Estimation of peanut seedling emergence rate of based on UAV visible light image

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Abstract
Seedling emergence rate is one of the important factors affecting crops yield. In this paper, the estimation method of peanut seedling emergence rate based on UAV visible light image was proposed to improve the timeliness and accuracy of peanut seedling emergence rate information acquisition. Firstly, obtained high resolution remote sensing images of June 25, 2021 and July 3, 2021 by self-built low altitude unmanned aerial vehicle platform at summer sowing peanut seedling stage, and the number of peanut plants was identified and counted by combining HSV and Otsu adaptive threshold method. Then, combined with visual interpretation data, linear regression was used to establish a linear relationship model between visual interpretation and computer automatic extraction of peanut plant number. Finally, the information of peanut emergence rate was extracted based on this model to evaluate the sowing effect and quality. The results showed that the correlation coefficient R2 between computer automatic identification of plant number and artificial visual interpretation of plant number was more than 0.85 in two periods. The overall accuracy of peanut plant number extraction was higher than 95 %, and the average relative errors of seedling rate estimation in two stages were 6.0 % and 0.4 %, respectively. The monitoring accuracy of UAV in the middle and late stages of seedling was better than that in the early stage of seedling, which was suitable for peanut seedling rate monitoring. The emergence rate of narrow high ridge sowing was better than wide high ridge sowing. This paper quantitatively analyzed the sowing effect and quality of wide high ridge planting and narrow high ridge planting, and provided technical support for fine management of peanut industrial park.