In order to effectively identify the types of fruits and improve the efficiency of commercial deep processing of fruit industry and offline fruit sales channels, this paper proposes a fruit image recognition method based on the combination of semantic segmentation model （U2-Net） and ResNet-50 model to realize automatic fruit image recognition. U2-Net is used to segment the binary image of fruit, and then the white pixel value in the binary image is changed into the real color value of fruit by OpenCV algorithm. Finally, the fruit image is recognized by ResNet-50. The results show that the accuracy of Alexent, VGG16, GoogLeNet and this model on the training set is 99.66%, 99.65%, 99.9% and 99.8%, and the accuracy of the verification set is 96.5%, 99.9%, 99.6% and 100%, respectively. The result showed that the fruit image recognition method proposed in this paper can effectively extract the color, shape, texture and other features of fruits, thus realizing accurate recognition of different kinds of fruit images.

According to the corridor environment and vegetation distribution in tomato greenhouse, SLAM and navigation algorithm of robot multi‑sensor fusion are optimized. Firstly, based on the Cartographer algorithm, the dedistortion processing of LiDAR data was carried out, and then the unscented Kalman filter (UKF) was used to fuse the information of LiDAR, odometer and IMU to optimize the robot pose estimation, and the optimized algorithm was used to construct a high‑precision map of the greenhouse. The established high‑precision raster map is verified by the improved A* and DWA fusion algorithm, and the search efficiency and path safety of the A* algorithm are improved by dynamically adjusting the weights and optimizing the search logic, so that the robot can find the optimal and safe path more intelligently in the greenhouse environment, and the effectiveness of the algorithm is verified in the gazebo platform of ROS and the greenhouse environment in the field. The experimental results indicated that the average position deviation was 10.3 cm when the running speed of the robot was not more than 0.6 m/s, which met the operation requirements of the tomato greenhouse.

Leaf vegetable output in our country is huge and has the considerable economic value. At present, artificial harvesting is the main method to harvest leafy vegetables, which restricts the development of industry seriously, so it is imperative to carry out the research on mechanized leaf vegetable harvesting. In order to understand the development status of the harvesting technology and equipment for leafy vegetables at home and abroad, this paper classified leafy vegetables and non-leafy vegetables, expounded the performance characteristics, applicable environment, working principle and technical advantages and disadvantages of key components such as cutting, conveying and so on of the representative models of leaf vegetable harvesting equipment at home and abroad, and analyzed the research status of profile modeling and automatic alignment of cutting table. It is concluded that the rootcutting consistency of the cutting parts of the existing nonheading leafy vegetables under soil cutting machine in our country is poor, and the clamping and conveying device damages the leafy vegetables greatly, and the problem of the standardized planting model is not formed, finally, a series of suggestions are put forward to carry out study on the shovel cutting parts under soil, strengthen the research on the basic physical and mechanical properties of leafy vegetables, and promote the development of the whole mechanized industrial chain.

In order to protect the privacy of sensitive data of traceability companies, improve the storage performance of blockchain ledgers, and achieve safe and effective supervision of tea product quality, based on the group technology of the FISCO BCOS alliance chain, a blockchain multichain model for supervising tea traceability information was constructed, differentiated data uploading and query methods were proposed, and the inter planetary file system was used to store unstructured traceability data such as pictures and videos. In order to verify the feasibility of the model, a tea multichain traceability information supervision prototype system was developed, and the blockchain network testing tool Hyperledger Caliper and the interface testing tool Postman were used to test the blockchain network data writing query performance and application interface response performance respectively. The results show that the model divides the blockchain network into four chains such as planting and picking supervision, processing and packaging supervision, transportation and distribution supervision, and purchasing and sales supervision. The average writing operation throughput of the blockchain network built based on this model is 185 tps, and the average query operation throughput is 620 tps. The average data uploading latency of the prototype system is 1 365.00ms, the average query latency of consumers is 54.82ms, and the average query latency of regulatory agencies is 73.02ms.

In view of the problems of poor driving comfort, easy driving fatigue and low working efficiency of the domestic high‑horsepower tractor, a non‑independent suspension front axle is designed, the structural parameters are optimized and determined by simulation analysis, boundary test, response test and vibration isolation quality test. According to the boundary of suspension front axle life of 15 000 hours, tractor maximum speed of 40 km/h, maximum braking deceleration of 5 m/s², suspension capacity of ±65 mm, combined with theoretical analysis and empirical design, the stiffness value of the suspension front axle is initially determined to be 310-980 N/mm, and the corresponding undamped natural frequency range is less than 2.0 Hz. The damping coefficient range is 0.2-0.7 s-1. When the mode is switched, the position adjustment time is 6-30 s, and the pressure relief time is less than 30 s. The results of simulation analysis and boundary test show that the suspension front axle meets the life requirement of 15 000 hours, the maximum speed of 40 km/h and the maximum braking deceleration of 5 m/s². After the response test and optimization, the position adjustment time is 3.57-14.71 s and the pressure relief time is less than 16.69 s when the mode is switched. The vibration isolation quality test shows that the undamped natural frequency is less than1.8 Hz, and the damping coefficient is 0.45-0.56 s-1.

