# title
Field-region and plant-level classification of cotton root rot based on UAV remote sensing

# abstract
Cotton root rot (CRR), caused by the fungus, Phymatotrichopsis omnivora, is a destructive cotton disease that mainly affects the crop in Texas. Once a plant is infected by CRR, it cannot be cured and will die within a few days. However, flutriafol fungicide (Topguard Terra, FMC Agricultural Solutions, Philadelphia, PA) applied at or soon after planting has proven effective at protecting cotton plants from being infected by CRR. Previous research has indicated that CRR will reoccur in the same regions of a field as in past years. Therefore, mapping the CRR-infected area is helpful for precision fungicide application to prevent CRR from appearing. The CRR-infected plants can be detected with aerial remote sensing (RS). As unmanned aerial vehicles (UAVs) have been introduced into agricultural RS, the spatial resolution of farm images has increased significantly, making high-precision CRR classification possible. An unsupervised classification method was developed to detect CRR at the field-region level, and another algorithm based on the Superpixel concept was developed to delineate CRR-infested areas at roughly the single-plant level. Five-band multispectral data were collected with a UAV to test these methods. The results indicated that both the regional and the single-plant level classification achieved high accuracies of 90.8% and 93.5%, respectively.

# publicationOutlet
2019 Boston, Massachusetts July 7- July 10, 2019

# nameOfConference
2019 Boston, Massachusetts July 7- July 10, 2019

# publisher.label
American Society of Agricultural and Biological Engineers (ASABE)

# authorList[]
Wang, T., Thomasson, J. A., Yang, C., & Isakeit, T.