多光谱波段选择用于葡萄园病害检测的成像传感器设计——以黄萎病为例

H. Al-Saddik, J. Simon, O. Brousse, F. Cointault
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引用次数: 10

摘要

因此,病害检测和控制是法国葡萄园研究的主要目标之一。人工病害监测繁琐且耗时,因此目前的研究目标是开发一种葡萄园病害自动检测系统。该项目探索了使用嵌入在无人机(UAV)上的高分辨率多光谱相机来识别油田中的感染区域。进行了现场光谱研究,以确定传感器设计的最佳光谱带。最佳模型是所考虑的葡萄品种的函数,并且发现520-600-650-690-730-750-800 nm波段对所有类型的葡萄都是最有效的,总体分类准确率超过94%。
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Multispectral band selection for imaging sensor design for vineyard disease detection: case of Flavescence Dorée
Disease detection and control is thus one of the main objectives of vineyard research in France. Monitoring diseases manually is fastidious and time consuming, so current research aims to develop an automatic detection of vineyard diseases. This project explored the use of a high-resolution multi-spectral camera embedded on a UAV (Unmanned Aerial Vehicle) to identify the infected zones in a field. In-field spectrometry studies were performed to identify the best spectral bands for the sensor design. The best models were found to be the function of the grapevine variety considered and the 520-600-650-690-730-750-800 nm bands were found to be the most efficient for all types of grapevines, with an overall classification accuracy of more than 94%.
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Proceedings of the British Society of Animal Science Proceedings of the XIIIth International Symposium on Ruminant Physiology (ISRP 2019) Proceedings of the British Society of Animal Science Proceedings of the Seventeenth Biennial Conference of the Australasian Pig Science Association (APSA) Proceedings of the 9th Workshop on Modelling Nutrient Digestion and Utilization in Farm Animals (MODNUT)
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