The invention discloses a chrysanthemum salt tolerance high-
throughput identification method which comprises the following steps: selecting a plurality of chrysanthemum
germplasm resources, setting
sodium chloride solutions with different concentrations to carry out salt stress treatment, and carrying out
dimensionality reduction calculation on a plurality of salt tolerance related characters through a
principal component analysis method to obtain a comprehensive salt tolerance D value; after the salt stress
phenotype appears, RGB images of each
plant at four side view angles and one overlook angle are collected, and image
color calibration and standardized naming are carried out; segmenting the image in an excessive green and HSV
color space to obtain a
plant binary image, extracting morphological and textural digital characteristic parameters, and analyzing the reliability of the characteristic parameters by using a
linear regression model; adopting independent sample t test, variability analysis, feature importance analysis and generalized
heritability analysis to screen representative features which are significant in salt stress response and stable in
heredity from the digital feature parameters; the screened representative features are divided into a plurality of feature subsets, and a
random forest algorithm is adopted to
train a salt tolerance prediction model with the representative features as independent variables and salt tolerance D values as dependent variables; on the basis of a salt tolerance prediction model, evaluating the importance of each feature, screening out an optimal
feature combination with the minimum prediction error, and performing salt tolerance grade automatic division on the chrysanthemum
germplasm resources; according to the invention, lossless dynamic measurement of plants can be realized.