Developing field-based phenotyping platforms for canola

开发双低油菜籽现场表型平台

• 批准号: 514648-2017
• 负责人: Fotouhi, Reza
• 金额: $ 1.46万
• 依托单位: University of Saskatchewan
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=696336
• 关键词: Developing; field; based; phenotyping; platforms

The main purpose of this project is to develop field-based phenotyping (FBP) mobile platforms for Canola crop for rapid assessment of multiple quantitative plant traits. The objective is to develop platforms to be attached to a tractor or an existing wheeled mobile robot developed by PI. Proximal sensing tools and GPS referencing will be integrated to utilize mobile platforms that are low cost, flexible, and applicable to contrasting crop species. A key concept for this research is to integrate streams of data from multiple sensors to increase both the accuracy and number of traits that can be quantified for field grown plants. The developed FBP system, and associated algorithms will be applied to examine multiple quantitative traits in canola. The field platform will be designed, fabricated, and tested in a laboratory setting and evaluated in crop breeding nurseries of Cargill in Saskatchewan, Alberta, and Manitoba. Upon successful testing, the platform will be used in breeding and research applications. Automation of manual breeding process, sensor selection, and mobile robot navigation in canola breeding setting are part of this project. The milestones for this project are: 1. Test of the 1st generation boom; 2. Developing software for data management; 3. Development and test of the 2nd generation boom; 4. Development and test of the 3rd generation boom; 5. Vibration control of the booms; 6. Automation of navigation of the system; 7. Writing papers/reports. The results will be published in technical journals and will be presented in technical conferences. Upon completion of this project some of the most popular high-throughput phenotyping features will be used automatically to achieve precision phenotype in crop plants. The focus of this project will be on canola because of their importance for Saskatchewan/Alberta/Canada economy.

本项目的主要目的是开发油菜作物田间表型（FBP）移动的平台，用于快速评估多个植物数量性状。我们的目标是开发平台连接到拖拉机或现有的轮式移动的机器人开发的PI。近端传感工具和GPS参考将被集成，以利用低成本、灵活且适用于不同作物品种的移动的平台。 这项研究的一个关键概念是整合来自多个传感器的数据流，以提高田间种植植物可量化性状的准确性和数量。所开发的FBP系统和相关算法将被应用于检测油菜的多个数量性状。现场平台将 在实验室环境中设计、制造和测试，并在萨斯喀彻温省、阿尔伯塔省和马尼托巴省的嘉吉作物育种苗圃中进行评估。测试成功后，该平台将用于育种和研究应用。人工育种过程的自动化，传感器的选择，和移动的机器人导航油菜育种设置是这个项目的一部分。 该项目的里程碑是：1。第一代吊杆的测试; 2.开发数据管理软件; 3.第二代吊杆的研制和试验; 4.第三代吊杆的研制和试验; 5.臂架的振动控制; 6.导航系统的自动化; 7。写论文/报告。 研究结果将在技术期刊上发表，并在技术会议上介绍。 该项目完成后，一些最流行的高通量表型特征将自动用于实现作物植物的精确表型。由于油菜对萨斯喀彻温省/阿尔伯塔省/加拿大经济的重要性，本项目的重点将放在油菜上。