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

向日葵是一种价值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，因为它可能会因疾病而造成损失。疾病管理计划的一个主要组成部分是及早发现病原体并立即实施控制策略，以将经济损失降至最低。监测和管理是非常劳动密集型的，当症状变得明显时，感染已经根深蒂固，降低了杀菌剂的效果。相比之下，基于传感器的自动化诊断提供了传统视觉筛查的强大替代方案。在这个项目中，我们将检验Ecoation公司开发的高分辨率传感系统在对向日葵中一些最重要的疾病：锈病、拟南芥茎溃烂病(PSC)和菌核病(SHR)进行抗性筛选方面的实用价值。我们还将比较这项技术的效率与一些可用的替代方法，以及最广泛使用的方法-视觉筛选。这些知识将使人们能够制定更准确、更有效的战略来检测和量化可用于精准农业的疾病严重程度。

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.