Omar Elhamdaoui, A. El Orche, A. Cheikh, K. Laarej, K. Karrouchi, M. El Karbane, M. Bouatia
{"title":"Tracing the Geographical Origin of Moroccan Saffron by Mid-Infrared Spectroscopy and Multivariate Analysis","authors":"Omar Elhamdaoui, A. El Orche, A. Cheikh, K. Laarej, K. Karrouchi, M. El Karbane, M. Bouatia","doi":"10.30744/brjac.2179-3425.ar-23-2022","DOIUrl":null,"url":null,"abstract":"This work aims to investigate the potential of mid-infrared spectroscopy (MIR) and chemometrics algorithms for the determination of geographical origin and detection of adulteration of Moroccan saffron samples. First, the determination of the geographical origin of five saffron varieties was analyzed by linear discriminant analysis (PCA-LDA) and partial least squares discriminant analysis (PLS-DA). As a result, the developed models correctly classified saffron samples in a subset of external validation with 100% predictive ability. Next, partial least squares regression (PLS-R) was conducted to estimate the amount of adulterants (safflower) in the saffron samples. A good performance was found with Coefficient of Determination (R2) between 0.97 and 0.99. Compared to other techniques, the main advantage of the proposed methods are non-destructive, fast and sensitive which allows to achieve very precise and accurate results.","PeriodicalId":9115,"journal":{"name":"Brazilian Journal of Analytical Chemistry","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brazilian Journal of Analytical Chemistry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30744/brjac.2179-3425.ar-23-2022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
引用次数: 1
Abstract
This work aims to investigate the potential of mid-infrared spectroscopy (MIR) and chemometrics algorithms for the determination of geographical origin and detection of adulteration of Moroccan saffron samples. First, the determination of the geographical origin of five saffron varieties was analyzed by linear discriminant analysis (PCA-LDA) and partial least squares discriminant analysis (PLS-DA). As a result, the developed models correctly classified saffron samples in a subset of external validation with 100% predictive ability. Next, partial least squares regression (PLS-R) was conducted to estimate the amount of adulterants (safflower) in the saffron samples. A good performance was found with Coefficient of Determination (R2) between 0.97 and 0.99. Compared to other techniques, the main advantage of the proposed methods are non-destructive, fast and sensitive which allows to achieve very precise and accurate results.
期刊介绍:
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