首页|期刊导航|安徽农业科学|基于区域生态型的农作物病虫害模型预报运行管理平台的设计与实现

基于区域生态型的农作物病虫害模型预报运行管理平台的设计与实现OA

Design and Implementation of Model Forecasting System of Crop Diseases Based on Regional Ecotype

中文摘要英文摘要

为提高病虫害监测有效性、预报准确性,解决预测模型时空适应性差的问题,采用开放式架构产品(open architecture products,OAP)设计理念和客户/服务器(client/server,C/S)开发方式,以田间小气候数据和病虫害监测数据为主要数据源,结合病害预测预报模型,设计和实现了基于区域生态型的农作物病虫害模型预报运行管理平台.该系统包括采集层、数据层、模型层和发布层 4 层框架,具有动态建模、自由定制、数据管理、模型预测、预报发布、辅助决策等功能.以四川省大竹县苗瘟预测模型为示范对象进行测试和试运行,结果表明,该系统能够实现较高程度的个性化建模或模型修正,预测结论符合模型预期,验证了该方法的可靠性.

To improve the effectiveness and accuracy of disease and pest monitoring and forecasting,and to solve the problem of poor spatio-temporal adaptability of prediction models,a model forecasting system for crop diseases based on regional ecotype was designed and implemen-ted.The system adopts open architecture products(OAP)design concept and client/server(C/S)development approach,integrated with pre-diction models.Its data sources are mainly field microclimate and disease and pest surveillance data.The system includes a four-layer software framework:acquisition layer,data layer,model layer,and publishing layer.It has functions for dynamic modeling,personalized customization,data management,model prediction,forecast release,decision-making assistance,etc.Taking the prediction model of seeding blasts in Dazhu County,Sichuan Province as the demonstration object,the system functions were tested and trial-operated.The results showed that the system can achieve a high degree of personalized modeling or model revision,and the prediction conclusions are in line with the model expectations,which verifies the reliability of the method in this study.

蒲颇;封传红;曾娟;杜永均;杨淞杰;吴金鑫;梅耀天;张国芝

四川省农业农村厅植物保护站,四川 成都 410061四川省农业农村厅植物保护站,四川 成都 410061全国农业技术推广服务中心,北京 100125浙江大学农药与环境毒理研究所,浙江 杭州 310058四川省农业农村厅植物保护站,四川 成都 410061四川省农业农村厅植物保护站,四川 成都 410061四川省农业农村厅植物保护站,四川 成都 410061四川省农业农村厅植物保护站,四川 成都 410061

农业科技

监测预警区域生态型预测模型开放式架构

Monitoring and forecastingRegional ecotypePrediction modelOpen architecture products

《安徽农业科学》 2026 (10)

190-196,237,8

国家重点研发计划(2022YFD1400400)四川省科技计划资助(2023YFN0074).

10.3969/j.issn.0517-6611.2026.10.037

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