Machine Learning for Predicting Zearalenone Contamination Levels in Pet Food - Wang, Zhenlong; An, Wei; Wang, Jiaxue; Tao, Hui; Wang, Xiumin; Han, Bing; Wang, Jinquan (Toxins, 2024)
Keywords: Accuracy; Acute toxicity; Algorithms; Animal Feed - analysis; Animal Feed - microbiology; Animals; Classification; Communication; Contamination; Cost effectiveness; Data mining; E-nose; Electronic Nose; Electronic noses; Food; Food contamination; Food contamination & poisoning; Food Contamination - analysis; Food law; Health problems; Learning algorithms; Legislation; Liquid chromatography; Machine Learning; Mass spectrometry; Mass spectroscopy; Metal oxides; Methane; Multilayer perceptrons; Multilayers; mycotoxin; Mycotoxins; Performance evaluation; Pet food; Pet supplies industry; Petfoods; Pets; Positron emission; Safety and security measures; Sensors; Sulfur; Support vector machines; Tandem Mass Spectrometry; VOCs; Volatile compounds; Volatile organic compounds; Volatile Organic Compounds - analysis; Zearalenone; Zearalenone - analysis; China; mycotoxin; pet food; zearalenone; machine learning; E-nose