Autonomously-Targeted Weed Management System

自主目标杂草管理系统

• 批准号: 537254-2018
• 负责人: Rogers, Kevin
• 金额: $ 1.82万
• 依托单位: Saskatchewan Polytechnic
• 依托单位国家: 加拿大
• 项目类别: Applied Research and Development Grants - Level 1
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=680317
• 关键词: Autonomously; Targeted; Weed; Management; System

In partnership with Expert Systems Inc., Saskatchewan Polytechnic is developing an autonomously-targeted weed management system for the agricultural industry. Weeds tend to grow in clusters and are often absent from large patches of cropland, presenting the possibility of developing a neural network that uses machine learning to identify weeds. Thus, herbicide use can be automated to specifically target weeds, not the crop. The first phase of the project will involve sowing common prairie weeds and crops together in a controlled environment and studying them through hyperspectral imagery in order to develop and train a neural network that can distinguish between them. This will be a highly-marketable breakthrough for Expert Systems and a significant scientific accomplishment for Saskatchewan Polytechnic. The agricultural industry will also benefit by producing crops with vastly reduced herbicide usage.

萨斯喀彻温理工学院与专家系统公司合作，正在开发一种针对农业行业的自主杂草管理系统。杂草往往呈簇状生长，在大片农田中往往看不到杂草，这就为开发一种利用机器学习识别杂草的神经网络提供了可能性。因此，除草剂的使用可以自动地专门针对杂草，而不是作物。该项目的第一阶段将包括在受控环境中播种常见的草原杂草和作物，并通过高光谱图像研究它们，以开发和训练能够区分它们的神经网络。这将是专家系统的一个高度市场化的突破，也是萨斯喀彻温理工学院的一项重大科学成就。农业也将受益于生产大大减少除草剂使用的作物。