提出利用微型近红外光谱仪、 结合Y型光纤探头, 在900～1 700 nm范围内对奶粉中蛋白质、 脂肪含量进行快速、 无损检测的漫反射光谱检测方法。 基于Unscrambler 9.7化学计量学软件, 选择合适的光谱波段, 通过PLS算法分别建立了蛋白质、 脂肪的校正模型, 得到蛋白质、 脂肪校正模型的决定系数R2分别为0.987和0.986, 均方根误差RMSC分别为0.385和0.419。 利用所建模型对预测样本数据集进行预测验证, 得到蛋白质的标准差SEPProtein=0.768、 脂肪的标准差SEPFat=1.109, 表明所建模型具有较高的预测能力, 已基本达到实用化要求。

The method based on miniature near-infrared spectrometer combined with Y fiber optic probe to detect the protein and fat in milk powder by diffuse reflectance spectroscopy in the wavelength range of 900～1 700 nm was proposed. By selecting the appropriate spectral bands, the correction models of protein and fat were established with partial least squares algorithm using Unscrambler 9.7 Chemometrics software. The determination coefficients R2 of the correction modes are 0.987 and 0.986 for protein and fat respectively, and the root mean square errors RMSEC are 0.385 and 0.419 respectively. Using these correction models to predict the protein and fat contents with 30 sets of forecast sample data, the prediction standard deviation is SEPProtein=0.751 for protein, and is SEPFat=1.109 for fat. The results indicate that these correction models have prediction capability with unknown samples and meet the on line requirements.