A Comprehensive Threat Management Framework for a Crop Biosecurity National Architecture

由病原体豆薯层锈菌（Phakopsora pachyrhizi）引起的大豆锈病通常被称为澳大拉西亚锈病或亚洲锈病，是一种严重的大豆病害，其在世界许多地区造成作物损失，包括亚洲、印度、非洲、澳大利亚以及最近的南美洲。 由于过去十年来大豆锈病在世界范围内的迅速蔓延，引起了人们的广泛关注。根据环境条件和处理策略，亚洲大豆锈病造成的产量损失可能在10%至90%之间。 迫切需要了解作物生物安全系统的现状，确定各组成部分的基线，并寻求提高整个系统反应能力的方法。 这项工作建立在观察的基础上，即有可能在植物出现可见症状前两周检测到大豆中的视觉应激。 这是由于植物的细胞结构是控制近红外范围内叶片反射率的主导因素。 然后可以利用遥感来评估农作物的状况。 将通过遥感和地理空间技术基线对目前的能力进行评估，该基线将提供关于南美洲大豆锈病进展情况的历史视角（环境，气象，文化，时间），定义当前最先进的直接和间接测量大豆锈病，定义全谱（光学、热、雷达后向散射）特征的疾病进展，库存和评估疾病媒介模型，并提供了一个概念性的示范，该系统的组成部分，在一个综合的形式，包括社会和组织对作物安全威胁的反应之间的相互作用。该项目的结果将导致新的战略，以早期发现这种病原体并监测随后的疾病进展，这可能是限制这种疾病的经济影响的关键组成部分。美国大豆生产的疾病。 该系统的架构也可以适用于其他代理。 这种跨学科的研究不仅涉及教师和技术人员，而且涉及本科生。

Soybean rust, caused by the pathogen Phakopsora pachyrhizi and often referred to as Australasian or Asian rust, is a serious disease of soybean that causes crop losses in many parts of the world, including Asia, India, Africa, Australia, and most recently South America. Much concern has arisen because of the rapid spread of soybean rust around the world within the past ten years. Yield losses from Asian soybean rust can range from 10 to 90% depending on environmental conditions and treatment strategies. There is a critical need to understand the current condition of the crop biosecurity system, baseline the various components, and seek ways to enhance the responsiveness of the overall system. The work builds on the observation that it is possible to detect pre-visual stress in soybeans two weeks prior to visible symptoms appearing on the plant. This is due to the fact that a plant's cellular structure is the dominant factor in controlling leaf reflectance in the near infrared range. Remote sensing can then be used to assess the condition of crops. An assessment of current capabilities will be provided by a remote sensing and geospatial technology baseline, which will provide a historical perspective on the progression of soybean rust in South America (environmental, meteorological, cultural, temporal), define the current state-of-the-art for direct and indirect measurements of soybean rust, define the full spectrum (optical, thermal, radar backscatter) characteristics of the disease progression, inventory and assess disease vector models, and provide a conceptual demonstration of the components of the system in an integrated form, including the interplay between social and organizational responses to crop safety threats.Results from this project will lead to new strategies to detect this pathogen early and monitor subsequent disease progression that are likely to be critical components to limiting the economic impact of this disease on U.S. soybean production. The architecture of the system can be adapted to other agents as well. This interdisciplinary research engages not only faculty and technicians, but also undergraduates.