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The timing of flowering is one of the important indexes of wheat breeding, but it is difficult to detect the flowering stage from a large number of wheat breeding materials accurately and quickly. A method to determine the flowering date of wheat based on comprehensive color features and super-pixel segmentation algorithm was proposed. Firstly, according to the light intensity and image clarity, the excess red color component of comprehensive color features, the saturation component of HSV color space and the normalized red green color component were adaptively adjusted to enhance the difference between florets and spikelets. Secondly, the clustering rules of the super-pixel segmentation algorithm were improved based on the center distance function and the gray change function to obtain the image region composed of adjacent pixels with homogeneous features. Then the image area path search algorithm was optimized to achieve accurate segmentation of each image area, and the classification of each image area was completed through grayscale and contrast indicators to achieve accurate and rapid segmentation of florets and spikelets, and the flowering period was determined according to the proportion of floret and spikelet. The experimental results showed that the average computing time of the proposed algorithm was 0.172s, the average recognition accuracy of floret was 91%, the average recognition accuracy of spikelet was 90.9%, the average error between the predicted flowering rate and the actual was only 1.16%, which met the basic requirements of determining the flowering date of wheat in the field.