Design and implementation of anti-leakage planting system for transplanting machine based on fuzzy information

Abstract Selective operation of potted seedlings on transplanter is the fundamental way to improve the survive rate after the transplanting operation. However, due to the problems of high transplanting speed and complicated working condition of the transplanter, higher requirements for information detection, mechanism control and their coordination are needed. In this paper, the Fuzzy C-means (FCM) method is used to detect the image information of potted seedlings with high throughput. Segmentation of seedling individuals and recognition of seedlings vacancy were realized. An automatic transplanting machine is designed to verify the reliability of the proposed on-line FCM method. The proposed algorithm is implemented in VB and MATLAB, and is used to control the automatic transplanting machine. The algorithm can effectively identify the status of the seedling during the transplanting process. The test results show that when the speed of seedling delivery was 70 plants per minute, the rate of leakage planting was 1.08%, and the accuracy of seedling identification was 97.33%. The monitoring system designed in this paper can realize the vacancy detection of potted seedlings. With the use of information detection by FCM, the leakage rate of automatic transplanting machine can be reduced significantly.