Rapid detection of mercury in food via rhodamine 6G signal using surface-enhanced Raman scattering coupled multivariate calibration
| Autor: | Peihuan He, Muhammad Zareef, Waqas Ahmad, Quansheng Chen, Yawen Rong, Tianhui Jiao, Yi Xu, Huanhuan Li, Mehedi Hassan |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Materials science
Silver Analytical chemistry Nanoparticle chemistry.chemical_element Metal Nanoparticles Spectrum Analysis Raman 01 natural sciences Analytical Chemistry Rhodamine 6G symbols.namesake chemistry.chemical_compound 0404 agricultural biotechnology Desorption Surface plasmon resonance Rhodamines 010401 analytical chemistry Substrate (chemistry) 04 agricultural and veterinary sciences General Medicine Mercury Surface Plasmon Resonance 040401 food science 0104 chemical sciences Mercury (element) chemistry Calibration symbols Gold Amalgam (chemistry) Raman scattering Food Analysis Food Science |
| Zdroj: | Food chemistry. 358 |
| ISSN: | 1873-7072 |
| Popis: | Considering food safety and limitations of biorecognition elements, this study focused on the development of a novel method for predicting mercury (Hg2+) in fish and water samples using surface-enhanced Raman scattering (SERS) coupled wavenumber selection chemometric method. Herein, core–shell Au@Ag nanoparticles (Au@Ag NPs) were synthesized as SERS substrate, and rhodamine 6G (R6G) was used as signaling probe for Hg2+. In the presence of Hg2+, citrate ion of Au@Ag NPs induced complexation and become amalgam causes desorption of R6G occurred, resulted in decreased SERS signal intensity. Compared to surface Plasmon resonance method, SERS coupled genetic algorithm-partial least squares realized good correlation coefficient (0.9745 and 0.9773) in their prediction over the concentration ranges 1.0 × 102 to 1.0 × 10−3 µg/g. The recovery (88.45 – 94.73%) and precision (coefficient of variations, 3.28 – 5.76%) exhibiting satisfactory results suggested that the proposed method could be employed to predict Hg2+ in fish and water samples towards quality and safety monitoring. |
| Databáze: | OpenAIRE |
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