Your browser doesn't support javascript.
loading
Research on grade prediction of Persicae Semen based on binary Logistic regression analysis / 中草药
Chinese Traditional and Herbal Drugs ; (24): 4691-4696, 2019.
Article in Chinese | WPRIM | ID: wpr-850819
ABSTRACT

Objective:

A Logistic model for quality evaluation of Persicae Semen slices was constructed and its feasibility was verified in this study based on the thoughts on quality control of Chinese materia medica “Components reflect activity and activity points to efficacy”.

Methods:

Content of amygdalin, thrombin time (TT), ABTS clearance rate, DPPH inhibition rate, and hydroxyl radical scavenging ability in vitro were analyzed by a binary Logistic algorithm. Besides, a grade prediction model for Persicae Semen was established and verified.

Results:

A total of 18 batches of Persicae Semen were divided into four grades excellent (represented by Neimeng Persicae Semen), good (represented by Gansu Persicae Semen), medium (represented by Liang Persicae Semen), and poor (represented by Shaanxi Persicae Semen) according to the probability formula of the Logisitc model. All batches of Persicae Semen slices were classified accurately, manifested by the high value of fitting probability (P > 98%).

Conclusion:

The classification standard based on the Logistic algorithm involving quality control component-in vitro titer is applicable to Persicae Semen slices on the market. Classification results are accurate and reliable.

Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Chinese Traditional and Herbal Drugs Year: 2019 Type: Article

Similar

MEDLINE

...
LILACS

LIS

Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Chinese Traditional and Herbal Drugs Year: 2019 Type: Article