Method for detecting profile phenotype of arabidopsis

Abstract

Provided is a method for detecting a profile phenotype of arabidopsis. The method includes the steps that a calibration board is placed in a planting pot of the arabidopsis, an RGB image of the arabidopsis is collected through a camera, the collecting image is preprocessed, automatic correction and calibration of the image are achieved, image correction is used for correcting deformation of the image, image calibration is used for obtaining a real size of a unit pixel, the preprocessed image is divided, the arabidopsis is separated from the background and extracted from the image, after the arabidopsis image is separated, a profile phenotype parameter of the arabidopsis is extracted, and an overall profile of the arabidosis is quantitatively described through an oval Fourier descriptor. The differences of the overall profile and growth orientation of the arabidopsis with different genes can be described through analysis of the profile phenotype parameters, and accordingly the function of different genes and influences of the different genes on the arabidopsis can be concluded.

Description

technical field [0001] The invention relates to a method for detecting the outline phenotype of Arabidopsis thaliana, which uses a camera to collect pictures of Arabidopsis thaliana, uses an image processing method to extract the profile phenotype parameters of Arabidopsis thaliana, and realizes the non-destructive detection of the growth process of Arabidopsis thaliana . Background technique [0002] Arabidopsis is an important model plant in botany, genetics and genetics. The research on Arabidopsis phenotype can comprehensively and thoroughly clarify the physiological function of Arabidopsis thaliana, especially the relationship between its phenotype and its genes, and the influence of different environmental conditions on its growth. The detection methods of plant phenotypic characteristics include destructive measurement, contact measurement and computer vision detection methods. Destructive measurement is to randomly select a certain number of plants for a batch of p...

AI Technical Summary

Problems solved by technology

[0004] 1. The use of destructive measurement methods will cause damage to plants, and the continuous measurement of plant growth cannot be performed

[0005] 2. The use of sensors for measurement and direct contact with plants will have a certain impact on the growth of plants, and its cost is high, and its development is relatively difficult

[0006] 3. The existing computer vision technology mainly focuses on the phenotype detection of a single leaf or other crops, while the phenotype detection of Arabidopsis mainly relies on manual implementation, which has a large workload and low efficiency

[0007] At present, there are few literature reports on computer vision detection of Arabidopsis phenotypes at home and abroad.

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