Determination of Dicofol in Tea Using Surface-Enhanced Raman Spectroscopy Coupled Chemometrics

Author:

Ke Qian1,Yin Limei12,Jayan Heera1,El-Seedi Hesham R.34,Gómez Paula L.5,Alzamora Stella M.5,Zou Xiaobo25,Guo Zhiming16ORCID

Affiliation:

1. School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China

2. China Light Industry Key Laboratory of Food Intelligent Detection & Processing, Jiangsu University, Zhenjiang 212013, China

3. Pharmacognosy Group, Department of Pharmaceutical Biosciences, BMC, Uppsala University, P.O. Box 591, SE 751 24 Uppsala, Sweden

4. International Research Center for Food Nutrition and Safety, Jiangsu University, Zhenjiang 212013, China

5. Consejo Nacional de Investigaciones Cientificasy Tecnicas (CONICET), University of Buenos Aires, Ciudad Autónoma de Buenos Aires C1428EGA, Argentina

6. International Joint Research Laboratory of Intelligent Agriculture and Agri-Products Processing, Jiangsu University, Zhenjiang 212013, China

Abstract

Dicofol is a highly toxic residual pesticide in tea, which seriously endangers human health. A method for detecting dicofol in tea by combining stoichiometry with surface-enhanced Raman spectroscopy (SERS) technology was proposed in this study. AuNPs were prepared, and silver shells were grown on the surface of AuNPs to obtain core–shell Au@AgNPs. Then, the core–shell Au@AgNPs were attached to the surface of a PDMS membrane by physical deposition to obtain a Au@AgNPs/PDMS substrate. The limit of detection (LOD) of this substrate for 4-ATP is as low as 0.28 × 10−11 mol/L, and the LOD of dicofol in tea is 0.32 ng/kg, showing high sensitivity. By comparing the modeling effects of preprocessing and variable selection algorithms, it is concluded that the modeling effect of Savitzky–Golay combined with competitive adaptive reweighted sampling–partial least squares regression is the best (Rp = 0.9964, RPD = 10.6145). SERS technology combined with stoichiometry is expected to rapidly detect dicofol in tea without labels.

Funder

National Key R&D Program of China

Outstanding Young Teachers of Blue Project in Jiangsu Province, the Key R&D Project of Jiangsu Province

Postgraduate Research and Practice Innovation Program of Jiangsu Province

Jiangsu Agriculture Science and Technology Innovation Fund

Open Fund of the Key Laboratory of Modern Agricultural Equipment and Technology of the Ministry of Education

Youth Project of the Faculty of Agricultural Equipment of Jiangsu University

Publisher

MDPI AG

Subject

Chemistry (miscellaneous),Analytical Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Molecular Medicine,Drug Discovery,Pharmaceutical Science

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