Institute of Medicinal Plants, Yunnan Academy of Agricultural Sciences, Kunming, 650200, China.
Yunnan Comtestor CO., LTD., Kunming, 650106, China.
Sci Rep. 2018 Jan 8;8(1):89. doi: 10.1038/s41598-017-18458-9.
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.
药用真菌拟层孔菌（云芝）干菌核是一种传统的中药材。由于其化学成分在地理起源上存在差异，这使得其治疗效果难以保持一致。拟层孔菌产地的鉴定是其在世界范围内得到认可和接受的基本前提。本研究采用四种变量选择方法对近红外光谱（NIR）进行变量选择，并对来源于中国云南的拟层孔菌进行特征变量筛选，建立 Fisher 函数模型，以进一步对其产地进行鉴别。在主成分分析（PCA）的模式空间中，由于药用真菌拟层孔菌菌核的外表皮（中文名称：茯苓皮，简称：FLP）和内部（中文名称：白茯苓，简称：BFL）之间存在明显差异，因此我们分别为 FLP 和 BFL 建立了判别模型。通过变量选择，模型得到了显著的改进，并且通过仅使用一小部分变量简化了模型。筛选出特征变量（BFL 为 13 个，FLP 为 10 个），建立 Fisher 判别函数模型，验证结果表明模型可靠有效。此外，还对特征变量进行了解释。
