摘要
将系统分析原理和数学建模技术应用于油菜管理知识表达体系,通过解析和提炼油菜生育指标及栽培技术与生态环境和生产技术水平之间的基础性关系和定量化算法,构建了具有时空规律的油菜栽培管理动态知识模型;并进一步利用软构件技术在VisualC++平台上构建了基于知识模型的油菜管理决策支持系统(KMDSSRM),实现了不同环境条件下的油菜播前方案设计及产中调控指标预测。其中,播前方案设计包括产量目标与产量结构,品种选择,播种期,基本苗和播种量,移栽方案,肥料运筹及水分管理等;调控指标预测包括叶龄动态,叶面积指数动态,角果皮面积指数动态和干物质积累动态等。油菜栽培管理知识模型的建立,克服了传统油菜栽培模式及专家系统地域性强和广适性差的不足,从而为实现油菜栽培管理决策的定量化和数字化奠定了基础。
By applying the system analysis principle and mathematical modeling technique to knowledge expression system for crop cultivation management, the fundamental relationships and quantitative algorithms of rapeseed growth and management indices to variety types, ecological environments and production levels were analyzed and extracted, and a dynamic knowledge model with temporal and spatial characteristics for rapeseed crop management was developed. Based on the utilization of the soft component characteristics, a knowledge model-based decision support system for rapeseed management (KMDSSRM) was developed on the platforms of Visual C^(++). The system can be used to design pre-sowing cultivation plan and predict suitable growth regulation indices of rapeseed. The pre-sowing cultivation plan includes yield level and components, variety type, sowing date, population density and sowing rate, transplanting plan, fertilization and water management. Regulation indices include time-course leaf age, leaf area index, pod area index and dry matter weight. The knowledge model overcomes the shortcomings of traditional rapeseed cultivation pattern and expert system, such as site specific and narrow applicability, and thus provides a framework for quantitative and digital decision-making on rapeseed cultivation management.
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2004年第6期141-144,共4页
Transactions of the Chinese Society of Agricultural Engineering
基金
国家自然科学基金重点项目(30030090)
国家863计划项目(2003AA209030)资助
关键词
油菜
栽培管理
知识模型
决策支持系统
数字化农作
rapeseed
cultivation management
knowledge model
decision support system
digital farming
