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研究利用傅里叶红外光谱结合化学计量学方法来实现对苏丹阿拉伯胶的产地和蛋白质含量的快速无损检测的可行性。采集自6个不同的产地,每个产地12个,总计72个阿拉伯胶样本,作为研究对象,运用线性判别分析(linear discriminant analysis,LDA)和反向区间偏最小二乘(backward interval partial least squares,Bi-PLS)法分别实现对苏丹阿拉伯胶的产地区分和蛋白质含量检测。结果表明,当主成分数为6时,LDA对样本的训练集(48个样本)和预测集(24个样本)的识别率都为100%。Bi-PLS法回归联合20个光谱子区间中的4个子区间得到最佳的蛋白质预测模型,其预测集相关系数为0.937 3,均方根误差为0.173%。因此,利用傅里叶红外光谱结合化学计量学方法可实现对苏丹阿拉伯胶的产地以及蛋白质的含量的快速无损检测。
The feasibility of rapid and non-destructive detection of the origin and protein content of gum arabic by using Fourier transform infrared spectroscopy and chemometrics methods was studied. A total of 72 gum arabic samples were collected from 6 different producing areas, each producing 12 samples. Linear discriminant analysis (LDA) and backward interval partial least squares , Bi-PLS) were used to detect the origin and protein content of gum arabic respectively. The results show that when the number of principal components is 6, LDA has a 100% recognition rate for the training set (48 samples) and the prediction set (24 samples) of the sample. The best protein prediction model was obtained by Bi-PLS regression combined with four sub-intervals of 20 spectral subsets. The correlation coefficient of prediction set was 0.937 3, and the root mean square error was 0.173%. Therefore, fast and non-destructive detection of the origin of Arab gum arabicum as well as the content of protein can be achieved by using the Fourier transform infrared spectroscopy combined with stoichiometry.