CN107357893A - 一种粮食作物有害生物诊治专家系统 - Google Patents
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Abstract
本发明公开了一种粮食作物有害生物诊治专家系统,包括基本信息模块,内设有粮食作物发生的181种病虫草害,分为玉米病虫、水稻病虫、其他粮作病虫和农田杂草四部分;辅助功能模块,包括专家答疑、来访留言板、联系模块,用户可通过联系模块与专家沟通,实现直接对专家的咨询,从而得到更直接和优质地服务,并可以收集用户的意见和建议,完善该系统。管理模块,通过输入管理者口令,进入编辑模式对知识库进行更新与添加。本发明采用图像指认式专家系统,兼有查询浏览功能,系统容量适中,设计科学合理,系统为动态的,可实时更新。
Description
技术领域
本发明涉及农业领域,具体涉及一种粮食作物有害生物诊治专家系统。
背景技术
根据已报道的相关农业专家系统,涉及栽培植物有害生物诊治方面的专家系统有查询浏览式系统、图像指认式系统和基于规则诊治式系统三种。
目前进入实用阶段并与之相近的仅见“蔬菜病虫害辅助诊断与防治系统”,其具有以下客观缺点:1、知识库庞大。包括了瓜类、茄果类等15类103种蔬菜的2167种病虫害,每种病虫害有5~30幅图像和大量文本信息。这样庞大的数据库占用空间大,也不利于用户快速诊治有害生物。2、图像和文本信息冗繁,用户针对性不强。将所有采集的图像和文本信息均使用并放在同一页面上,导致各类用户如农技员、农户、植保科研人员和专业技术人员不能迅速找到自己所需要的知识点。3、门槛较高。如诊断病害时先区分根、茎、叶等植物器官,诊断害虫时要能区别卵、幼虫、成虫等专业性知识,低端用户如农户可能有一定困难。4、静态系统。不能根据生产上病虫害及所用农药的变化而随时更新内容。
发明内容
为解决上述问题,本发明提供了一种粮食作物有害生物诊治专家系统,采用了图像指认式系统,兼有查询浏览的功能,具有诊断准确率高、诊治时效性好、门槛低而用户多等优点。
为实现上述目的,本发明采取的技术方案为:
粮食作物有害生物诊治专家系统,包括:
基本信息模块,内设有粮食作物发生的181种病虫草害,分为玉米病虫、水稻病虫、其他粮作病虫和农田杂草四部分;知识库页面的左侧为上述四部分目录,余下大部分为所有粮食作物病虫草害的最为典型的、能准确诊断该有害生物的生态图像,即病害为植物最常发病器官上的典型症状图、害虫系为害虫态及为害状图、杂草为典型成株期危害状图;用户通过比对来确定有害生物种类,缩短了诊断时间,提高了诊断准确率,同时无需区分植物器官或害虫虫期再进入生态图像区,降低了使用门槛。
辅助功能模块,包括专家答疑、来访留言板、联系模块,用户可通过联系模块,比如电话、QQ、微信、上传图像等形式与专家沟通,实现直接对专家的咨询,从而得到更直接和优质地服务,并可以收集至用户的意见和建议,完善该系统。
管理模块,通过输入管理者口令,进入编辑模式对知识库进行更新与添加。
其中,所述病虫的生态图像内设有相关病虫害典型图像的放大版,并有该种的识别特征、发生规律、防治方法内容的链接。
其中,所述基本信息模块内还设有“更多”模块,包括该种有害生物的学名、英文名、发生特点、病原菌及害虫的分类地位及其它时期的形态文本信息及图像、新发种类的参考文献,供植保科研人员及专业技术人员使用。
本发明具有以下有益效果:
1、采用图像指认式专家系统,兼有查询浏览功能。克服了规则诊治式系统的用文字描述复杂的生物形态及门槛过、高非专业人士无法使用,用时过长多步骤才获得结果,模糊查询结果不准确等问题。
2、系统容量适中。包括吉林省主栽的玉米、水稻及高粱、谷子、小麦、甘薯等粮食作物发生的181种病虫草害。既可以满足粮食生产上有害生物的诊治需要,又不至于容量过大而影响用户的高效使用。
3、系统设计科学合理。将每种作物发生的与准确诊断有直接关系的典型田间生态图像放在首页面,并根据不同用户对植保知识的需求,把图文信息进行分层设计,使用户高效率地找到所需的知识点。
4、知识库图文信息质量高,具有完全自主产权。数据库里所有图像均为作者多年田间拍摄而来,文本信息多为多年科研和生产实践所得。选材科学合理,符合绿色植保和可持续植保特色,防治技术中农药均为国家现时登记的品种。
5、系统为动态的,可时时更新。知识库可随时根据生产、科研而更新和添加。并且用户可通过电话、QQ、E-mail、微信等方式与专家沟通咨询,以快速解决植保问题,提高系统服务的速度和质量。
6、系统运行环境简单,可用智能手机使用。无需登录注册完全开放性。计算机水平低者可使用。该系统可用于相关人员的自我学习与培训功能。
附图说明
图1为本发明实施例粮食作物有害生物诊治专家系统的系统框图。
具体实施方式
为了使本发明的目的及优点更加清楚明白,以下结合实施例对本发明进行进一步详细说明。应当理解,此处所描述的具体实施例仅仅用以解释本发明,并不用于限定本发明。
