Detection Precision of Seedmeter for Large-granule Seeds

A detecting method based on machine vision was put forward to test the performance of seedmeter with corn and soybean seeds as test samples, in which MATLAB software was applied to process image data and analyze the results. The experimental results showed that the mean value of absolute error of the sowing speed for soybean was 0.004-0.68 seed · s−1; the mean value of relative error was from 6.5% to 130%, and there were no significant differences of mean value, standard deviation and coefficient of variation of flowing seeds between manual statistics and MATLAB statistics. The machine vision method was proved to be time-saving, labor-saving and no-touching in the seedmeter precision detecting.