Measurement of polycyclic aromatic hydrocarbons in edible oils and potential health risk to consumers using Monte Carlo simulation, southwest Iran

Barzegar, Gelavizh; Kalantary, Roshanak Rezaei; Bashiry, Moein; Jaafarzadeh, Nematollah; Ghanbari, Farshid; Shakerinejad, Ghodratollah; Khatebasreh, Masoumeh; Sabaghan, Mohamad

doi:10.1007/s11356-022-22446-6

Cited by 3 publications

(1 citation statement)

References 43 publications

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“…Li et al [18] used ILCR for assessing the risk of BaP in doughnuts. Gelavizh Barzegar et al [19] used Monte Carlo simulations to characterize the daily intake MOEs and ILCR of edible oils sold in southwestern Iran. Bomi Kang et al [20] employed MOEs to assess the risk of PAHs in Korean edible oils and found that despite the detection of PAHs, their effects on human exposure were not significant.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Safety Risk Levels of Benzopyrene Residues in Edible Oils in China Based on the Variable-Weight Combined LSTM-XGBoost Prediction Model

Cheng

Zhang

Wang

et al. 2023

Foods

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To assess and predict the food safety risk of benzopyrene (BaP) in edible oils in China, this study collected national sampling data of edible oils from 20 Chinese provinces and their prefectures in 2019, and constructed a risk assessment model of BaP in edible oils with consumption data. Initially, the k-means algorithm was used for risk classification; then the data were pre-processed and trained to predict the data using the Long Short-Term Memory (LSTM) and the eXtreme Gradient Boosting (XGBoost) models, respectively, and finally, the two models were combined using the inverse error method. To test the effectiveness of the prediction model, this study experimentally validated the model according to five evaluation metrics: root mean square error (RMSE), mean absolute error (MAE), precision, recall, and F1 score. The variable-weight combined LSTM-XGBoost prediction model proposed in this paper achieved a precision of 94.62%, and the F1 score value reached 95.16%, which is significantly better than other neural network models; the results demonstrate that the prediction model has certain stability and feasibility. Overall, the combined model used in this study not only improves the accuracy but also enhances the practicality, real-time capabilities, and expandability of the model.

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Section: Introductionmentioning

confidence: 99%

Prediction of Safety Risk Levels of Benzopyrene Residues in Edible Oils in China Based on the Variable-Weight Combined LSTM-XGBoost Prediction Model

Cheng

Zhang

Wang

et al. 2023

Foods

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Photo- and Bio-degradation of Selected Persistent Organic Pollutants

Gupta,

Dhiman,

Kumar

et al. 2024

Separation & Purification Reviews

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Levels and Health Risk Assessment of Polycyclic Aromatic Hydrocarbons in Vegetable Oils and Frying Oils by Using the Margin of Exposure (MOE) and the Incremental Lifetime Cancer Risk (ILCR) Approach in China

Liu

Zhou

et al. 2023

Foods

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A total of 139 vegetable oils and 48 frying oils produced in China were tested for the levels of 15 Environmental Protection Agency-regulated polycyclic aromatic hydrocarbons (PAHs). The analysis was completed by high-performance liquid chromatography-fluorescence detection (HPLC-FLD). The limit of detection and limit of quantitation were ranged between 0.2–0.3 and 0.6–1 μg/kg, respectively. The average recovery was 58.6–90.6%. The highest mean of total PAHs was found in peanut oil (3.31 μg/kg), while the lowest content was found in olive oil (0.39 μg/kg). In brief, 32.4% of vegetable oils exceeded the European Union maximum levels in China. The detected level of total PAHs in vegetable oils was lower than the frying oils. The mean dietary exposure to PAH15 ranged from 0.197 to 2.051 ng BaPeq/kg bw/day. The margin of exposure values was greater than 10,000, and the cumulative probabilities of the incremental lifetime cancer risk of different age groups were less than the priority risk level (10−4). Therefore, there was no potential health concern for specific populations.

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Measurement of polycyclic aromatic hydrocarbons in edible oils and potential health risk to consumers using Monte Carlo simulation, southwest Iran

Cited by 3 publications

References 43 publications

Prediction of Safety Risk Levels of Benzopyrene Residues in Edible Oils in China Based on the Variable-Weight Combined LSTM-XGBoost Prediction Model

Prediction of Safety Risk Levels of Benzopyrene Residues in Edible Oils in China Based on the Variable-Weight Combined LSTM-XGBoost Prediction Model

Photo- and Bio-degradation of Selected Persistent Organic Pollutants

Levels and Health Risk Assessment of Polycyclic Aromatic Hydrocarbons in Vegetable Oils and Frying Oils by Using the Margin of Exposure (MOE) and the Incremental Lifetime Cancer Risk (ILCR) Approach in China

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