LIU Changyong, LU Chunxia, CHEN Xia, et al. Colorimetric Detection of Sudan Based on the Aptamer and Cationic Compound Induced Gold Nanoparticles Aggregation[J]. Science and Technology of Food Industry, 2023, 44(3): 279−285. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2022030314.
Citation: LIU Changyong, LU Chunxia, CHEN Xia, et al. Colorimetric Detection of Sudan Based on the Aptamer and Cationic Compound Induced Gold Nanoparticles Aggregation[J]. Science and Technology of Food Industry, 2023, 44(3): 279−285. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2022030314.

Colorimetric Detection of Sudan Based on the Aptamer and Cationic Compound Induced Gold Nanoparticles Aggregation

  • In this study, a simple, economical and rapid colorimetric assay was developed for the detection of Sudan, in which Sudan-binding aptamer was used as recognition element, unmodified gold nanoparticles (AuNPs) as sensing signal, and poly(diallyldimethylammonium chloride) (PDDA) as inducer for gold nanoparticle aggregation. The sensitivity, accuracy and specificity of developed method were evaluated under optimized condition. Finally, the colorimetric sensor was applied to detection Sudan in food samples, and the results were compared with GB standard method (GB/T 19681-2005). The best procedure for Sudan analysis in our system was: The concentration of aptamer at 5 nmol/L, the concentration of PDDA at 20 nmol/L, and the reaction time was 4 min. The correlation between concentration of Sudan III and absorbance ratio of gold nanoparticles (A650nm/A530nm) was observed to be linear within the range of 3.13 to 50 ng/mL. The limit of visual detection was 3.13 ng/mL by naked-eye observation. The detection time was 5 min. The colorimetric sensor had high specificity for Sudan I, II, III and IV, and no cross-reactivity towards sunset yellow, tartrazine, and 1-amino-2-methylanthraquinone. Further, the colorimetric sensor was applied to measure Sudan Ⅲ in spiked real samples, and the recoveries were in the range of 85.4%~102.5%, with relative standard deviations of 3.37%~6.75%. Our study provides a simple, fast, and easy to read method for Sudan analysis, which can be applied in future on-site detection in food samples.
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