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Pest occurrence risk assessment and prediction in neighboring fields, crops and soils using crowd-sourced occurrence data
Pest occurrence risk assessment and prediction in neighboring fields, crops and soils using crowd-sourced occurrence data
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机译:使用人群来源的发生数据对邻近田间,作物和土壤中的有害生物发生风险进行评估和预测
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摘要
A pest and disease modeling framework for precision agriculture applies weather information, pest biological characteristics, and crop management data to anonymous crowd-sourced observations of pest presence for a reporting field. A risk assessment profile of pest occurrence for targeted fields in proximity to reporting fields is modeled to generate field-specific measures for pest management of pest infestation. The pest and disease modeling framework matches and filters weather and crop information in infested and pest-free fields based on the anonymous, crowd-sourced reporting of an existing pest presence, by evaluating similarities in pest-relevant data. Fields that are similar to infested fields have the highest risk of infestation, and the modeling framework provides output data in the form of a prediction of pest occurrence based on the risk assessment profile.
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