Multivariate screening in food adulteration: Untargeted versus targeted modelling
•High ability in adulteration testing is archived combining NIR and SIMCA technique.•A multivariate screening methodology is established by one-class modelling.•Untargeted model is suitable when there is lack of knowledge about the adulterant.•If there is a common or known adulterant, targeted model...
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Veröffentlicht in: | Food chemistry 2014-03, Vol.147, p.177-181 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •High ability in adulteration testing is archived combining NIR and SIMCA technique.•A multivariate screening methodology is established by one-class modelling.•Untargeted model is suitable when there is lack of knowledge about the adulterant.•If there is a common or known adulterant, targeted model is a good approximation.•Samples which are similar in more of 90% were properly distinguished.
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. |
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ISSN: | 0308-8146 1873-7072 |
DOI: | 10.1016/j.foodchem.2013.09.139 |