我国种植业产品良好农业规范生产的信息化应用研究

发布时间：2018-03-05 16:12

本文选题：中国良好农业规范(CHINAGAP)　切入点：信息技术　出处：《中国农业大学》2016年博士论文　论文类型：学位论文

【摘要】：本文对良好农业规范(GAP)进行了系统的整理和研究,对良好农业规范的概念、内容、标准体系、发展历程和现状等方面进行了探讨和分析,提出了中国良好农业规范(CHINAGAP)发展的对策。基于农业部优质农产品开发服务中心开展良好农业规范推广和信息化建设工作,本文研究了CHINAGAP生产和认证信息服务平台、专家系统和可追溯系统的开发应用,并对上述系统的推广使用情况进行了调查和分析。CHINAGAP生产和认证信息服务平台对象定位为农业生产者(CHINAGAP认证申请人)、认证机构和消费者,在技术上采用具有良好跨平台性的ASP.NET三层架构体系结构,将良好农业规范生产和认证信息服务平台分成前台展示和后台管理两部分。CHINAGAP生产和认证信息服务平台的内容包括工作动态、办事大厅、认证进度查询、认证统计、用户登录、认证申请,资料下载、查询专区、特色功能、网上调查、站内搜索、友情链接12个栏目,有效实现CHINAGAP生产和认证信息服务、知识查询、在线认证申请、网上审核等功能。CHINAGAP专家系统采用B/S架构,MVC设计模式设计为服务层、业务逻辑层和数据层3层。具体功能主要包括标准咨询模块、知识管理模块、生产管理方案推荐模块、用户管理模块、系统维护模块和帮助模块6个模块。通过本体推理与数据挖掘技术相结合,成功实现CHINAGAP控制点的推荐功能。CHINAGAP标准知识采用本体作为知识表现形式实现了CHINAGAP标准知识共享与重用,为进一步的CHINAGAP相关软件和语义网开发提供参考。采用数据挖掘技术对CHINAGAP认证历史资料关联规则进行挖掘,通过对经典Apriori算法的改进,优化运算流程,获得了用户使用CHINAGAP标准的偏好模式。采用多指标的控制点评价模型,将专家经验与历史上的用户偏好相结合进行分析判断,结果择优向用户推荐,使专家系统的推理既具科学性又有人性化,推荐结果更符合用户自身特点,可操作性强。CHINAGAP可追溯系统基于CHINAGAP标准内容设计追溯内容,采用故障树分析法建立相应的风险评估模型,由信息查询模块、环节管理模块、风险评估模块、标签管理模块、系统维护模块5部分组成,实现生产记录档案电子化存储和查询、生产失败风险的评估、追溯标签的生成等功能。通过对CHINAGAP生产与认证服务平台、专家系统和可追溯系统的推广使用情况调查,用户对平台和两个系统的评价基本符合设计之初的目标,在CHINAGAP标准宣传、认证服务、生产指导等方面都发挥了较好的作用,同时也发现了一些问题与不足,为下一步改进平台栏目设计和系统的功能方面提供了重要参考。
[Abstract]:In this paper, the concept, content, standard system, development course and current situation of good agricultural norms are systematically studied. This paper puts forward the countermeasures for the development of China's good Agricultural Standards (CHINAGAPP). Based on the good agricultural standard extension and information construction work carried out by the Ministry of Agriculture High quality Agricultural products Development Service Center, the CHINAGAP production and certification information service platform is studied in this paper. The development and application of the expert system and the traceability system, and the investigation and analysis of the popularization and use of the above-mentioned system. The production and certification information service platform of CHINAGAP is targeted at agricultural producers, certification agencies and consumers. Technically, the ASP.NET three-tier architecture with a good cross-platform nature is adopted. The good agricultural standard production and certification information service platform is divided into two parts: foreground display and background management. The contents of CHINAGAP production and certification information service platform include work dynamics, work hall, certification progress query, authentication statistics, user login, Certification application, data download, inquiry area, feature function, online investigation, in-station search, friendship link 12 columns, effective implementation of CHINAGAP production and certification information services, knowledge inquiries, online certification applications, The expert system of CHINAGAP is designed as service layer, business logic layer and data layer with B / S architecture and MVC design pattern. The specific functions include standard consultation module, knowledge management module, production management scheme recommendation module, etc. User management module, system maintenance module and help module. Through ontology reasoning and data mining technology, The recommendation function of CHINAGAP control point .CHINAGAP standard knowledge is realized successfully. Ontology is used as knowledge representation to realize CHINAGAP standard knowledge sharing and reuse. Data mining technology is used to mine the association rules of CHINAGAP authentication history data. By improving the classical Apriori algorithm, the operation flow is optimized. The preference model of user using CHINAGAP standard is obtained. The expert experience and historical user preference are analyzed and judged by using multi-index control point evaluation model, and the results are recommended to the user. The reasoning of the expert system is scientific and humanized, the recommended results are more in line with the user's own characteristics, and the traceability system has strong maneuverability based on the CHINAGAP standard content design traceability. The corresponding risk assessment model is established by using fault tree analysis, which consists of five parts: information query module, link management module, risk assessment module, label management module and system maintenance module. To realize the functions of electronic storage and query of production records, evaluation of production failure risk, generation of traceability labels, etc. Through the investigation of the popularization and use of CHINAGAP production and certification service platform, expert system and traceability system, The evaluation of the platform and the two systems is basically in line with the initial design objectives, and has played a better role in the CHINAGAP standard promotion, certification services, production guidance, and so on. At the same time, some problems and deficiencies have been found. It provides an important reference for the next step to improve the platform column design and the function of the system.
【学位授予单位】：中国农业大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：S126

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