采用近红外光谱技术结合化学计量学手段,建立不同品牌食醋的快速鉴别方法。用近红外光谱仪对103组食醋样品进行扫描,采用二阶导数对图谱进行预处理、标准化处理、T检验和主成分分析(principal component analysis,PCA),运用留一法构建线性判别分析(linear discriminant analysis,LDA)模型。结果表明,原始近红外谱图经过处理后,显示出同种品牌食醋主成分的聚类趋势;交叉验证结果表明,PCA-LDA模型预测不同品牌食醋的正确率高达85.57%,该模型具有较好的预测效果。该研究结合近红外光谱与PCA-LDA模型,为不同品牌食醋提供一种快速鉴别方法,具有处理近红外光谱数据,研究物质主成分的应用潜力。
Near-infrared spectroscopy combined with chemometrics has been used to establish identification methods for different brands of vinegar. The data of 103 groups of vinegar samples were obtained by near-infrared spectrometer, and the second derivative, standard treatment, T-text test and principal component analysis (PCA) were used to process the data, and the last linear discriminant analysis (LDA) model was constructed by using the method of one remaining method. The results indicated that compared with the original infrared spectrum, the processed data showed the clustering trend of the main components of the same brand of vinegar. The results of cross-validation demonstrated that the accuracy rate of identifying different brands of vinegar was 85.57% using PCA-LDA model, which was feasible and applicable. Overall, the method of combining near-infrared spectroscopy with PCA-LDA model has provided a rapid identification technique for different brands of vinegar, which has the potential to process near-infrared spectroscopy data to study the main components of different matter.
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