关键词: 无人农场, 水稻, 智慧农业, 智能决策, 智能装备

Abstract:

[Significance] Rice smart unmanned farm is the core component of smart agriculture, and it is a key path to realize the modernization of rice production and promote the high-quality development of agriculture. Leveraging advanced information technologies such as the Internet of Things (IoT) and artificial intelligence (AI), these farms enable deep integration of data-driven decision making and intelligent machines. This integration creates an unmanned production system that covers the entire process from planting and managing rice crops to harvesting, greatly improving the efficiency and precision of rice cultivation. [Progress] This paper systematically sorted out the key technologies of rice smart unmanned farms in the three main links of pre-production, production and post-production, and the key technologies of pre-production mainly include the construction of high-standard farmland, unmanned nursery, land leveling, and soil nutrient testing. The construction of high-standard farmland is the foundation of the physical environment of the smart unmanned farms of rice, which provides perfect operating environment for the operation of modernized smart farm machinery through the reasonable layout of the field roads, good drainage and irrigation systems, and the scientific planting structure. Agricultural machine operation provides a perfect operating environment. The technical level of unmanned nursery directly determines the quality of rice cultivation and harvesting in the later stage, and a variety of rice seeding machines and nursery plate setting machines have been put into use. Land leveling technology can improve the growing environment of rice and increase the land utilization rate, and the current land leveling technology through digital sensing and path planning technology, which improves the operational efficiency and reduces the production cost at the same time. Soil nutrient detection technology is mainly detected by electrochemical analysis and spectral analysis, but both methods have their advantages and disadvantages, how to integrate the two methods to achieve an all-round detection of soil nutrient content is the main direction of future research. The key technologies in production mainly include rice dry direct seeding, automated transplanting, precise variable fertilization, intelligent irrigation, field weed management, and disease diagnosis. Among them, the rice dry direct seeding technology requires the planter to have high precision and stability to ensure reasonable seeding depth and density. Automated rice transplanting technology mainly includes three ways: root washing seedling machine transplanting, blanket seedling machine transplanting, and potting blanket seedling machine transplanting; at present, the incidence of problems in the automated transplanting process should be further reduced, and the quality and efficiency of rice machine transplanting should be improved. Precision variable fertilization technology is mainly composed of three key technologies: information perception, prescription decision-making and precise operation, but there are still fewer cases of unmanned farms combining the three technologies, and in the future, the main research should be on the method of constructing the whole process operation system of variable fertilization. The smart irrigation system is based on the water demand of the whole life cycle of rice to realize adaptive irrigation control, and the current smart irrigation technology can automatically adjust the irrigation strategy through real-time monitoring of soil, climate and crop growth conditions to further improve irrigation efficiency and agricultural production benefits. The field weed management and disease diagnosis technology mainly recognizes rice weeds as well as diseases through deep learning and other methods, and combines them with precision application technology for prevention and intervention. Post-production key technologies mainly include rice yield estimation, unmanned harvesting, rice storage and processing quality testing. Rice yield estimation technology is mainly used to predict yield by combining multi-source data and algorithms, but there are still problems such as the difficulty of integrating multi-source data, which requires further research. In terms of unmanned aircraft harvesting technology, China's rice combine harvester market has tended to stabilize, and the safety of the harvester's autopilot should be further improved in the future. Rice storage and processing quality detection technology mainly utilizes spectral technology and machine vision technology to detect spectra and images, and future research can combine deep learning and multimodal fusion technology to improve the machine vision system's ability and adaptability to recognize the appearance characteristics of rice. [Conclusions and Prospects] This paper reviews the researches of the construction of intelligent unmanned rice farms at home and abroad in recent years, summarizes the main difficulties faced by the key technologies of unmanned farms in practical applications, analyzes the challenges encountered in the construction of smart unmanned farms, summarizes the roles and responsibilities of the government, enterprises, scientific research institutions, cooperatives and other subjects in promoting the construction of intelligent unmanned rice farms, and puts forward relevant suggestions. It provides certain support and development ideas for the construction of intelligent unmanned rice farms in China.

Key words: unmanned farms, rice, smart agriculture, smart decision-making, smart equipment