当前位置: X-MOL 学术Comput. Electron. Agric. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Toward near-real-time forecasts of airborne crop pests: Aphid invasions of cereal grains in North America
Computers and Electronics in Agriculture ( IF 8.3 ) Pub Date : 2020-12-01 , DOI: 10.1016/j.compag.2020.105861
Tomasz E. Koralewski , Hsiao-Hsuan Wang , William E. Grant , Joseph H. LaForest , Michael J. Brewer , Norman C. Elliott , John K. Westbrook

Abstract Airborne invasions of crop pests pose a significant challenge in agriculture. Novel infestations, such as the recently observed invasion of sugarcane aphid [Melanaphis sacchari (Zehntner) (Hemiptera:Aphididae)] on sorghum [Sorghum bicolor (L.) Moench] in the Great Plains of the U.S., emerge rapidly and require fast management actions to mitigate economic losses. Areawide integrated pest management has been a recognized strategic response to such problems. Management tactics may benefit from analysis of pest infestation data and from predictive simulation modeling. Within such a framework, a predictive simulation model could provide short- and long-term decision support. We describe a prototype of a computational framework that could be used to forecast sugarcane aphid invasions of sorghum in near-real-time, as supported by timely field reports on current aphid infestation status. Within the framework, a modeling platform that simulates spread of aphid infestations of sorghum is linked to EDDMapS, a web-based mapping system for documenting invasive species and agronomic pest distributions. The interconnectivity of the modeling process and sorghum field sampling through EDDMapS allows for regular updates of the internal states of the model, which support short-term infestation forecasts based on field data feeds. Practical application of the system could support informed short-term decisions on pesticide application and field sampling, as well as longer-term decisions regarding crop variety deployment.

中文翻译:

对空气传播的作物害虫进行近实时预测:蚜虫入侵北美谷物

摘要 农作物害虫的空中入侵给农业带来了重大挑战。新的虫害,例如最近观察到的甘蔗蚜虫 [Melanaphis sacchari (Zehntner) (Hemiptera:Aphididae)] 在美国大平原的高粱 [Sorghum bicolor (L.) Moench] 上的入侵,迅速出现并需要快速的管理行动以减轻经济损失。区域综合虫害管理已成为对此类问题的公认战略反应。管理策略可能受益于有害生物侵扰数据的分析和预测模拟建模。在这样的框架内,预测模拟模型可以提供短期和长期的决策支持。我们描述了一个计算框架的原型,该框架可用于近乎实时地预测甘蔗蚜虫入侵高粱,得到关于当前蚜虫感染状况的及时现场报告的支持。在该框架内,模拟高粱蚜虫侵扰传播的建模平台与 EDDMapS 相关联,EDDMapS 是一种基于网络的绘图系统,用于记录入侵物种和农艺害虫分布。通过 EDDMapS 建模过程和高粱田间采样的互连允许模型的内部状态的定期更新,这支持基于田间数据馈送的短期侵染预测。该系统的实际应用可以支持关于农药应用和田间取样的知情短期决策,以及关于作物品种部署的长期决策。一个模拟高粱蚜虫侵扰传播的建模平台与 EDDMapS 相关联,EDDMapS 是一个基于网络的绘图系统,用于记录入侵物种和农艺害虫分布。通过 EDDMapS 建模过程和高粱田间采样的互连允许模型的内部状态的定期更新,这支持基于田间数据馈送的短期侵染预测。该系统的实际应用可以支持关于农药应用和田间取样的知情短期决策,以及关于作物品种部署的长期决策。一个模拟高粱蚜虫侵扰传播的建模平台与 EDDMapS 相关联,EDDMapS 是一个基于网络的绘图系统,用于记录入侵物种和农艺害虫分布。通过 EDDMapS 建模过程和高粱田间采样的互连允许模型的内部状态的定期更新,这支持基于田间数据馈送的短期侵染预测。该系统的实际应用可以支持关于农药应用和田间取样的知情短期决策,以及关于作物品种部署的长期决策。通过 EDDMapS 建模过程和高粱田间采样的互连允许模型的内部状态的定期更新,这支持基于田间数据馈送的短期侵染预测。该系统的实际应用可以支持关于农药应用和田间取样的知情短期决策,以及关于作物品种部署的长期决策。通过 EDDMapS 建模过程和高粱田间采样的互连允许模型的内部状态的定期更新,这支持基于田间数据馈送的短期侵染预测。该系统的实际应用可以支持关于农药应用和田间取样的知情短期决策,以及关于作物品种部署的长期决策。
更新日期:2020-12-01
down
wechat
bug