The mechanized sowing operation of corn breeding can improve test accuracy and efficiency and speed up the test process. In view of the problems of low flexibility, high price, and poor sowing quality of the current seeder in corn breeding experiments, the critical components of a hand-pushing corn plot precision planter were optimized. Through the analysis of the relative motion between corn seed and the hole seed-metering wheel, the hole diameter range and hole depth range of the hole seed-metering wheel were determined as 13~19 mm and 6~12 mm, respectively. The chamber structure was optimized to improve the seed filling performance under the condition of a small number of seeds. The angle range between the connecting plate and the horizontal line (ACP) and the angle range between the back plate and the horizontal line (ABP) were 35~55° and 40~70°, respectively. EDEM was used to simulate the seeding circumstances of hole seed-metering wheel with different holes sizes. The optimal combination of hole diameter and depth under different seeds’ sizes and the appropriate angle combination of ACP and ABP were obtained through the orthogonal test. The results of the simulation experiment showed that the optimal hole diameter–depth combinations of the small, medium, and large corn seeds were 13–8, 15–10, and 17–8 mm, respectively. The angle ACP and the angle ABP were, respectively, 45°and 70°. The soil bin test was carried out to further verify the actual seeding effect and the influence of the rotating speed of hole seed-metering wheel on seeding. The results showed that when the rotating speed of hole seed-metering wheel was less than 16.0 r/min, the qualified seeding rates and the double seeds rates of the small, medium, and large corn seeds were higher than 90% and 85%, respectively. The missing seeding rates were 0%. The variation coefficients of plant spacing were less than 5%, indicating good stability of plant spacing, which met the design requirements. The study results can provide a theoretical reference for the optimization design of maize breeding equipment in a plot.

The accuracy and real-time performance of the speed measurement method were important factors influencing the accuracy of the seeding spacing monitoring. In this study, three different speed measurement methods (including GNSS (Global Navigation Satellite System) receiver speed measurement, radar speed measurement, and encoder measurement rotation speed) were used to compare and analyze the monitoring results of seeding spacing. The same monitoring system was used to calculate the seeding spacing under three different speed measurement methods. The encoder directly measured the rotation speed of the seeding disc instead of the traditional method of measuring the rotation speed of the driving wheel. The monitoring results of uniform-speed and variable-speed seeding field tests showed that the three speed measurement methods have extremely high correlations, with a correlation coefficient R > 0.95. There was small difference among the three speed measurement methods, and they all met the needs of field seeding operations. After comprehensively considering the use cost and installation complexity, it was recommended to use GNSS receiver speed measurement to monitor the speed of the seeding operation and the real-time seeding spacing.

To avoid issues such as the greenhouse working robot’s inability to perform normal tasks or reduced working accuracy due to the influence of uneven ground, this study designed a set of greenhouse self-balancing mobile robots. The self-balancing mobile robot system designed in this study uses a quadruped mobile robot as a carrier, equipped with a three-degrees-of-freedom wheel-leg structure and is complemented with a posture control algorithm. The algorithm calculates the adjustment of each leg based on the vehicle’s tilt angle and wheel-ground pressure, achieving control over the robot’s posture angle, the center of gravity height, wheel-ground contact force, and other functions. To address the issue of over-constrained (weak legs) posture adjustment during mobile robot fieldwork, a flexible joint sensor based on the PR structure has been designed and developed. After field testing, it was verified that the greenhouse self-balancing mobile robot proposed in this study can adapt well to field environments, such as climbing hills, overcoming obstacles, crossing furrows, and so on. The response speed of the flexible joint sensor can meet the requirements of self-balancing while effectively solving the problem of weak legs.

Haploid breeding can shorten the breeding period of new maize varieties and is an important means to increase maize yield. In the breeding program, a large number of haploid seeds need to be screened, and this step is mainly achieved manually, which hinders the industrialization of haploid maize breeding. This article aims to develop a multispectral camera to identify the haploid seeds automatically. The camera was manufactured by replacing narrow-band filters of the ordinary CCD camera, and the RGB, 405 nm, 980 nm and 1050 nm images of haploid or diploid seeds were simultaneously captured (the characteristic wavelengths were determined according to color and high-oil markers of maize). The performance was tested using four maize varieties with the two genetic markers. The results show that the developed multispectral camera significantly improved the recognition accuracy of haploid maize seeds to 92.33%, 97.33%, 97% and 93.33% for the TYD1903, TYD1904, TYD1907 and TYD1908 varieties, respectively. The cameras in the near-infrared region (wavelengths of 980 nm and 1050 nm) achieved better performance for the varieties of high-oil marker, with an increase of 0.84% and 1.5%, respectively. These results demonstrate the strong potential of the multispectral imaging technology in the haploid seed identification of maize.