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Fast sensing of imidacloprid residue in tea using surface-enhanced Raman scattering by comparative multivariate calibration
摘要： This study focused on the fabrication of a rapid, highly sensitive and inexpensive technique for the quantification of imidacloprid residue in green tea, based on surface-enhanced Raman scattering (SERS) using highly roughed surface flower shaped silver nanostructure (as SERS substrate) coupled with the chemometric algorithm. The basic principle of this method is imidacloprid yielded SERS signal after adsorption on Ag-NF under laser excitation by the electromagnetic enhancement and the intensity of the peak is proportional to the concentration ranging from 1.0×103 to 1.0×10-4 μg/mL. Among the models used, the GA-PLS (Genetic algorithm-partial least square) exhibited superiority to quantify imidacloprid residue in green tea. The model achieved Rp (correlation coefficient) of 0.9702 with RPD of 4.95 % in the test set and RSD for precision recorded up to 4.50 %. Therefore, the proposed sensor could be employed to quantify imidacloprid residue in green tea for the safeguarding of quality and human health.
关键词： Different PLS algorithm,Green tea,Flower-shaped silver nanostructure,Surface-enhanced Raman scattering,Imidacloprid residue
更新于2025-09-10 09:29:36
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D-Optimal Design and PARAFAC as Useful Tools for the Optimisation of Signals from Fluorescence Spectroscopy Prior to the Characterisation of Green Tea Samples
摘要： A procedure based on a D-optimal design coupled with PARAFAC was proposed to optimise signals from molecular fluorescence spectroscopy to obtain the best experimental conditions for the achievement of the best fluorescence signal of green tea samples. Excitation-emission signals (EEMs) were used to analyse the liquid samples (tea infusions), whereas front-face fluorescence excitation-emission matrices (FFEEMs) were recorded for the solid samples (raw or powder tea leaves). The experimental effort was reduced considerably in both cases thanks to the D-optimal design. Once the optimal conditions have been found, the characterisation of green tea was carried out and the sensitivity and specificity were evaluated. The projection of the principal component analysis (PCA) scores enabled to differentiate among the types of liquid green tea (Chinese tea, Chinese tea with lemon and Indian tea with and without theine). The discrimination of solid green tea according to its geographical origin (Chinese, Indian and Japanese) was also carried out through PCA. In addition, the discrimination between the most expensive Japanese tea and the cheapest one was possible. The sensitivity of the models built with SIMCA was 100% and the specificity of the models for the Chinese tea with respect to the Japanese tea was also high.
关键词： Characterisation,Green tea,PCA,D-optimal design,Front-face fluorescence spectroscopy,PARAFAC
更新于2025-09-10 09:29:36