Application of variable selection in the origin discrimination of Wolfiporia cocos (FA Wolf) Ryvarden & Gilb. based on near infrared spectroscopy

作者：Yuan, Tianjun; Zhao, Yanli; Zhang, Ji; Wang, Yuanzhong^*

来源：Scientific Reports, 2018, 8(1): 89.

DOI：10.1038/s41598-017-18458-9

• PARTIAL LEAST-SQUARES
• REWEIGHTED SAMPLING METHOD
• MULTIVARIATE CALIBRATION
• RAPID IDENTIFICATION
• CHEMOMETRIC ANALYSIS
• GEOGRAPHICAL ORIGIN
• SPECTRAL-ANALYSIS
• ALGORITHM
• REGRESSION
• ELIMINATION

Dried sclerotium of Wolfiporia cocos (F.A. Wolf) Ryvarden & Gilb. is a traditional Chinese medicine. Its chemical components showed difference among geographical origins, which made it difficult to keep therapeutic potency consistent. The identification of the geographical origin of W. cocos is the fundamental prerequisite for its worldwide recognition and acceptance. Four variable selection methods were employed for near infrared spectroscopy (NIR) variable selection and the characteristic variables were screened for the establishment of Fisher function models in further identification of the origin of W. cocos from Yunnan, China. For the obvious differences between poriae cutis (fu-ling-pi in Chinese, or FLP) and the inner part (bai-fu-ling in Chinese, or BFL) of the sclerotia of W. cocos in the pattern space of principal component analysis (PCA), we established discriminant models for FLP and BFL separately. Through variable selection, the models were significant improved and also the models were simplified by using only a small part of the variables. The characteristic variables were screened (13 for BFL and 10 for FLP) to build Fisher discriminant function models and the validation results showed the models were reliable and effective. Additionally, the characteristic variables were interpreted.

• 出版日期2018-1-8
• 单位河北医科大学; 云南省农业科学院