Development of expert system modeling based decision support system for swine manure management

Animal waste has always been considered as a resource for agricultural input as biofertilizer. However, the management is becoming more stringent due to environmental regulations. Livestock producers are faced with different manure management options that may be implemented into their operations. Given the expansion of the livestock industry, the implementation of environmental regulations, and the increasing importance of social and health issues, the selection of optimal manure management systems is becoming a strategically important task. Increasingly, integrated decision support systems (DSSs) are becoming necessary to assist decision makers in their evaluation of different manure management alternatives, like, liquid system, semi-solid system, solid system and bio-gas or bio-energy system based on combinations of different manure management sub-systems (collection, storage and application). To address this situation, a user-friendly computer program called Integrated Swine Manure Management (ISMM) is being developed for the Canadian Prairie provinces. Decision criteria including environmental, agronomic, social and health, greenhouse gas emission, and economic factors have been considered for the selection, design, and operation of the DSS. The expert system modeling is based on Visual Basic programming. Decision on adopting a particular combination of systems components is based on performance rating of the overall system. The program is interactive so that weighting factors for the different decision criteria can be varied to suit site-specific considerations. In this paper, the systems approach for development of an integrated liquid manure management system is discussed. Using a case study, sensitivity analysis of different combinations of management components is also reported for systems performance. The decision software compared satisfactorily with other available DSS packages.     

Economic feasibility of site-specific optical sensing for managing nitrogen fertilizer for growing wheat

A site-specific nitrogen fertilizer application system that uses optical reflectance measurements of growing wheat plants to estimate N requirements has been developed. The machine enables unique applications of liquid N fertilizer at a grid level of 0.37 m². To achieve widespread adoption, the precision application system must be efficient enough to overcome the cost advantage of pre-plant applications of anhydrous ammonia (NH₃) relative to top-dress applications of either dry or liquid N sources on growing wheat. The objective of this research is to determine if the system is more profitable than conventional methods. Data from on-farm N fertilizer experiments were collected across three years and nine locations in the Southern Plains of the U.S.A. Net returns were calculated for each of eight treatments. The site-specific precision system was competitive economically, but it was not unambiguously superior to the conventional alternatives because it could not overcome the cost advantage of NH₃ pre-plant N sources relative to the cost of applying urea-ammonium nitrate (UAN) during the growing season. The value of the precision system is sensitive to the price of UAN relative to the price of NH₃.

棉花膜下滴灌决策支持系统研究*

实现棉花膜下滴灌水分实时管理与自动控制,是新疆节水技术发展的必然要求。结合新疆生产实践,自主研发的棉花膜下滴灌决策支持系统以数据库、模型库、知识库和方法库为技术核心,通过田间传感器进行数据实时采集、计算、分析与决策,由控制系统发送决策指令来控制灌溉设备开闭提高了灌溉的时效性     

林业及生态系统管理决策支持系统研究综述

概述了决策支持系统的概念、结构组成，以及与MIS，ES的区别与联系，提出了DSS的未来发展方向。详细评价了国内外林业及生态系统管理决策支持系统的研究与应用情况。     

基于知识模型和生长模型的小麦管理决策支持系统

 将系统分析方法和数学建模技术应用于小麦栽培管理知识表达体系,通过解析和提炼小麦生育、管理指标与环境因子、生产水平之间的基础性关系和定量化算法,创建了小麦栽培管理动态知识模型(WheatKnow);进一步结合小麦生长模拟模型(WheatGrow)和小麦管理智能系统,充分利用软构件的语言无关性、可重用性及简便快捷的系统维护机制等特点,在Visual　C++和Visual　Basic平台上构建了综合性、数字化和构件化的基于知识模型与生长模型的小麦管理决策支持系统(MBDSSWM),实现了预测功能和决策功能的有机耦     

紫苏栽培管理知识模型及决策支持系统研究

将系统分析原理和数学建模技术应用于紫苏栽培管理知识表达体系,通过解析和提炼紫苏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紫苏栽培管理动态知识模型,并进一步利用软件技术在Visual C++平台上构建了基于知识模型的紫苏管理决策支持系统(KMDSSPM),实现了不同环境条件下的紫苏播前栽培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、密度设计、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,叶面积指数动态和干物质积累动态等。紫苏栽培管理知识模型的建立,克服了传统紫苏栽培模式及专家系统地域性强和广适性差的不足,从而为实现紫苏栽培管理决策的定量化和数字化奠定了基础。     

基于知识模型的网络化作物管理决策支持系统

以气象因子、土壤特性、品种参数、生产条件等数据为农作信息依托,以具有时空适应性的作物栽培管理动态知识模型为管理决策支撑,以网络通讯为系统信息发布与流通平台,运用软构件技术与Web应用技术,设计和实现了基于浏览器/服务器(B/S)模式的具有4层分布结构的网络化作物管理决策支持系统(knowledge model and web-based decision support system for crop management,KMWDSSCM).以江苏省为案例区,对系统进行了示范应用,结果表明,系统能在Internet环境下有效地进行作物生产管理决策,在江苏部分地区稻麦生产实践中具有较好的适用性和指导性.     

.NET框架下蛋鸡龙头企业生产经营管理辅助决策支持系统的研究

针对我国畜禽生产龙头企业的总体水平现状以及对禽蛋需求的增加,构思和完善畜禽养殖业龙头企业生产经营管理辅助决策支持系统,以蛋鸡为实例,设计基于数据库、网络技术的蛋鸡生产龙头企业生产经营管理系统,探索建设养鸡场生产网络信息系统的技术和方法,已建成一个可在单机、局域网以及Internet/Intranet等不同模式运行的生产经营管理系统。以提高我国规模化蛋鸡企业生产管理水平为目标,为科学饲养提供早期预测和辅助决策支持,为管理人员提供蛋鸡生产动态管理及科学决策提供依据。