Application of Orthogonal Selection on the Alcohol Precipitation Processes of Flos Lonicerae Japonicae Extractions
正交空间样本选择在金银花多批醇沉过程中的应用

In this article, orthogonal selection (OS) was proposed in the sample selection in order to update the raw calibration model. Models described the relationship between concentrations of chlorogenic acid. And the corresponding spectra were used to monitor the alcohol precipitation processes. A comparison between models built using model updating (MU) and interval partial least squares (iPLS). Stacked partial least squares (SPLS) was executed on three batches of Flos Lonicerae Japonicae extractions. It was found that MU can be used to successfully correct batch-wise variations. The performance of model updating with OS outperforms that of Kennard-Stone algorithm.