| In order to meet the planting needs of wheat drill and direct seeding in the dry hole of rice in the rice and wheat rotation area of northern Jiangsu province, and to solve the problems of uneven sowing and poor utilization of both rice and wheat for the outer groove seed metering, a spiral trough seed metering was designed for both rice and wheat. The main working parts of the seed metering are the handwheel, the sowing quantity regulating mechanism and the seed metering wheel. By rotating the handwheel, the sowing quantity regulating mechanism is pushed to change the working length of the seed metering wheel, and then the size of the seed metering wheel groove is controlled to realize the dual use of rice and wheat under different sowing quantity conditions. The key structural parameters such as the spiral angle range, the diameter and height of the seed row groove and the diameter of the seed row wheel were determined. Wheat was selected as experiment to obtain the optimal helical angle of seed metering, which is determined as 30°. Under the optimum helical angle, rice and wheat seeding performance tests were carried out with the rotation speed and the working length as variables. The results showed that the optimum speed of sowing wheat was 34.93 r/min, and the optimum working length was 1.28 cm. The optimal speed of sowing rice was 35 r/min, and the optimal working length was 0.6 cm. A wheat displacement prediction model was constructed, with a determination coefficient R2 of 0.987. The applicability of the planter was verified for the sowing wheat of Ningmai 13, Sumai 11 and rice of Nanjing 46 and Suxiu 867. The results showed that the fragmentation rate of sowing wheat was 0.24% and 0.27%, the coefficient of variation was 1.71% and 1.66%, and the deviation between the sowing quantity and the predicted value was 7.14% and 7.78%, respectively. The eligible indexes of sowing rice were 92.40% and 91.73%, the unsown indexes were 3.73% and 4.26%, the replay indexes were 3.87% and 4.01%, and the coefficient of variation was 3.11% and 3.84%, respectively.