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A method for predicting the content of quality markers in salvia miltiorrhiza

A technology of markers and salvia miltiorrhiza, applied in the direction of measurement devices, neural learning methods, biological neural network models, etc., can solve problems such as redundancy, reduce model prediction ability, noise, etc., achieve accurate prediction performance, reduce overall computing costs, and train fast effect

Active Publication Date: 2022-03-01
SHANDONG UNIV OF TRADITIONAL CHINESE MEDICINE +1
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Problems solved by technology

Because in a given set of features, not all features are necessary, and some features are noisy or redundant, which may even reduce the predictive ability of the model

Method used

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  • A method for predicting the content of quality markers in salvia miltiorrhiza
  • A method for predicting the content of quality markers in salvia miltiorrhiza
  • A method for predicting the content of quality markers in salvia miltiorrhiza

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Embodiment Construction

[0035] A method for predicting the content of quality markers in Salvia miltiorrhiza, comprising the following steps:

[0036] (1) Preparation of plant material

[0037] Under laboratory conditions, seeds of Salvia miltiorrhiza of cultivar CK were sown in square flowerpots under laboratory conditions by soil culture. After two weeks of germination, the unified salvia seedlings were transplanted to 3 test sites (each test site was about 667 square meters) in 3 cities in Shandong Province, such as figure 1 shown. Each site, including unshaded plots with moderately fertile soils and no additional fertilizer or water inputs, was managed according to uniform standards. 2-29 weeks after transplantation (April-October 2018), 10 individual plants of Salvia miltiorrhiza in the same growth state were collected every week, and the distance between each plant was greater than 25m. All samples were preserved in the School of Pharmacy, Shandong University of Traditional Chinese Medicine,...

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Abstract

The invention relates to a method for predicting the content of quality markers in Salvia miltiorrhiza. A long-term and short-term memory network model is adopted, and a climatic factor and metabolite spectrum analysis (plant metabolomics) method is used to analyze four quality markers of Salvia miltiorrhiza in the field in the later stage of root expansion. content is predicted. Due to the existence of interference factors, the maximum information coefficient (MIC) is used for correlation analysis to achieve feature selection, and the key factors are obtained after filtering. The Long Short-Term Memory (LSTM) model ensures the accuracy of prediction by effectively extracting and fully reflecting the intrinsic characteristics of climatic factors and product changes related to the metabolic process. The LSTM algorithm based on MIC has been verified in the experimental field of Salvia miltiorrhiza in Sandi, Shandong, which ensures the robustness of the model. The invention helps to formulate a reasonable harvesting strategy for Salvia miltiorrhiza or take remedial measures to obtain qualified medicinal materials under extreme weather conditions.

Description

technical field [0001] The invention relates to a method for predicting the content of quality markers in salvia miltiorrhiza. Background technique [0002] For thousands of years, medicinal plants around the world have been a staple in the prevention and treatment of human disease and the source of numerous prescription and over-the-counter medicines. Medicinal plants are a special kind of economic crops, and their harvest time is affected by both crop yield and active ingredient content. [0003] Salvia miltiorrhiza is a medicinal plant of Lamiaceae. As one of the most widely used medicinal materials in my country, danshen has good economic, social and ecological benefits. Danshen has been used to treat cardiovascular and cerebrovascular diseases for more than 2,000 years. Danshen has been used in the clinical treatment of dysmenorrhea, amenorrhea, hypertension, liver cirrhosis, chronic renal failure and other diseases. It also has the potential to treat neurodegenerati...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16C20/70G06N3/04G06N3/08G01N30/02
CPCG16C20/70G06N3/049G06N3/08G01N30/02G06N3/048G06N3/045
Inventor 赵妍张永清刘谦
Owner SHANDONG UNIV OF TRADITIONAL CHINESE MEDICINE
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