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Quantitative determination method for chlorophyll of green vegetable leaves based on computer image analysis

A quantitative detection method and image analysis technology, applied in image analysis, calculation, image enhancement and other directions, can solve the problems of unsuitable green leaf chlorophyll content, large volume of color difference meter, expensive instrument, etc. Flexible and simple, high-precision effects

Active Publication Date: 2016-06-08
ZHEJIANG UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Because the color difference meter has certain requirements on the size, shape, color uniformity, and surface smoothness of the sample, and the color difference meter is large in size and expensive, it is suitable for scientific research but not for grassroots research and production units.
b. The current chlorophyll content detection models are mostly based on RGB and other color systems, and the prediction accuracy is not high
c. The use of computer images to establish chlorophyll content reported in the literature is mostly based on the detection model of cotton and other crops. Because green vegetables are quite different from the above-mentioned crops in terms of plant type, leaf shape, and surface structure, there are already prediction models for chlorophyll content. Not suitable for the determination of chlorophyll content in green vegetable leaves

Method used

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  • Quantitative determination method for chlorophyll of green vegetable leaves based on computer image analysis
  • Quantitative determination method for chlorophyll of green vegetable leaves based on computer image analysis
  • Quantitative determination method for chlorophyll of green vegetable leaves based on computer image analysis

Examples

Experimental program
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Effect test

Embodiment 1

[0024] At 10:30 on October 10, 2015, 10 groups of green vegetable leaf samples purchased at the Desheng Road Farmer’s Market in Xiacheng District, Hangzhou City, Zhejiang Province were taken. When the camera shoots the front image of the green vegetable leaves, put the green vegetable leaves to be tested in the dark box with white paper as the background, place the digital camera on the observation hole above the dark box, turn on the standard light source (D65) of the dark box, and set the flashlight of the digital camera to off , the pixel is 5 million, set the camera in M ​​mode, and the shooting parameters are 1 / 400, F8.0, ISO100. The white balance is automatic, and the focal length of the lens is adjusted to 20cm. The photo was taken under clear and cloudless weather conditions, the camera was taken perpendicular to the leaves, and there were no shadows on the leaves. The image was stored in JPG format and transferred to the computer, and the acquired digital image of th...

Embodiment 2

[0029]At 10:30 on October 15, 2015, 10 groups of green vegetable leaf samples were taken. The green vegetable variety was "Ai Kang Qing". In the background, the digital camera is placed on the observation hole above the obscura, the standard light source (D65) of the obscura is turned on, the flash of the digital camera is set to off, the pixel is 5 million, the camera is set in M ​​mode, and the shooting parameters are 1 / 400. F8.0, ISO100. The white balance is automatic, and the focal length of the lens is adjusted to 20cm. The photo was taken under clear and cloudless weather conditions, the camera was taken perpendicular to the leaves, and there were no shadows on the leaves. The image was stored in JPG format and transferred to the computer, and the acquired digital image of the leaf was used to make a leaf selection (excluding the stem veins on the leaf) with the magic wand tool in Adobe Photoshop CS6 image processing software, and the size of the pen tip was set to 8 pi...

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Abstract

The invention provides a quantitative determination method for chlorophyll of green vegetable leaves based on computer image analysis. The quantitative determination method comprises the following steps: causing color change of the leaves according to content change of the chlorophyll of the green vegetable leaves; acquiring green vegetable leaf images by adopting a digital camera or a scanner, and acquiring color parameter values (L, a, b and deltaE) of the leaves in the images by adopting a computer image technology; determining the content of the chlorophyll of the corresponding leaves by adopting a traditional spectrophotometer method; fitting a relation between color parameter values of the leaves and the content of the chlorophyll by adopting different function models so as to construct a chlorophyll content predication model based on the color parameter values, wherein the determination of the chlorophyll content of the leaves can be realized only if the color values of the leaves are acquired and then are input into the model.

Description

technical field [0001] The invention relates to a method for quantitatively detecting chlorophyll content in green vegetable leaves, which belongs to a method for testing physiological indexes of crops. Background technique [0002] At present, the commonly used method for measuring chlorophyll content is the spectrophotometer method, that is, weighing and cutting the leaves, extracting the chlorophyll of the leaves with a large amount of organic solvents such as acetone and ethanol for a long time, and then measuring the optical density values ​​of the extract at 645nm and 663nm with a spectrophotometer , and then use the Arnon formula to calculate the chlorophyll content. [0003] Another method is to use a chlorophyll meter to measure the leaves and directly read the value of the leaf chlorophyll content. The most used is SPAR-502 produced by Minolta Corporation of Japan. It is based on the characteristics that leaf chlorophyll has absorption valleys and reflection peaks...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/31G06T7/00G06T7/40
CPCG01N21/31G01N2021/3155G06T7/0012G06T2207/10004G06T2207/10024G06T2207/30004
Inventor 王德海孙宇露朱国建
Owner ZHEJIANG UNIV OF TECH
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