Abstract Sudden death syndrome (SDS), a fungal infection in soybean caused by Fusarium virguliforme, greatly affects the plant health and in some cases, can cause yield losses of more than 70%. Infected plants are scored by visual assessment based on severity and extent of infection. This manual process is time intensive and not practical for large acreages. Diseased and stress in plants show elevated canopy temperatures that can potentially lead to identification of unhealthy plants without manual scoring. The infection decreases nutrient distribution causing stress that results in internal plant temperature to increase. Thermal infrared (TIR) sensors have the ability to measure the emitted radiation of an object in the infrared region of the electromagnetic spectrum to estimate canopy temperatures. However, TIR sensors have not yet been utilized to capture changes in canopy temperatures to detect SDS in soybean. Therefore, the goal of this study was to (1) use a TIR sensor to assess plant health and vitality, and (2) evaluate canopy temperatures over the growing season to quantify disease development. A thermal infrared camera was mounted on a small unmanned aerial system to capture aerial imagery over the growing season. The first flight was achieved once SDS foliar symptoms began initial development. The remaining three flights occurred before, during, and after full pod fill when symptoms had reached their apex. Results show increasing correlations over the four days. Elevated canopy temperature changes were observed on canopies at early SDS symptom development. Symptoms at the end of the growing season displayed strong correlations to the canopy temperature with ρ = 0.7404. Disease severity showed the strongest correlation throughout the four flights with the last at ρ = 0.7245. The four flights exhibit a decreasing trend with Spearman's rho (R2 = 0.86 for disease severity). Therefore, thermal imaging can be utilized to detect diseased plots. Future studies will be conducted to understand how to mitigate for SDS using thermal detection.

中文翻译：

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远程热红外成像快速筛查大豆猝死综合征

摘要 猝死综合征（SDS）是一种由镰刀菌引起的大豆真菌感染，严重影响植物健康，在某些情况下，可造成70%以上的产量损失。基于感染的严重性和程度，通过视觉评估对感染的植物进行评分。该手动过程是时间密集型的并且对于大面积不实用。植物中的病害和压力显示冠层温度升高，这可能导致无需手动评分即可识别不健康的植物。感染减少了养分分布，造成压力，导致植物内部温度升高。热红外 (TIR) 传感器能够测量物体在电磁光谱红外区域发出的辐射，以估计冠层温度。然而，TIR 传感器尚未用于捕获冠层温度的变化以检测大豆中的 SDS。因此，本研究的目标是 (1) 使用 TIR 传感器评估植物健康和活力，以及 (2) 评估生长季节的冠层温度以量化疾病的发展。一个热红外相机安装在一个小型无人机系统上，以捕捉生长季节的航拍图像。一旦 SDS 叶面症状开始初步发展，就实现了第一次飞行。当症状达到顶点时，剩余的三个飞行发生在豆荚装满之前、期间和之后。结果显示在四天内相关性增加。在 SDS 症状发展的早期，在树冠上观察到了升高的树冠温度变化。生长季节结束时的症状显示出与冠层温度的强相关性，ρ = 0.7404。疾病严重程度在四次飞行中表现出最强的相关性，最后一次在 ρ = 0.7245。四次飞行表现出 Spearman's rho 下降的趋势（疾病严重程度的 R2 = 0.86）。因此，热成像可用于检测病区。未来将进行研究以了解如何使用热检测减轻 SDS。