The transformation and upgrading of traditional agriculture are required to address its shortcomings and deficiencies, which have resulted in environmental pollution or water problems. Precision agriculture emerged at the historic moment to solve the current problems. Field information collection, information management and decision-making, and execution systems are the three key links of precision fertilization and irrigation. The technical principle and application of field information acquisition systems are analyzed. The information management and decision-making system describes the management and summary of information in crop growth. The execution system combines the knowledge of various disciplines and experts for targeted applications to specific crops. It further focuses on the core implementation system, that is, variable fertilization technology and variable spraying technology that can realize variable operations. Major contributions from different countries, institutions, corresponding authors, and journals are presented in detail. This study proposes several suggestions and ideas based on the research status and progress of the three key systems to provide a theoretical basis and technical support for the research and development of key technologies and innovative devices of precision agricultural fertilization and irrigation.

Corn is a crucial crop and has a vital application value in many aspects of our lives. Mechanical grain harvesting is the developing direction of corn harvesting technology, with corn threshing as its most imperative procedure. The quality of the threshing device of the corn harvester has a major influence on its damage rate, loss rate, and other parameters. Therefore, it is of great significance to effectively lower the damage rate in the process of corn threshing. This review presents the research progress and the application status of corn threshing technology and corn threshing machinery. The conclusions and suggestions on low-damage corn threshing technology and corn threshing machinery are summarized to provide a reference for the reduction in the damage rate of mechanical grain harvesting and promote the development of mechanical grain harvesting technology.

The reciprocating cutting system is one of the key parts of a tea harvester; and its cutting performance directly determines the cutting power consumption and harvesting quality of the machine. Because the structural parameters of reciprocating cutting systems do not match the tea cut; resulting in larger cutting resistance, it is necessary to optimize the structural parameters. The cricket mouth part has outstanding performance in tea tree fiber cutting; and the curved structural characteristics of the upper jaw of the cricket have been useful to improve the cutting efficiency of cutting system. Quantitative analysis of the structure of the upper jaw revealed that the arc-shaped structure of the incisor lobe would inspire new bionic blades and bionic cutters to solve the above problems. The cutting performance experiment of the cutting blade was designed for investigating the effects of inter-node number; tea variety and blade type (ordinary blade; bionic blade e and bionic blade f) on the cutting force and cutting power consumption. Experimental results of cutting performance have shown that the bionic blade could reduce cutting resistance and cutting power consumption. Tea varieties had little effect on cutting force and cutting power consumption. In addition, the orthogonal test was carried out to study the influence of cutter type with the cutting speed ratio and cutting angle on the integrity rate and missing rate of tea shoot. The field cutting experiment showed that the cutting angle was the most important for the integrity rate and missing rate of tea shoot; followed by the cutter speed ratio; and finally, the cutter type. The optimum combination of parameters was a cutting speed of 0.8 m/s; a forward speed of 1.0 m/s; a cutting angle of −3°, and using the bionic cutter e. With the optimal parameter combination, the integrity rate and missing rate of the tea shoot were 92.7% and 3.9%, which were increased by 13.2% and decreased by 6.4% compared to those under the condition of the 0° cutting angle and an ordinary cutter. As a result, the bionic cutter could obviously reduce cutting resistance; reduce cutting power consumption and improve the harvesting quality. These results would provide guidance for the design of the reciprocating cutting system of tea harvesters and other stalk cutting machinery.

Compared with the movement of corn seeds in the sowing machine, the movement in the threshing machine is more intense. The collision between corn seeds and threshing parts and other corn seeds will not only change the movement path of corn seeds in the threshing clearance but also cause damage to corn seeds. Therefore, when using discrete element simulation technology to optimize the critical components of corn threshing machinery, it is necessary to measure corn seeds’ accurate collision recovery coefficient. However, when measuring the collision recovery coefficient between corn seeds, there will be multi-point collisions between corn seeds, affecting the measurement results’ accuracy. In order to solve this problem, this study combined high-speed photography and the sound waveform of corn seed collision to eliminate the interference of the multi-point collision phenomenon and improve the accuracy of measurement results. According to the above test method, the contact parameters of corn seeds were measured. Finally, the corn–corn rolling friction coefficient and corn–PMMA rolling friction coefficient were 0.0784 and 0.0934, respectively. The corn–corn static friction coefficient was 0.32, and the corn–PMMA static friction coefficient was 0.445. The corn–corn collision recovery and corn–PMMA collision recovery coefficients were 0.28 and 0.62, respectively. After that, the method’s reliability and the measurement results’ accuracy were verified by the plane collision test and repose angle test.

Harvesting is an important procedure for hydroponic lettuces in plant factories. At present, hydroponic lettuces are mainly harvested manually, and the key difficulty in mechanical harvesting is reducing the occurrence of leaf injury. Measuring the size of hydroponic lettuces using the image processing method and intelligently adjusting the operating parameters of the harvesting device are the foundation of high-quality harvesting for lettuces. The overlapped leaves of adjacent hydroponic lettuces cause difficulties in measuring lettuce size, especially the leaves expansion size. Therefore, we proposed an image processing method for measuring lettuce height and leaves expansion size according to the upper contour feature of lettuces and an image included three lettuces. Firstly, the upper contours of the lettuces were extracted and segmented via image preprocessing. Secondly, lettuce height was measured according to the maximum ordinate of the contour. Lastly, the lettuce’s upper contour was fitted to a function to measure the leaves expansion size. The measurement results showed that the maximal relative error of the lettuce height measurements was 5.58%, and the average was 2.14%. The effect of the quadratic function in fitting the upper contour was the best compared with the cubic function and sine function. The maximal relative error of the leaves expansion size measurements was 8.59%, and the average was 4.03%. According to the results of the lettuce height and leaves expansion size measurements, the grabbing parameters of each lettuce were intelligently adjusted to verify the harvesting effect. The harvesting success rates of lettuces was above 90%, and the injured leaves areas of the left, middle, and right lettuces in each image were 192.6 mm², 228.1 mm², and 205.6 mm², respectively. This paper provides a reference for the design and improvement of intelligent harvesters for hydroponic lettuces.