农业生产大数据治理：关键技术、应用分析与发展方向

doi:10.12133/j.smartag.SA202503020

Smart Agriculture

• •

农业生产大数据治理：关键技术、应用分析与发展方向

郭威¹^,²^,³^,⁴, 吴华瑞¹^,²^,³^,⁴(), 朱华吉¹^,²^,³^,⁴, 王菲菲¹^,²^,³^,⁴

^1. 国家农业信息化工程技术研究中心，北京 100097，中国
^2. 北京市农林科学院信息技术研究中心，北京 100097，中国
^3. 农业农村部数字乡村技术重点实验室，北京 100097，中国
^4. 农业农村部农业信息技术重点实验室，北京 100097，中国

收稿日期:2025-03-17 出版日期:2025-06-04
基金项目:
国家重点研发计划子课题(2023YFD2000101-02)
作者简介:
郭威，博士，研究方向为农业大数据与人工智能。E-mail：guowei007@nercita.org.cn
通信作者:
吴华瑞，博士，研究员，农业人工智能与大模型。E-mail：wuhr007@nercita.org.cn

Agricultural Big Data Governance: Key Technologies, Applications Analysis and Future Directions

GUO Wei¹^,²^,³^,⁴, WU Huarui¹^,²^,³^,⁴(), ZHU Huaji¹^,²^,³^,⁴, WANG Feifei¹^,²^,³^,⁴

^1. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China
^2. Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
^3. Key Laboratory of Digital Village Technology, Ministry of Agriculture and Rural Affairs, Beijing 100097, China
^4. Key Laboratory of Agri-informatics, Ministry of Agriculture and Rural Affairs, Haidian District, Beijing 10097, China

Received:2025-03-17 Online:2025-06-04
Foundation items:Subtopic of National Key Research and Development Program of China(2023YFD2000101-02)
About author:
GUO Wei, E-mail: guowei007@nercita.org.cn
Corresponding author:
WU Huarui, E-mail: wuhr007@nercita.org.cn

摘要/Abstract

摘要：

[目的/意义] 本文针对中国农业生产数据存在获取标准不一、数据采集不全、治理机制不明的问题，对现有的农业生产大数据治理模式进行了探索，通过大数据治理关键技术、适配工具的集成与场景化创新应用，阐明面向农业生产大数据治理的数据要素价值发挥的技术路径，为实现数据驱动农业高质量生产提供参考。 ［进展］ 从农业生产大数据治理的视角，探索了数据获取与处理、数据存储与交换、数据管理、数据分析、大模型和数据安全保障6大环节17个类大数据治理技术及工具，深度研究了大数据治理技术在农业生产中的应用方式，以上技术通过数据匹配、算力匹配、网络适配、模型匹配、场景匹配、业务组配等工具和中间件在场景中得到较好应用。剖析了农业生产产前、产中、产后全链条数据治理，以及面向不同类型农业园区、科研院所和高校、生产主体与农户服务案例。介绍了在国家级产业园区、省级农业科技园区和部分单品主体的治理经验，并调研了国内外农业生产大数据治理技术、做法和工具。 ［结论/展望] 对农业生产大数据治理未来发展方向提出了见解，包括推动农业生产大数据治理标准的制定与落地，构建农业生产大数据治理通用资源池，扩展农业生产大数据治理多元化应用场景，适应大模型及海量数据驱动下的农业生产大数据治理新范式和强化农业生产大数据安全与隐私保护。

关键词: 农业生产大数据治理, 农业生产数据获取与处理, 农业生产元数据, 农业生产数据安全保障, 农业生产大模型

Abstract:

[Significance] This paper addresses the issues of inconsistent acquisition standards, incomplete data collection, and unclear governance mechanisms in China's agricultural production data. It explores the existing governance models for agricultural production big data, clarifying the technical path for the value realization of data elements through the integration and innovative application of key big data governance technologies and tools in scenarios. This provides a reference for achieving high-quality agricultural production driven by data. [Progress] From the perspective of agricultural production big data governance, it explores 17 types of big data governance technologies and tools in 6 major processes: data acquisition and processing, data storage and exchange, data management, data analysis, large model, and data security guarantee. It deeply studies the application methods of big data governance technologies in agricultural production. The remote sensing, unmanned aerial vehicle, Internet of Things, and terminal data acquisition and processing systems are basically mature, the data storage and exchange system is developing rapidly, the data management technology is in the initial stage, the data analysis technology is widely applied, the large model technology system is initially formed, and the data security guarantee system is gradually applied. The above technologies are well applied in scenarios through tools and middleware such as data matching, computing power matching, network adaptation, model matching, scenario matching, and business configuration. It analyzes the data governance throughout the entire chain of agricultural production, including pre-production, production, and post-production, as well as service cases for different types of agricultural parks, research institutes and universities, production entities, and farmers. It shows that good data governance can provide sufficient planning and input analysis before production, helping planting entities to plan reasonably; in production, it can provide data-based guidance for key scenarios such as agricultural machinery operations and agricultural technical services to fully assist the decision-making process of the production process; and based on massive data, it can achieve good results in yield assessment and production benefit evaluation. It introduces the governance experience in national-level industrial parks, provincial-level agricultural science and technology parks, and some single-product entities, and investigates the technologies, practices, and tools of agricultural production big data governance at home and abroad, indicating that it is necessary to break through the business chain and service model of agricultural production across regions, themes, and scenarios. [Conclusions and Prospects] This paper puts forward insights on the future development direction of agricultural production big data governance, including promoting the formulation and implementation of standards for agricultural production big data governance, building a general resource pool for agricultural production big data governance, expanding diversified application scenarios for agricultural production big data governance, adapting to the new paradigm of agricultural production big data governance driven by large models and massive data, and strengthening the security and privacy protection of agricultural production big data.

Key words: agricultural production big data governance, agricultural production data acquisition and processing, agricultural production metadata, agricultural production data security, large model of agricultural production

中图分类号:

TP391
S-1

郭威, 吴华瑞, 朱华吉, 王菲菲. 农业生产大数据治理：关键技术、应用分析与发展方向[J]. 智慧农业(中英文), doi: 10.12133/j.smartag.SA202503020.

GUO Wei, WU Huarui, ZHU Huaji, WANG Feifei. Agricultural Big Data Governance: Key Technologies, Applications Analysis and Future Directions[J]. Smart Agriculture, doi: 10.12133/j.smartag.SA202503020.

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农业生产大数据治理：关键技术、应用分析与发展方向

Agricultural Big Data Governance: Key Technologies, Applications Analysis and Future Directions

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