ResNet and MaxEnt modeling for quality assessment of Wolfiporia cocos based on FT-NIR fingerprints.

ABSTRACT: As a fungus with both medicinal and edible value, Wolfiporia cocos (F. A. Wolf) Ryvarden & Gilb. has drawn more public attention. Chemical components' content fluctuates in wild and cultivated W. cocos, whereas the accumulation ability of chemical components in different parts is different. In order to perform a quality assessment of W. cocos, we proposed a comprehensive method which was mainly realized by Fourier transform near-infrared (FT-NIR) spectroscopy and ultra-fast liquid chromatography (UFLC). A qualitative analysis means was built a residual convolutional neural network (ResNet) to recognize synchronous two-dimensional correlation spectroscopy (2DCOS) images. It can rapidly identify samples from wild and cultivated W. cocos in different parts. As a qu

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC9666765 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature