黄曲霉毒素
化学计量学
多元统计
污染
傅里叶变换红外光谱
线性判别分析
吸光度
花生
数学
色谱法
环境科学
化学
食品科学
统计
植物
光学
生物
物理
生态学
作者
Yu Yang,Yanan Zhang,Caiyan He,Mengyuan Xie,Huitai Luo,Ying Wang,Jun Zhang
摘要
Summary Contamination of peanut oil is a great concern in the industry. FTIR spectroscopy combined with chemometrics could develop a rapid and nondestructive method to screen aflatoxin‐contaminated peanut oil. Aflatoxin B1 ( AFB 1)‐ and aflatoxin ( AFT )‐positive peanut oils were screened by mid‐ IR ( MIR ) with classification models established by a novel multivariate decision tree ( MDT ) method. Two discriminant functions were developed in the fingerprint region based on absorbance ratio and moving window Fisher discrimination analysis methods for the two complex nodes in each MDT model. Window adjustment reduced the total different spectral data points in modelling to 23. The true‐positive and true‐negative rate of calibration and validation could both reach up to 100%. These results would render the possibility of efficient and economical design of a portable high‐speed multitasking MIR instrument for screening AFB 1‐ and AFT ‐contaminated peanut oil.
科研通智能强力驱动
Strongly Powered by AbleSci AI