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Issue 20, 2014
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Simultaneous determination of thiocyanate ion and melamine in milk and milk powder using surface-enhanced Raman spectroscopy

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Abstract

In this study, a simple and efficient method based on surface-enhanced Raman spectroscopy (SERS) was developed to detect thiocyanate ion (SCN) and melamine in milk and milk powder. Silver nanoparticles (AgNPs), sodium chloride (NaCl) and sodium hydroxide (NaOH) were used as the substrate, the aggregating agent and the alkaline adjusting agent for the SERS process, respectively. The SERS peak intensity at 445 cm−1 was measured under low NaCl concentration for determining SCN, followed by the measurement of the SERS peak intensity at 704 cm−1 under high NaCl concentration for determining melamine. The determination conditions for SERS, including the amount of AgNPs, NaCl and NaOH, and the mixing time before measurement, were optimized. By the present method, good linear responses were obtained for SCN and melamine in the concentration ranges of 2.00–191.00 mg L−1 and 0.01–4.80 mg L−1 respectively, with correlation coefficients higher than 0.998. The present method was successfully applied to the simultaneous determination of SCN and melamine in four spiked milk samples and three certified milk powder samples. The recoveries of SCN and melamine in spiked milk samples were 95.15–100.47% and 94.43–102.84%, respectively. The relative standard deviations (RSDs) for determining melamine in certified milk powder samples were lower than 1.6%.

Graphical abstract: Simultaneous determination of thiocyanate ion and melamine in milk and milk powder using surface-enhanced Raman spectroscopy

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Publication details

The article was received on 23 Apr 2014, accepted on 25 Aug 2014 and first published on 26 Aug 2014


Article type: Paper
DOI: 10.1039/C4AY00965G
Citation: Anal. Methods, 2014,6, 8388-8395

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    Simultaneous determination of thiocyanate ion and melamine in milk and milk powder using surface-enhanced Raman spectroscopy

    Q. Yang, F. Liang, D. Wang, P. Ma, D. Gao, J. Han, Y. Li, A. Yu, D. Song and X. Wang, Anal. Methods, 2014, 6, 8388
    DOI: 10.1039/C4AY00965G

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