Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Traditional Chinese medicinal material seed distinguishing and grade rapid distinguishing method

A discrimination method and technology of Chinese herbal medicines, applied in the field of hyperspectral images, can solve the problems of difficult application of rapid detection of Chinese herbal medicine seeds identification, time-consuming and labor-intensive, etc., and achieve the effect of rapid intelligent discrimination and screening, and fusion problem solving

Active Publication Date: 2019-08-23
湖南省中医药研究院
View PDF13 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Traditional seed identification methods generally rely on manual work, which is time-consuming and labor-intensive, and it is difficult to apply to the rapid detection of traditional Chinese medicine seed identification.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Traditional Chinese medicinal material seed distinguishing and grade rapid distinguishing method
  • Traditional Chinese medicinal material seed distinguishing and grade rapid distinguishing method
  • Traditional Chinese medicinal material seed distinguishing and grade rapid distinguishing method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0085] Identification of Qianhu and Fangfeng seeds based on random forest algorithm:

[0086] The discriminant analysis process is divided into the following steps: First, use random forest to train the training set samples to build a prediction model; based on the constructed training model, classify and predict the remaining 12 prediction set samples to evaluate their predictive ability. The results of the classification and analysis of the two types of seeds through the random forest algorithm are shown in the appendix figure 1 , it can be seen that the seeds of Peucedanum and Fangfeng are gathered in their respective areas, indicating that the calculation model constructed by the random forest algorithm can effectively distinguish the seeds of Peucedanum and Fangfeng. The results are shown in Table 1.

[0087] Table 1 Classification prediction results of Peucedanum and Parsnip seed samples

[0088]

Embodiment 2

[0090] To identify the different grades of beard seeds:

[0091] According to the 100-seed weight, three categories of large, medium and small were screened out from the Peucedanum seeds. The information of the samples of the three categories is shown in Table 2.

[0092] Table 2 Information of three types of samples

[0093] Sample category Sample 1 (g) Sample 2 (g) Sample 3 (g) Sample 4 (g) Sample 5 (g) mean ± variance beard (big) 0.4475 0.4207 0.4412 0.4624 0.4512 0.4446±0.0154 Front Hu (middle) 0.3050 0.3291 0.3246 0.3190 0.3221 0.3199±0.0091 beard (small) 0.2147 0.2236 0.2085 0.2292 0.2277 0.2207±0.0088

[0094] According to the proposed pattern recognition method, the three categories of seeds are classified and predicted, and the prediction accuracy reaches 80%.

[0095] In summary, this application uses hyperspectral imaging technology to obtain image information and spectral information of samples, and uses m...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a traditional Chinese medicinal material seed distinguishing and grade rapid distinguishing method, which comprises the following steps: randomly selecting every 100 seeds fromradix peucedani and radix saposhnikoviae seeds as a sample, and respectively constructing 18 samples for each type of seeds; analyzing the sample by using a hyperspectral imaging technology to obtainsample information of different types of seeds; furthermore, the ROI area of each sample is preferably selected; the method comprises the following steps: carrying out averaging processing on spectrums of an area to construct characteristic spectrum information of the area, fusing two types of characteristics by adopting a kernel fusion technology, constructing a plurality of classification regression tree models for optimizing kernel fusion parameters, and establishing a classification prediction model in an optimization process, so that the discrimination accuracy of different types of seeds reaches 92%. According to the method, the hyperspectral imaging technology is utilized to obtain the sample image features and the spectral features at the same time, the multi-feature extraction and fusion technology is adopted, the random forest algorithm is combined to establish the discrimination model, and rapid and lossless discrimination of different types of seeds is achieved.

Description

technical field [0001] The invention relates to the technical field of hyperspectral images, in particular to a method for quickly distinguishing seeds of Chinese medicinal materials and grades. Background technique [0002] The quality of Chinese herbal medicine seeds is directly related to the quality and output of Chinese herbal medicines. Effective monitoring and evaluation of Chinese herbal medicine seeds is of great significance for improving the quality of Chinese herbal medicines and regulating the market. [0003] For example, Peucedanum and Fangfeng are the roots of Peucedanum chinensis and Fangfeng of Umbelliferae, respectively. They belong to the same family and belong to different genera, and their seeds are even more difficult to distinguish. At present, there is a large price gap between Peucedanum and Parsnip seeds in the market, and there is often a phenomenon of seed adulteration, so the rapid detection and identification of seeds and germplasm of Chinese m...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/00G06F18/24G06F18/253G06F18/214
Inventor 黄建华谢景张水寒陈林蔡萍刘浩钟灿何丹
Owner 湖南省中医药研究院
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com