【摘要】 随着大数据、人工智能、物联网、云计算等现代信息技术与农业领域的深度融合，现代农业正朝着智能化方向迈进.知识工程在整合、管理、挖掘和利用农业知识方面发挥了至关重要的作用，为实现个性化、精准化的农业认知智能服务提供了强有力的技术支持.探讨了当前农业知识工程及认知智能服务面临的主要挑战，综述了国内外农业认知智能服务领域的研究现状，提出了集成数据层、算法层和认知服务层的基础研究框架.在此基础上，创新性地设计了基于主动元学习思想，通过软件智能体与科学大数据双向偶联自指循环方式完成农业大数据整合和知识建模、知识抽取、知识融合以及知识推理的农业认知智能服务构建框架，梳理了各环节涉及的关键技术和服务应用.最后，对农业认知智能服务领域的未来发展趋势和对策建议进行总结与展望.更多还原

【Abstract】 With the deep integration of agriculture and modern information technologies such as big data,artificial intelligence,the Internet of Things,and cloud computing,the field of modern agriculture is gradually embracing intelligence. Knowledge engineering plays a crucial role in integrating,managing,mining,and utilizing agricultural knowledge,providing robust support for personalized and precise agricultural cognitive intelligent services. This article discusses the primary challenges in agricultural knowledge engineering and cognitive intelligent services,reviews the current research status of both domestic and international agricultural cognitive intelligent services,and proposes a foundational research framework that integrates the layers of data,algorithms,and cognitive services. Building upon this framework,a novel framework for agricultural cognitive intelligent services utilizing active meta-learning is introduced to achieve data integrating and knowledge modeling,extraction,fusion,and reasoning for agricultural big data through bidirectional coupling with software intelligent agents and scientific big data. Key technologies and service applications involved in each step are outlined. Finally,the article concludes by summarizing future trends and offering recommendations for the development of agricultural cognitive intelligent services.更多还原