*2.5. Apple Flowering Monitoring*

In this experiment, the trained model was applied to 1494 images of apple trees taken at different times to detect flowers at different stages. The prediction of each apple tree image using S-YOLO-s to obtain the boxes corresponding to the four stages of flowers in each image and accumulating the number of boxes in the same category in all images on the same date obtained the total number of flowers in the four stages. On this basis, the total number of apple blossoms at each stage was divided by the number of images to obtain the average number of flowers at each stage in each image.

It is possible to determine the relative number share by evaluating the proportional relationships between the various stages of flowers within a single image. When the percentage of flowers at a particular stage in an image surpasses fifty percent, the fruit tree is deemed at the corresponding flowering stage. The day with the highest number of apple blossoms at a particular stage of the growth cycle is the peak time for apple blossoms at that stage. Among all images of fruit trees under a specific date, the average number of flowers in the four stages can be used to determine the flower proportion, and thus, the overall flowering status of the orchard. The percentages of fully open flowers correspond to the flowering intensities from 0 to 100, and this precise quantitative index will provide data support for flower-thinning decisions.
