近红外光谱法鉴别奶牛饲料中三聚氰胺甲醛树脂的可行性研究

摘要

Thirty-three samples of typical cow feed concentrate supplement without melamine-formaldehyde resin （MFR） and 99 ones adulterated with different concentrations of MFR were subjected to full wavelength near-infrared transmission and reflectance spectroscopic scanning. A discrimination model was established by BP （back propagation） neural network or PLS- LDA （partial least squares-linear discriminant analysis）. The BP neural network model showed 100% accurate prediction. The minimum cross validation error rate of the PLS-LDA model was 0.0778, misclassification rate 0.0667, and prediction error rate 0.1429. Therefore, it is feasible to establish a predictive model for detecting MFR adulteration in cow feed by means of near- infrared transmission and reflectance spectroscopy.%收集国内常用的、具有代表性的奶牛精补料33个样品,制备99个三聚氰胺甲醛树脂（MF）掺假样品,在全光谱范围内进行近红外透反射光谱扫描,选择合适的前处理方法,采用BP神经网络方法和PLS-LDA方法分别建立判别模型。建立的BP神经网络判别分析模型的预测正确率为100%,建立的PLS-LDA判别分析模型的交互验证最低错误率为0.0778,模型错分率为0.0667,模型预测错误率为0.1429。说明利用近红外透反射光谱建立定性分析模型来检测奶牛饲料中是否掺有MF的研究是可行的。