Compared with the lack of work efficiency of a single agricultural robot, it is difficult to effectively solve the problems of reducing the supply of agricultural labor and increasing labor costs, the multi‑robot collaborative technology with  intelligent, high‑precision, low‑cost, strong robustness and high anti‑interference ability can significantly improve the operation efficiency of the overall robot system and meet the development needs of precision agriculture. From the perspective of agricultural multi‑robot system architecture, this paper reviews the representative research results of four collaborative technologies of agricultural multi‑robot positioning, task allocation, path planning and multi‑robot communication in recent years, and analyzes the operation efficiency, communication damage, fault monitoring, resource conflict and other issues of agricultural multi‑robot collaboration. The future development of key directions such as centralized and distributed collaborative technology, fast and accurate environmental perception, reasonable real‑time task allocation, dynamic and reliable path planning and multi‑robot communication technology is prospected.

The improvement of the total factor productivity is an important part of the high‑quality development of agricultural enterprises, which has attracted much attention from the corporate and academic circles. Taking Chinese listed agricultural companies from 2008 to 2021 as research samples, this paper empirically tests the enabling effect of digital transformation on the improvement of the total factor productivity of agricultural enterprises and the intermediary effect of corporate human capital in them, and conducts heterogeneity analysis based on firm attributes and location characteristics. Studies have found that the coefficient of digital transformation degree is 0.178 5, which is significant at the 1% significant level, indicating that digital transformation can significantly promote the improvement of the total factor productivity of agricultural enterprises, after adding the intermediary variable of human capital, the regression coefficient of digital transformation has dropped from 0.178 5 to 0.164 9, indicating that human capital can play an intermediary effect in the process of digital transformation to promote the improvement of agricultural enterprises, that is, digital transformation can promote the optimization of the human capital structure of agricultural enterprises to improve the total factor productivity level, digital transformation has a more obvious effect on the improvement of agricultural enterprises' total factor productivity in non‑state‑owned enterprises, large enterprises and east enterprises.

As the core component of the seeder, the performance of the seeder determines the quality of sowing. In order to meet the research and development needs of precision seed metering technology in China, the research status, seed metering technology and driving technology of precision seed metering technology at home and abroad were analyzed in detail. Although the pneumatic seed metering device is suitable for high‑speed operation, it has high requirements for the sealing and wear resistance of the system. In complex field operation, the air pressure may be unstable, resulting in the decline of seeding quality. The traditional mechanical seed metering device still plays a leading role in China’s modern seeding operation because of its simple structure and low cost. However, with the continuous growth of the demand for intelligent seeding technology, the traditional mechanical seed metering device has problems such as the decline of seeding performance, the difficulty of maintaining the uniformity of plant spacing and poor adaptability under the conditions of high‑speed seeding operation and different planting modes in different regions. At the same time, under high‑speed operation, the ground wheel may slip, resulting in the failure of the seed metering device driven by the ground wheel to work normally and the phenomenon of missing seeding. However, the current electric drive technology can ensure the smooth progress of seed metering even if the slip phenomenon occurs with the support of the navigation system. However, due to the incompleteness of the evaluation criteria for the sowing quality of the electric driven seed metering device, the market has not been popularized. Therefore, in view of the above problems, we should vigorously strengthen the research on the precision seeder technology, make the continuous improvement of the seeder technology to meet the market demand, replace the traditional seeder technology, promote the application of related products in agricultural production, and provide a new idea for the development of the subsequent modern intelligent seeder.

Fruit picking robot is of great significance to realize automatic fruit picking, and vision system is the key to the research of fruit picking robot. Therefore, the research work on the key technologies of vision system of picking robot at home and abroad in recent years is summarized. According to the technical route of the picking vision system, the image acquisition technology of the picking vision system is discussed. This paper summarizes the common target recognition algorithms in the field of fruit target recognition, including singlestage algorithm, twostage algorithm, semantic segmentation and instance segmentation algorithms based on deep learning and their improvements, and summarizes the application of recognition technology in complex environment. The hardware system and software algorithm of fruit target location are summarized based on the method of picking point acquisition. Finally, the paper discusses the limitations of the picking vision system in algorithm, hardware and applicable environment, and proposes that the future research should focus on multiinformation fusion, deep learning technology and vision system in complex environment, so as to provide reference and guidance value for the research of fruit picking robots.

Agricultural socialization service is an important means to realize the modernization of agriculture, rural areas and farmers, and also an important way to realize the effective connection between rural revitalization and common prosperity. In order to objectively grasp the development context and future development trend of the research on agricultural socialization service in China, this paper selects 649 literatures in the field of agricultural socialization service from 1992 to the first half of 2023 through the database of China National Knowledge Network (CNKI), and draws a visualization map with CiteSpace software to summarize the research hotspots and knowledge progress. The results show that the research on agricultural socialization service can be divided into two periodssuch as the exploration period and the development period. The core author group is weak, the cooperation spirit between scholars and research institutions is lacking, and no significant “team effect” has been formed. Research hotspots mainly focus on agricultural socialization service itself, land transfer, rural revitalization, and the effective connection between small farmers and agricultural modernization. From the perspective of the overall research trend, the effective connection operation mechanism of rural revitalization, agricultural modernization and agricultural socialization service will become the key follow‑up research areas. Therefore, scholars should strengthen cooperation and exchanges with institutions, and devote themselves to building a more comprehensive theoretical system for the study of agricultural socialization service, so as to provide effective reference for the subsequent development of agricultural socialization service on the basis of enriching research perspectives.