A rapid detection and sorting system for seed maturity

To solve the problems of low speed and low efficiency of seed sorting, this study designs an efficient seed separation method. In this method, a vibrator is used to scatter the seeds and make them fall rapidly through parallel multi-tracks. The seeds are irradiated by a light source with a wavelength of 670 nm after passing through the identification area. The high-speed linear array camera takes photos of the irradiated seeds. The convolution neural network algorithm combining residual learning and attention mechanism is used to analyze and judge the maturity of the seeds. The algorithm model can effectively capture the characteristics of the seed photos and conduct efficient processing analysis and judgment, Finally, the low maturity seeds are blown away by an air compressor and blower to achieve rapid and efficient seed sorting. The test shows that the sorting speed can reach 50 particles/s and above, and the sorting accuracy can reach 96%.