如图1所示,本发明实施例提供了一种粮食作物有害生物诊治专家系统,包括:
基本信息模块,内设有吉林省主栽的玉米、水稻及高粱、谷子、小麦、甘薯等粮食作物发生的181种病虫草害,分为玉米病虫、水稻病虫、其他粮作病虫和农田杂草四部分;知识库页面的左侧为上述四部分目录,余下大部分为所有粮食作物病虫草害的最为典型的、最能确诊的该有害生物的生态图像,即病害为植物最常发病器官上的典型症状图、害虫系为害虫态及为害状图、杂草为典型成株期危害状图;用户通过比对来确定有害生物种类,缩短了诊断时间,提高了诊断准确率,同时无需区分植物器官或害虫虫期再进入生态图像区,降低了使用门槛。在点击图片进入的介面里,有病虫草的典型图像的放大版,并有该种有害生物的识别特征、发生规律、防治方法等内容,供生产一线的农技员和农户指导农业生产使用;通过“更多”进入另一个介面,这部分包括该种有害生物的学名、英文名、发生特点、病原菌及害虫的分类地位及其它时期的形态等文本信息及图像、新发种类的参考文献等,供植保科研人员及专业技术人员使用。将图文信息分层处理便于不同用户迅速找到各自所需的知识点,提高诊断的速度。
辅助功能模块,包括专家答疑、来访留言板、联系模块,用户可通过联系模块,比如电话、QQ、微信、上传图像等形式与专家沟通,实现直接对专家的咨询,从而得到更直接和优质地服务。同时可以收集用户的建议及生产上病虫害的动态,进一步完善该系统,实现良性循环。
管理模块,用于对知识库的更新与添加。随着有害生物种类的不断变化、发生规律及防治措施的深入研究、农药的更新及田间生态图像不断采集等,知识库图文信息的数量和质量将不断完善,这些可以通过后台管理,输入管理者口令,进入编辑模式来完成。
以上所述仅是本发明的优选实施方式,应当指出,对于本技术领域的普通技术人员来说,在不脱离本发明原理的前提下,还可以作出若干改进和润饰,这些改进和润饰也应视为本发明的保护范围。
Claims (3)
1.粮食作物有害生物诊治专家系统,其特征在于,包括:
基本信息模块,内设有粮食作物发生的181种病虫草害,分为玉米病虫、水稻病虫、其他粮作病虫和农田杂草四部分;知识库页面的左侧为上述四部分目录,余下大部分为所有粮食作物病虫草害的最为典型的、能准确诊断该有害生物的生态图像,即作物病害为最常发病器官上的典型症状图、害虫系为害虫态及为害状图、杂草为成株期危害状图;
辅助功能模块,包括专家答疑、来访留言板及上传图片、联系方式等,用户可通过其与专家进行沟通,实现直接对专家的咨询;
管理模块,通过输入管理者口令,进入编辑模式对知识库进行更新与添加。
2.如权利要求1所述的粮食作物有害生物诊治专家系统,其特征在于,所述病虫的生态图像内设有相关病虫害典型图像的放大版,并有该种的识别特征、发生规律、防治方法内容的链接。
3.如权利要求1所述的粮食作物有害生物诊治专家系统,其特征在于,所述基本信息模块内还设有“更多”模块,包括该种有害生物的学名、英文名、发生特点、病原菌及害虫的分类地位及其它时期的形态文本信息及图像、新发种类的参考文献等,供植保科研人员及专业技术人员使用。
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Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
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WO2000015847A2 (en) * | 1998-09-11 | 2000-03-23 | Gene Logic, Inc. | Genomic knowledge discovery |
CN106503785A (zh) * | 2015-09-05 | 2017-03-15 | 张学 | 一种农业虫害智能监控系统 |
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WO2000015847A2 (en) * | 1998-09-11 | 2000-03-23 | Gene Logic, Inc. | Genomic knowledge discovery |
CN106503785A (zh) * | 2015-09-05 | 2017-03-15 | 张学 | 一种农业虫害智能监控系统 |
Non-Patent Citations (1)
Title |
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谢艳新等: "基于ASP.NET的吉林省病虫害专家诊治系统开发", 《农业网络信息》 * |
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