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Smart Agriculture ›› 2024, Vol. 6 ›› Issue (6): 1-22.doi: 10.12133/j.smartag.SA202410018

• 专题--农业知识智能服务和智慧无人农场(上) • 上一篇    下一篇

水稻智慧无人农场关键技术研究现状与展望

于丰华1,2,3(), 许童羽1,2,3(), 郭忠辉1, 白驹驰1, 相爽1, 国斯恩1, 金忠煜1, 李世隆1, 王世宽1, 刘美含1, 惠尹宣1   

  1. 1. 沈阳农业大学 信息与电气工程学院,辽宁 沈阳 110866,中国
    2. 国家数字农业区域创新分中心(东北),辽宁 沈阳 110866,中国
    3. 辽宁省智慧农业技术重点实验室,辽宁 沈阳 110866,中国
  • 收稿日期:2024-10-19 出版日期:2024-11-30
  • 基金项目:
    国家自然科学基金青年项目(32201652); 辽宁省教育厅平台项目(JYTPT2024002); 辽宁省“兴辽英才计划”项目(XLYC2203005); 辽宁省应用基础研究计划项目(2023JH2/101300120)
  • 作者简介:
    于丰华,研究方向为农业无人机遥感与精准作业。E-mail:
  • 通信作者:
    许童羽,博士,教授,研究方向为智慧农业。E-mail:

Research Status and Prospects of Key Technologies for Rice Smart Unmanned Farms

YU Fenghua1,2,3(), XU Tongyu1,2,3(), GUO Zhonghui1, BAI Juchi1, XIANG Shuang1, GUO Sien1, JIN Zhongyu1, LI Shilong1, WANG Shikuan1, LIU Meihan1, HUI Yinxuan1   

  1. 1. College of Information and Electrical Engineering, Shenyang Agricultural University, Shenyang 110866, China
    2. National Regional Innovation Sub-center for Digital Agriculture (Northeast), Shenyang 110866, China
    3. Liaoning Key Laboratory of Intelligent Agricultural Technology, Shenyang 110866, China
  • Received:2024-10-19 Online:2024-11-30
  • Foundation items:Youth Project of the National Natural Science Foundation of China(32201652); Platform Project of Liaoning Provincial Department of Education(JYTPT2024002); Liaoning Province "Xingliao Talent Programme" Project(XLYC2203005); Liaoning Province Applied Basic Research Programme Project(2023JH2/101300120)
  • About author:
    YU Fenghua, E-mail:
  • Corresponding author:
    XU Tongyu, E-mail:

摘要:

[目的/意义] 水稻智慧无人农场是智慧农业的重要应用领域,代表了水稻生产现代化的关键路径,旨在推动农业的高质量发展。水稻智慧无人农场依托物联网、人工智能等先进信息技术,通过数据驱动和智能装备的集成,构建了涵盖水稻种植、管理、收获的全程无人化生产体系,提高水稻生产的效率和质量,降低生产成本。 [进展] 本文系统梳理了水稻智慧无人农场在产前、产中和产后三个主要环节的关键技术,包括高标准农田建设、无人育苗、土地平整、土壤养分检测、水稻旱直播、自动化插秧、精准变量施肥、田间病害诊断、智慧灌溉、水稻估产、无人收割及稻谷储藏、加工品质检测等。 [结论/展望] 通过对近年来国内外水稻智慧无人农场建设的案例进行综述,进而总结了无人农场关键技术在实际应用中面临的主要难点,分析了智慧无人农场在建设中所遇到的挑战,对政府、企业、科研机构、合作社等主体在推动水稻智慧无人农场建设中的角色和责任进行了总结,并提出了相关建议,为中国水稻智慧无人农场建设提供一定的支撑和发展思路。

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

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