in food adulteration: Untargeted versus targeted modelling

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• 作者：M. Isabel L贸pez ; Esther Trullols ; M. Pilar Callao ; Itziar Ruis谩nchez
• 关键词：Multivariate screening ; Untargeted modelling ; SIMCA classification ; Food fraud ; Hazelnut ; Adulteration
• 刊名：Food Chemistry
• 出版年：15 March, 2014
• 年：2014
• 卷：147
• 期：Complete
• 页码：177-181
• 全文大小：636 K

文摘

Two multivariate screening strategies (untargeted and targeted modelling) have been developed to compare their ability to detect food fraud. As a case study, possible adulteration of hazelnut paste is considered. Two different adulterants were studied, almond paste and chickpea flour. The models were developed from near-infrared (NIR) data coupled with soft independent modelling of class analogy (SIMCA) as a classification technique. Regarding the untargeted strategy, only unadulterated samples were modelled, obtaining 96.3% of correct classification. The prediction of adulterated samples gave errors between 5.5% and 2%. Regarding targeted modelling, two classes were modelled: Class 1 (unadulterated samples) and Class 2 (almond adulterated samples). Samples adulterated with chickpea were predicted to prove its ability to deal with non-modelled adulterants. The results show that samples adulterated with almond were mainly classified in their own class (90.9%) and samples with chickpea were classified in Class 2 (67.3%) or not in any class (30.9%), but no one only as unadulterated.