Article

Determining the adulteration of spices with Sudan I-II-II-IV dyes by UV-visible spectroscopy and multivariate classification techniques.

Department of Analytical and Organic Chemistry, Rovira i Virgili University, Marcel.lí Domingo s/n Campus Sescelades, E-43007 Tarragona, Spain.
Talanta (Impact Factor: 3.5). 09/2009; 79(3):887-92. DOI: 10.1016/j.talanta.2009.05.023
Source: PubMed

ABSTRACT We propose a very simple and fast method for detecting Sudan dyes (I, II, III and IV) in commercial spices, based on characterizing samples through their UV-visible spectra and using multivariate classification techniques to establish classification rules. We applied three classification techniques: K-Nearest Neighbour (KNN), Soft Independent Modelling of Class Analogy (SIMCA) and Partial Least Squares Discriminant Analysis (PLS-DA). A total of 27 commercial spice samples (turmeric, curry, hot paprika and mild paprika) were analysed by chromatography (HPLC-DAD) to check that they were free of Sudan dyes. These samples were then spiked with Sudan dyes (I, II, III and IV) up to a concentration of 5 mg L(-1). Our final data set consisted of 135 samples distributed in five classes: samples without Sudan dyes, samples spiked with Sudan I, samples spiked with Sudan II, samples spiked with Sudan III and samples spiked with Sudan IV. Classification results were good and satisfactory using the classification techniques mentioned above: 99.3%, 96.3% and 90.4% of correct classification with PLS-DA, KNN and SIMCA, respectively. It should be pointed out that with SIMCA, there are no real classification errors as no samples were assigned to the wrong class: they were just not assigned to any of the pre-defined classes.

1 Bookmark
 · 
226 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: The contents of 25 elements in 4 types of commercial marine species from the East China Sea were determined by inductively coupled plasma mass spectrometry and atomic absorption spectrometry. The elemental composition was used to differentiate marine species according to geographical origin by multivariate statistical analysis. The results showed that principal component analysis could distinguish samples from different areas and reveal the elements which played the most important role in origin diversity. The established models by partial least squares discriminant analysis (PLS-DA) and by probabilistic neural network (PNN) can both precisely predict the origin of the marine species. Further study indicated that PLS-DA and PNN were efficacious in regional discrimination. The models from these 2 statistical methods, with an accuracy of 97.92% and 100%, respectively, could both distinguish samples from different areas without the need for species differentiation.
    Journal of Food Science 11/2013; · 1.78 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Multivariate screening methods are increasingly being implemented but there is no worldwide harmonized criterion for their validation. This study contributes to establish protocols for validating these methodologies. We propose the following strategy: (1) Establish the multivariate classification model and use receiver operating characteristic (ROC) curves to optimize the significance level (α) for setting the model's boundaries. (2) Evaluate the performance parameter from the contingency table results and performance characteristic curves (PCC curves). The adulteration of hazelnut paste with almond paste and chickpea flour has been used as a case study. Samples were analyzed by infrared (IR) spectroscopy and the multivariate classification technique used was soft independent modeling of class analogies (SIMCA). The ROC study showed that the optimal α value for setting the SIMCA boundaries was 0.03 in both cases. The sensitivity value was 93%, specificity 100% for almond and 98% for chickpea, and efficiency 97% for almond and 93% for chickpea.
    Analytica chimica acta 05/2014; 827:28-33. · 4.31 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The presented work describes the development of a simple, fast and effective on-line SPE-UHPLC-UV/vis method using fused core particle columns for extraction, separation and quantitative analysis of the nine illegal dyes, most frequently found in chilli-containing spices. The red dyes Sudan I-IV, Sudan Red 7B, Sudan Red G, Sudan Orange G, Para Red, and Methyl Red were separated and analyzed in less than 9min without labor-consuming pretreatment procedure. The chromatographic separation was performed on Ascentis Express RP-Amide column with gradient elution using mixture of acetonitrile and water, as a mobile phase at a flow rate of 1.0mLmin(-1) and 55°C of temperature. As SPE sorbent for cleanup and pre-concentration of illegal dyes short guard fused core column Ascentis Express F5 was used. The applicability of proposed method was proven for three different chilli-containing commercial samples. Recoveries for all compounds were between 90% and 108% and relative standard deviation ranged from 1% to 4% for within- and from 2% to 6% for between-day. Limits of detection showed lower values than required by European Union regulations and were in the range of 3.3-10.3µgL(-1) for standard solutions, 5.6-235.6µgkg(-1) for chilli-containing spices.
    Talanta 12/2014; 130C:433-441. · 3.50 Impact Factor

Full-text

Download
84 Downloads
Available from
May 23, 2014