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

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,...

Ausführliche Beschreibung

Bibliographische Detailangaben
Hauptverfasser:	Cheng Hao, Qingchuan Zhang, Shimin Wang, Tongqiang Jiang, Wei Dong
Format:	Artikel
Sprache:	English
Veröffentlicht:	MDPI AG 2023-06-01
Schriftenreihe:	Foods
Schlagworte:	risk assessment LSTM XGBoost risk prediction edible oil BaP
Online Zugang:	https://www.mdpi.com/2304-8158/12/11/2241

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