Identifying the Origin of Potentilla Anserine Based on Infrared Spectroscopy and Random Forest Method
The infrared spectroscopy combining with random forest method was used in the identification of Potentilla anserine from different fields of Qinghai Province.Forty-two samples of Potentilla anserine from different fields of Qinghai province were surveyed by FTIR (Fourier transform infrared spectroscopy).The original data matrix of FTIR was pretreated with wavelet transform.The results showed that the infrared spectroscopy data were compressed to 1/8 of its original data,but the spectral information and analytical accuracy were not deteriorated.The 42 samples of Potentillaanserine were divided into 30 training samples and 12 validation samples.Random forest model was constructed by the training samples to predict the discrimination effect of identifying the origin of Potentilla anserine with internal cross validation and external validation sample.R language was adopted to achieve algorithm of random forest.Parameters of random forest model were optimized.The prediction accuracy of the proposed model was 100％ for the training samples and 100％ for the test samples.It can be concluded that the method is quite suitable for the fast discrimination of producing areas of Potentilla anserine.This infrared spectral analysis technology combined the random forest was proved to be a reliable and new practical method for the identification of geographical origin of Chinese medicine.The method in the present paper is very broad prospect of application.
Potentilla anserineinfrared spectroscopywavelet transformrandom forestR language
NETL
NSTL
万方数据
维普
