A Comprehensive Threat Management Framework for a Crop Biosecurity National Architecture

大豆锈病是一种严重的大豆病害，由病原菌肿根锈病（Phakopsora pachyrhizi）引起，通常被称为澳大利亚锈病或亚洲锈病，在世界许多地区造成作物损失，包括亚洲、印度、非洲、澳大利亚和最近的南美洲。近十年来，大豆锈病在世界范围内迅速蔓延，引起了人们的广泛关注。根据环境条件和处理策略，亚洲大豆锈病的产量损失可从10%到90%不等。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响应能力的方法。这项工作建立在观察的基础上，即有可能在大豆出现可见症状前两周检测到视觉前应激。这是因为植物的细胞结构是控制叶片近红外反射率的主要因素。然后，遥感可以用来评估作物的状况。遥感和地理空间技术基线将提供对当前能力的评估，该基线将提供关于南美洲大豆锈病进展的历史观点（环境、气象、文化、时间），确定大豆锈病直接和间接测量的当前最新技术，确定疾病进展的全光谱（光学、热、雷达后向散射）特征，盘点和评估病媒模型，并以综合形式提供系统组成部分的概念性演示，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早期发现这种病原体和监测随后的疾病进展的新策略，这可能是限制这种疾病对美国大豆生产的经济影响的关键组成部分。系统的架构也可以适应其他代理。这项跨学科研究不仅涉及教师和技术人员，也涉及本科生。

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.