Educational Commission of Hubei Province of China [Q20161709]
机构署名：
本校为第一且通讯机构
院系归属：
食品科学与工程学院
摘要：
A simple and rapid classification model for olive and Camellia oil was proposed based on ion mobility spectrometry (IMS) fingerprints and chemometric model (peak detection and random forest algorithm). Results indicated that IMS fingerprint spectra by second-derivative algorithm could completely separate 64 olive oil and 79 Camellia oil samples used in this study by simply calculating the peak area. Random forest algorithm was employed to establish discriminant model for olive oil adulterated by Camellia oil. Simulated adulteration detection sh...
