Non-invasive method of biotic and abiotic stress detection in sunflowers

向日葵生物和非生物胁迫的非侵入性检测方法

• 批准号: 515372-2017
• 负责人: Rieseberg, Loren
• 金额: $ 1.82万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=640487
• 关键词: Non; invasive; method; biotic; abiotic

Sunflower in a $20 billion oil crop and one of the world's main sources of vegetable oil. However, sunflowercan be a high-risk crop because of potential losses from diseases. A major component of disease managementprograms is early pathogen detection and immediate implementation of control strategies to minimizeeconomic loss. Monitoring and management is very labor intensive and by the time the symptoms becomevisible, the infection has become well-established, diminishing the efficacy of fungicides. In contrast,automated sensor-based diagnostics provides a powerful alternative to conventional visual screening. In thisproject, we will examine the practical utility of high-resolution sensory systems developed by Ecoation forresistance screening of some of the most important diseases in sunflower: rust, Phomopsis stem canker (PSC)and Sclerotinia head rot (SHR). We will also compare efficiency of this technology to some of the availablealternatives, as well as to most widely used method - visual screening. This knowledge will enable thedevelopment of more accurate and efficient strategies for detecting and quantifying disease severity that couldbe used for precision agriculture.

向日葵是价值200亿美元的油料作物，也是世界上植物油的主要来源之一。然而，向日葵可能是一种高风险作物，因为疾病可能造成损失。疾病管理计划的一个主要组成部分是早期病原体检测和立即实施控制策略，以尽量减少经济损失。监测和管理是非常劳动密集型的，当症状变得明显时，感染已经建立，降低了杀菌剂的功效。相比之下，基于传感器的自动诊断为传统的视觉筛查提供了一种强大的替代方案。在这个项目中，我们将研究由Ecoation开发的高分辨率传感系统的实际效用，用于向日葵中一些最重要的疾病的抗性筛选：锈病，拟茎点霉茎溃疡病（PSC）和核盘菌头腐病（SHR）。我们还将比较这项技术的效率，一些availablealternatives，以及最广泛使用的方法-视觉筛选。这些知识将有助于开发更准确和有效的策略，用于检测和量化可用于精准农业的疾病严重程度。