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

A method for predicting the content of ferulic acid in Lycium barbarum based on hyperspectral imaging technology

A technology of hyperspectral imaging and technical prediction, which is applied in the field of quality identification of Chinese medicinal materials, can solve the problems of complex chemical inspection operation methods, time-consuming and laborious, large empirical identification errors, and strong subjectivity, so as to facilitate market circulation monitoring and improve accuracy Scientific and cost-reducing effect

Active Publication Date: 2020-08-25
北京中研百草检测认证有限公司
View PDF2 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The empirical identification error is relatively large, the subjectivity is strong, and the operation method of chemical inspection is complicated, time-consuming and laborious

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
  • A method for predicting the content of ferulic acid in Lycium barbarum based on hyperspectral imaging technology
  • A method for predicting the content of ferulic acid in Lycium barbarum based on hyperspectral imaging technology
  • A method for predicting the content of ferulic acid in Lycium barbarum based on hyperspectral imaging technology

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0048] This embodiment provides a method for establishing a model based on hyperspectral imaging technology to predict the content of ferulic acid in Fructus Lycium barbarum and a method for determining the content of ferulic acid in Fructus Lycium barbarum, including the following steps:

[0049] 1) Take 6 samples, take 75 capsules for each sample and divide them into 5 groups randomly, place them on the mobile platform, and try not to exceed the scope of the lens. When placing goji berries, highlight the characteristics of each particle, place each group in a row, and place the whiteboard for black and white correction 5cm behind the sample. Wait for the instrument to connect and self-test. Set the scanning parameters of the hyperspectral imager, the lens distance is 30cm, and the platform moving speed is 1.5mm / s. Set the integration time of the 400-1000nm lens to 4350μs and the frame time to 22000. The integration time of the 1000-2400nm lens is 4000μs and the frame time t...

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 method for predicting ferulic acid content of barbary wolfberry fruit based on a hyperspectral imaging technology. The method comprises the following steps: 1) performing spectrum scanning on a sample with a high-spectrum imaging system, and collecting high-spectrum data of 400 to 1000 nm and 1000 to 2400 nm; 2) performing RAD (Radiometric calibration)on the original high-spectrum data in sequence, converting the high-spectrum data into relative reflection rate data by adopting a flat field processing method, processing the relative reflection rate data with a multiplicative scatter correction method, and performing principal component analysis dimensionality reduction; performing principal component analysis on effective wave bands to obtain main spectrum information; 3) modeling the main spectrum information and ferulic acid content with principal component regression to obtain a prediction model of the ferulic acid content of barbary wolfberry fruit; 4) processing the sample to be tested according to the steps 1) and 2), inputting the obtained main spectrum information into the prediction model, and calculating the ferulic acid content of the sample tobe tested.

Description

technical field [0001] The invention belongs to the field of quality identification of traditional Chinese medicinal materials, and in particular relates to a method for predicting ferulic acid content in wolfberry fruit based on hyperspectral imaging technology. Background technique [0002] Lycium barbarum resources are widely distributed in my country and there are many varieties. According to the description of "Flora of China", there are 7 species and 3 varieties of Lycium barbarum in my country. They are native to northern my country, such as northern Hebei, Inner Mongolia, northern Shanxi, northern Shaanxi, Gansu, Ningxia, and Qinghai. , Xinjiang has wild, because the fruit is used as medicine and gradually practice cultivation, now mostly based on cultivation. After many researches, Ningxia has been positioned as the authentic production area of ​​medicinal wolfberry. However, due to the rich variety, many production areas, and the influence of many environmental fac...

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
Patent Type & Authority Patents(China)
IPC IPC(8): G01N21/31
CPCG01N21/31
Inventor 张小波郭亮
Owner 北京中研百草检测认证有限公司
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