中文摘要：

利用JSP-12排种器性能检测试验台，分别检测2BQ系列玉米播种机的气吸式排种器播种杜玉一号、龙单38、先玉335和鑫鑫6号玉米种子的合格率，利用回归预测模型与BP神经网络模型进行拟合预测。结果表明：在播种机前进速度为6．0～12km／h时，气吸式排种器播种4个品种玉米种子的播种合格率分别为86％～96％、71％～94％、79％～92％、78％～96％；BP神经网络模型对气吸式玉米排种器合格率有较好的拟合能力。

英文摘要：

Qualified rate of the air suction seed metering device of 2BQ series corn seeder in seeding Duyul, Longdan38, Xianyu335 and Xinxin6 was tested by using JSP-12 metering device. Regression prediction model and the BP neural network model was used to forecast the gas suction qualified rate of corn seed metering device. The results show that in the speed of 6.0-12 km/h, sowing Duyul the percent of pass is 86%-96% of seed, Longdan38 the percent of pass is 71%-94%, Xianyu335 the percent of pass is 79%-92% of seed, Xinxin6 the percent of pass is 78%-96%. The BP neural network model for gas suction qualified rate of corn seed metering device has good fitting capability and relatively high prediction accuracy.