摘要
利用啤酒的近红外光谱数据比较了 PLS(偏最小二乘法,partial-Squares)和 PCA(主成分回归法,principal componentregression)两种方法在近红外光谱定量分析中的应用。并应用所建模型预测了 21 个啤酒样品麦芽的含量,结论为两种方法均适合近红外光谱定量分析,PLS 法所得预测结果准确度更高。
The different was compared between applications of PLS(partial-Squares) and PCA(principal component regression) with near-infrared spectra of beer. The content of enthol in 21 beer samples were pridicted by the model.The conclution is two methods can both application on quantitation analysis in NIR and the result of prediction by PLS is more accuracy .
