As the largest fruit producer in the world, China’s comprehensive orchard mechanization rate is below 30% and faces the problem of aging orchard farmers. Thinning is an essential agronomic practice in orchard management. Therefore, to get a marketable product, artificial hand fruit thinning (AHFT) has become a major but costly management practice in modern orchard planting. The authors developed two types of new orchard blossom thinners: a tractor-mounted three-arm blossom thinner (TTBT) and a hand-held electric blossom thinner (HEBT). The arm shape, spindle rotation speed, and rope arrangement density of TTBT can be adjusted flexibly according to the canopy structure of the fruit tree. HEBT is portable and suitable for different canopy types, especially for traditional orchards with a complex-structured canopy. In this paper, a performance evaluation of the two types of blossom thinners on Y-trellis ‘Sucui’ No.1 pear orchard was carried out. In field tests, three treatments were designed and tested, which are TTBT combined with AHFT, HEBT combined with AHFT, and AHFT only. Four indices were used to evaluate the tests: blossom retention rate, fruit setting rate, fruit yield and quality, and work efficiency and cost. The test results showed that the blossom retention rate of TTBT and HEBT at 50% for Y-trellis ‘Sucui’ No.1 pear orchard was perfect; the difference in blossom retention rate and coefficient of variation of every layer of TTBT was very small, and the mean coefficient of variation was 2.97%, which is 1.98% lower than that of HEBT, meaning that the working stability of TTBT was higher than HEBT. The working efficiencies of TTBT and HEBT were much higher than that of AHFT, specifically, 130 and seven times higher, respectively. Although mechanical blossom thinning reduces the fruit setting rate to a certain extent, it has no effect on fruit yield and quality after fruit thinning for final marketable fruit. The profitable areas of TTBT and HEBT were 0.87 hm² and 0.08 hm², respectively.

To solve the problem of effective utilization of orchard green fertilizer, a small one-rotor orchard horizontal rotary rake (OHRR) was developed, which is used for grass collection in the mowing agronomic section of orchard management. In the working process, the disc drives the arms rotating around the vertical shaft, the guide cam that is fixed to the vertical shaft controls tine movement, and the tines turn to different inclination angles in different positions. The kinematic validation model of OHRR was built based on the theory that there is no gap or small overlap between the two adjacent working areas of the tines. This model determines the relationship between the advancing speed, disc rotational speed, rotation radius, arm number, and tine working width. The leakage and repeating rate of OHRR virtual prototype were calculated by tines movement trajectories analysis in multi-body dynamics simulation. Box-Behnken three-factor and three-level test plans for advancing speed, disc rotational speed, and tine working width were designed to obtain the optimal operation parameters of the OHRR: advancing speed was 11.16 km/h, disc rotational speed was 6.98 rad/s, and tines working width was 0.3 m. Taking labor working as the control group, OHRR field tests were evaluated by four indices: strip density, leakage rate, working efficiency, and profitable area. Field tests results showed that the leakage rate of OHRR was 4.56%, which meets the requirements of national standard JB/T10905. The strip density, width, and height of OHRR were 29.44 kg/m³, 0.5 m, and 0.25 m, respectively. These data can provide support for the subsequent loading and transportation operation. The profitable area of OHRR was 6.7 hm², which is suitable for large-scale mechanized orchard management.

With the rapid advancement of modern agriculture, mechanized and intelligent pollination has emerged as a crucial focus for enhancing agricultural efficiency and minimizing labor expenses. Traditional pollination methods, limited by environmental factors and high labor costs, fail to adequately address the production demands of large-scale orchards and vegetable gardens. Consequently, researchers have integrated mechanized equipment, drone technology, robotics, and deep learning algorithms to achieve accurate identification and precise pollination on inflorescences. The research on mechanized and intelligent pollination has not only injected new momentum into the field of fruit and vegetable pollination but also provided key technological support for addressing global agricultural labor shortages and increasing crop yields. This review summarizes recent advances in mechanized and intelligent pollination, focusing on deep learning’s role in object recognition, improvements in pollination equipment, and the effectiveness of intelligent pollination across various fruits or vegetables. Studies indicate that mechanized and intelligent pollination significantly enhances working efficiency and fruit yields, though it continues to face challenges such as technical complexity and high implementation costs. Looking ahead, as robotics and artificial intelligence algorithms continue to advance, mechanized and intelligent pollination is poised for broader adoption in agricultural management practices. This review systematically summarizes the research progress in mechanized and intelligent pollination technologies for fruit and vegetable crops, providing significant theoretical support and reference value for future studies in crop pollination techniques.