Tobacco maturity detection method and device
A technology of tobacco leaf maturity and detection method, which is applied in the direction of measuring device, color/spectral characteristic measurement, and material analysis through optical means, which can solve the problems of lack of accuracy of judgment, lack of practicability, and inability to judge the maturity of tobacco leaves in real time, etc. , to achieve intuitive judgment, reduce the impact on the model, and improve the accuracy
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment 1
[0032] Embodiment 1 A kind of tobacco leaf maturity detection method, the steps are as follows:
[0033] (1) Observe and record the phyllotaxy (phyllotaxy) of the tobacco leaves to be tested, reflecting the planting position of the leaves;
[0034] (2) Obtain the JPG format image of the tobacco leaves to be detected with the camera, process the image to establish an image in HSV color mode, and obtain the H and S color component values of the image (can be input into the computer to obtain through MATLAB software);
[0035] (3) Divide the maturity grade MD of the tobacco leaves to be tested according to the following formula,
[0036]
[0037]
[0038] In the formula, MD-maturity grade, H / S-ratio of H to S in the HSV color model of tobacco leaf image, f-coefficient, PHY-bottom-to-top phyllotaxy of harvestable tobacco leaves (phvllolaxy).
Embodiment 2
[0039] Example 2 Correlation verification with colorimetric identification method
[0040] In 2006, K 326 tobacco leaves were collected in the Science and Education Park of Henan Agricultural University, and 50 tobacco leaf samples were collected. The grades were determined by experienced technicians according to the colorimetric identification method, and the maturity grades M0-M4 were collected (see Table 1 for grade classification) Each sample was 10; images were taken of these tobacco leaves at the same time, and the method described in Example 1 was used to determine its maturity. The results obtained by the two methods are shown in Table 2. Then, the correlation test was carried out between the maturity level calculated by the model and the level judged by the colorimetric identification method, and the results were as follows: figure 1 shown.
[0041] Table 1 Tobacco leaf maturity classification standard
[0042] maturity level mature features Leaf (M...
Embodiment 3
[0045] Example 3 Correlation Verification with Chemical Composition Analysis
[0046] In 2007, 80 tobacco leaf samples were randomly collected from the K 326 tobacco leaves collected in the Science and Education Park of Henan Agricultural University, and their grades were determined using the tobacco leaf chemical composition analysis method; at the same time, images were taken of these tobacco leaves, and the method described in Example 1 was used to determine The maturity, the results obtained by the two methods are shown in Table 3. Then the maturity grade determined by the inventive method and the grade judged by tobacco leaf chemical composition analysis method are carried out correlation test, and its result is as follows figure 2 shown.
[0047] Table 3 Chemical composition analysis method of the present invention determines the comparison of maturity grade results
[0048]
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
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