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Research Progress and Prospects of Intelligent Control Technology for Facility Vegetable
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Jian WANG1, Haosen ZHAO1, Yue MA1, Bin XING2, Wenying ZHU2
Smart Agriculture | 2026, 8(1) : 104 - 119
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Smart Agriculture | 2026, 8(1): 104-119
• Overview Article •
Research Progress and Prospects of Intelligent Control Technology for Facility Vegetable
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Jian WANG1, Haosen ZHAO1, Yue MA1, Bin XING2, Wenying ZHU2
Affiliations
  • 1.Beijing Digital Agriculture and Rural Development Promotion Center, Beijing 101117, China
  • 2.Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
  • WANG Jian, E-mail:

About Author:

WANG Jian, E-mail:

Published: 2026-01-30 doi: 10.12133/j.smartag.SA202508003
Outline
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[Significance] With the advancement of technology and diversified consumer demands, traditional agriculture is gradually transforming towards information and intelligence. Conducting research on intelligent management and control technologies for facility vegetable production is of great significance for improving vegetable yield and quality, ensuring stable market supply, and promoting high-quality development of the vegetable industry. The purpose of this article is to systematically collate the research status, key technologies and application constraints in the field of intelligent management and control of facility vegetables. By analyzing the development trends of environmental regrlation, growth monitoring and precise management, it provides scientific basis, theoretical support and decision-making references for the intelligent upgrading, technological innovation and policy formulation of Chinese facility vegetable industry, so as to boost the high-quality and sustainable development of facility agriculture. [Progress] This paper systematically analyzes the innovative applications of information technologies such as Internet of Things, block chain, and artificial intelligence in critical domains of facility vegetable production information, including precise regulation of the production environment, intelligent cultivation management and smart storage information management. In terms of precise regulation of the production environment, a temperature and humidity model for the optimal growth environment of tomatoes has been established, primarily utilizing Internet of Things technology. This enables precise monitoring and intelligent control of environmental parameters such as temperature, humidity, light, and carbon dioxide concentration within the facility, creating an optimal environment for vegetable growth. In the field of intelligent cultivation management, the integration of intelligent integrated water and fertilizer equipment, agricultural robotic operation systems, and pest and disease control has optimized the whole-process information-based management, effectively improving cultivation efficiency and vegetable quality. The integrated water and fertilizer systems apply Internet on Things technology to coordinate irrigation and fertilization through digital methods. Agricultural robotic operation systems are based on artificial intelligence, encompassing technologies such as machine learning, deep learning, neural networks and image processing. The pest and disease control section highlights the information-based applications in physical control, biological control and chemical control. In terms of smart storage information management, the application of origin storage preservation technology, intelligent classification and sorting systems, as well as traceability information platforms has significantly enhanced the circulation quality and safety assurance level of vegetables. Specifically, the origin storage preservation technology focuses on the development status of pre-cooling preservation, controlled atmosphere preservation, biological preservation and coating preservation. Intelligent grading and sorting technologies are categorized into non-destructive testing for both the external and internal quality of vegetables. The traceability information platform, leveraging blockchain and large model technologies, enables more intelligent management of facility vegetable production. [Conclusions and Prospects] This paper explores the problems encountered in the development of intelligent management and control technology for protected vegetables, including insufficient accuracy and stability of sensors, lagging regulatory decision-making, lack of equipment coordination mechanisms, poor integration of pest and disease control, fragmentation of information in the whole process of storage, difficulty in quality traceability, and lagging risk warning. Corresponding countermeasures and suggestions are proposed as follows: optimization of hardware, multi-technology integration to support precise perception and intelligent regulation, enhancement of equipment coordination and optimization, integration of pest and disease control, and construction of a virtual-real interactive storage management system through the integration of digital twins and metaverse. Finally, the paper prospects the future development direction of facility vegetable in precise control of production environment, cultivation management information, and storage information control.

facility vegetable  /  storage and preservation  /  intelligent control  /  water and fertilizer integration  /  pest and disease control  /  artificial intelligence
王剑, 赵浩森, 马越, 邢斌, 朱文颖. 设施蔬菜智能管控技术研究进展与展望. 智慧农业(中英文), 2026 , 8 (1) : 104 -119 . DOI: 10.12133/j.smartag.SA202508003
Jian WANG, Haosen ZHAO, Yue MA, Bin XING, Wenying ZHU. Research Progress and Prospects of Intelligent Control Technology for Facility Vegetable[J]. Smart Agriculture, 2026 , 8 (1) : 104 -119 . DOI: 10.12133/j.smartag.SA202508003
  • National Key Research and Development Program Project(2023YFD2001304)
  • Beijing Academy of Agriculture and Forestry Sciences Project(KJCX20251003)
Year 2026 volume 8 Issue 1
119
53
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Article Info
doi: 10.12133/j.smartag.SA202508003
  • Receive Date:2025-08-01
  • Online Date:2026-10-16
  • Published:2026-01-30
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History
  • Received:2025-08-01
Funding
National Key Research and Development Program Project(2023YFD2001304)
Beijing Academy of Agriculture and Forestry Sciences Project(KJCX20251003)
Affiliations
    1.Beijing Digital Agriculture and Rural Development Promotion Center, Beijing 101117, China
    2.Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China

Corresponding:

ZHU Wenying, E-mail:
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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