Establishment of a quality evaluation method for Angelica different processed products from genuine producing areas based on data mining

The paper reports the development of a quality evaluation method for Angelica different    processed products.  The data of high-performance liquid chromatography, water, total ash and extract were analyzed with SPSS Clementine11.0 software.  Discriminant analysis (DA) established the classification model and parameter for Angelica different processed products.  Fish’s discriminant functions of Angelica different processed products were generated using 8 predictor variables selected from 59 indexes.  The correct rate of  discriminating back substitution is 96.7%.  Angelica different processed products can be accurately and reliably recognized and validated with DA of SPSS Clementine11.0 software.