杂草信息实时获取技术与设备研究进展

Advance Techniques and Equipments for Real-time Weed Detection

杂草信息的实时获取技术是田间杂草精准控制研究的首要问题,杂草实时获取设备是制约精准除草作业实现的瓶颈。综述了基于光谱、图像和光谱成像技术的杂草实时获取技术与设备的国内外研究现状,以促进精准杂草管理技术在我国的应用和发展。基于光谱的杂草信息获取方法较适用于实时防除作物出苗前的杂草,国外已有WeedSeeker、Weed-IT等杂草传感器。基于图像的杂草信息获取方法较适用于识别行间杂草,国外已有Autopilot、Cam Pilot、Robocrop等视觉导航产品和Robocrop InRow机械除草机防除行内杂草。基于光谱成像的杂草信息获取方法较适用于识别行内杂草,中、澳正联合研发微光子植物判别和杂草控制传感器。需要继续深入研究在复杂的开放式非结构的农田环境中,快速、准确地实时获取农田杂草信息技术。

Real-time infield weed detection is the most important technique of the precision infield weeds control. The real-time weed detection equipment is a key of the site specific weed management. Currently research is being carried out relating to weed sensor based on the spectroscopic, imaging and spectral imaging techniques. Theses advance technologies and equipments were reviewed for application them in China. The weed detection technique based on spectroscopic is suitable for classifying weeds from soil background without crop seedlings, such as the WeedSeeker and Weed-IT. The weed detection technique based on imaging is appropriate for discriminating inter-row weeds, including the Robocrop InRow mechanical weed control machine and the vision navigation product of the Autopilot, Cam Pilot and Robocrop, etc. The weed detection technique based on spectral imaging is more appropriate for distinguishing intra-row weeds, and a joint research on microphotonic plant discrimination and weed control sensor has been done by China and Australia. It is still a continuous project that how to detect infield weeds in real-time and specific under the complex and open field environment.