中国农业科学 ›› 2005, Vol. 38 ›› Issue (02): 283-289 .

• 耕作栽培.生理生态 • 上一篇    下一篇

小麦栽培管理动态知识模型的构建与检验

朱艳,曹卫星,田永超,戴廷波,邹忠   

  1. 南京农大农业部作物生长调控重点开放实验室
  • 收稿日期:2003-12-29 修回日期:1900-01-01 出版日期:2005-02-10 发布日期:2005-02-10
  • 通讯作者: 曹卫星

Development and Testing of a Dynamic Knowledge Model for Wheat Cultural Management

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  1. 南京农大农业部作物生长调控重点开放实验室
  • Received:2003-12-29 Revised:1900-01-01 Online:2005-02-10 Published:2005-02-10

摘要: 将系统分析方法和数学建模技术应用于小麦管理知识表达体系,通过解析和提炼小麦生育及管理指标与环境因子及生产水平之间的基础性关系和定量化算法,创建了小麦管理动态知识模型WheatKnow;充分利用软构件的技术特点,在Visual C++和Visual Basic平台上研制了数字化和组件化小麦管理动态知识模型系统,实现了播前栽培方案的设计和产中适宜调控指标动态的预测2大功能。其中,播前栽培方案包括产量目标、适宜品种、播期、基本苗及播种量、肥料运筹和水分管理;产中调控指标包括适宜生育期、穗分化进程、生长指标、源库指标和营养指标动态。利用不同生态点、不同品种、不同土壤等资料及大田对比试验对所建知识模型进行实例分析和检验的结果表明,所提出的小麦管理动态知识模型总体上具有较好的广适性和决策性。本研究克服了传统作物栽培模式与专家系统地域性强和广适性弱的不足,从而为实现作物栽培管理的精确化和数字化奠定了基础。

关键词: 小麦, 知识模型, 栽培方案, 调控指标, 构建, 检验

Abstract: By adopting the principle of system analysis and technique of mathematical modeling to knowledge expression system for wheat management, a dynamic knowledge model with temporal and spatial characters for digital wheat management was developed by extracting and formulating the fundamental relationships and quantitative algorithms of wheat growth indices and management criteria to variety types, ecological environments and production levels. With incorporation of the soft component characteristics, a component-based knowledge model system for digital wheat management was established on the platforms of Visual C++ and Visual Basic. The system realized two major functions as design of pre-sowing cultural plan and prediction of regulation index dynamics. The module of cultural plan design included the sub-models for determination of target yield and quality, suitable variety, sowing date, population density and sowing rate, fertilization strategy and water management, and the module of regulation index dynamics included the sub-models for suitable development stages, spike differentiation stages, dynamics of growth indices, source-sink indices and nutrient indices. Simulation studies on the knowledge model with the data sets of different eco-sites, cultivars, soil types and so on, and comparative field experiments indicated a good performance of the knowledge model system in decision-making and wide applicability. The present knowledge model system overcomes the shortcomings as specific site limitation and low quantification of traditional wheat cultivation patterns and expert systems, and lays a foundation for facilitating the digitization of wheat management.

Key words: Wheat, Knowledge model, Cultural plan, Regulation index, Model development, System testing