Machine learning methods to predict the cultivation age of Panacis Quinquefolii Radix.

ABSTRACT:

Background

American ginseng (AG) is a valuable medicine widely consumed as a herbal remedy throughout the world. Huge price difference among AG with different growth years leads to intentional adulteration for higher profits. Thus, developing reliable approaches to authenticate the cultivation ages of AG products is of great use in preventing age falsification.

Methods

A total of 106 batches of AG samples along with their 9 physicochemical features were collected and measured from experiments, which was then split into a training set and two test sets (test set 1 and 2) according to the cultivation regions. Principle component analysis (PCA) was carried out to examine the distribution of the three data sets. Four machine learning (ML) algorithms, namely elastic net, k-neares

SUBMITTER: Hu X 

PROVIDER: S-EPMC8501543 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature