Qualitative and quantitative studies of phthalates in extra virgin olive oil (EVOO) by surface-enhanced Raman spectroscopy (SERS) combined with long short term memory (LSTM) neural network

Xijun Wu; Zherui Du; Renqi Ma; Xin Zhang; Daolin Yang; Hailong Liu; Yungang Zhang

doi:10.1016/j.foodchem.2023.137300

Qualitative and quantitative studies of phthalates in extra virgin olive oil (EVOO) by surface-enhanced Raman spectroscopy (SERS) combined with long short term memory (LSTM) neural network

Food Chem. 2024 Feb 1:433:137300. doi: 10.1016/j.foodchem.2023.137300. Epub 2023 Aug 26.

Authors

Xijun Wu¹, Zherui Du², Renqi Ma³, Xin Zhang¹, Daolin Yang¹, Hailong Liu¹, Yungang Zhang¹

Affiliations

¹ Measurement Technology & Instrumentation Key Laboratory of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004 China.
² Measurement Technology & Instrumentation Key Laboratory of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004 China. Electronic address: 1139347409@qq.com.
³ Measurement Technology & Instrumentation Key Laboratory of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004 China. Electronic address: 1824242910@qq.com.

PMID: 37657163
DOI: 10.1016/j.foodchem.2023.137300

Abstract

Phthalates are commonly used plasticizers in the plastics industry, and have received extensive attention due to their reproductive toxicity. Since phthalates are lipophilic solutions, phthalates can easily migrate from packaging to edible oils. This study synthesized stable and sensitive Gold Nanostars as SERS substrates to conduct qualitative and quantitative analysis of two common phthalates, dibutyl phthalate and di(2-ethylhexyl) phthalate. Two ethanol standard solutions and actual oil solutions of phthalates at different concentrations (10, 5, 1, 0.5, 0.1, 0.02 mg/kg) were prepared. After dimension reduction, LSTM achieved the accuracy of 98% for pure EVOO and EVOO adulterated with different types of phthalates. In terms of quantification, LSTM demonstrates great predictive performance with R_p² greater than 0.97 and the ratio of performance to deviation greater than 5. These results have certain guiding significance for the analysis of plasticizers in edible oil.

Keywords: Deep learning; Gold Nanostar; Olive oil; Phthalate; SERS.