Automatic real-time monitoring of fungal spores: the case of Alternaria spp.

被引：0
|
作者：
Sophie Erb
Alexis Berne
Nina Burgdorfer
Bernard Clot
Marie-José Graber
Gian Lieberherr
Christine Sallin
Fiona Tummon
Benoît Crouzy
机构：
[1] MeteoSwiss,Surface Measurements
[2] École Polytechnique Fédérale de Lausanne,Environmental Remote Sensing Laboratory
来源：
Aerobiologia | 2024年 / 40卷
关键词：
Fungal spores; Automatic monitoring; Machine learning; Real-time;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
We present the first implementation of the monitoring of airborne fungal spores in real-time using digital holography. To obtain observations of Alternaria spp. spores representative of their airborne stage, we collected events measured in the air during crop harvesting in a contaminated potato field, using a Swisens Poleno device. The classification algorithm used by MeteoSwiss for operational pollen monitoring was extended by training the system using this additional dataset. The quality of the retrieved concentrations is evaluated by comparison with parallel measurements made with a manual Hirst-type trap. Correlations between the two measurements are high, especially over the main dispersion period of Alternaria spp., demonstrating the potential for automatic real-time monitoring of fungal spores.
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页码：123 / 127
页数：4
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