Using UAV Technology Paired with Multispectral Cameras to Assess Crown Rust Epidemics in Oats

Abstract

Crown rust, caused by Puccinia cornonata f. sp. avenae, is a common disease of oats (Avena sativa) found virtually everywhere oats are cultivated. This disease has caused yield losses of 10 to 40% worldwide. Early detection is important for effective management. A more recently utilized technology in agriculture is unmanned aerial vehicles (UAVs). UAVs, or drones, equipped with cameras are now being used as a resource to take images of fields to identify pests and other issues that may be occurring. Normalized differentiated vegetative index (NDVI) is a numerical indicator used to determine the vegetative health of a field. Tests were conducted at Central Research Station and Dean Lee Research and Extension Center to compare visual crown rust severity ratings to NDVI values. Treatments were arranged in a randomized complete block design (4 replicates). The susceptible cultivar, Brooks, was sprayed with Prosaro fungicide applied at either 146.2mL/ha, 292.3mL/ha, 584.6 mL/ha, 584.6mL/ha applied twice, or a non-sprayed control. Fungicide applications were used to regulate crown rust epidemics. One of the objectives was to determine yield loss associated with different fungicide regimes. The second objective was to determine if NDVI collected by UAV can be correlated with disease severity ratings. There was a significant correlation between disease severity and fungicide rate, with plots sprayed twice with 584.8 mL/ha resulting in less disease than all other plots. There was also a significant negative correlation between NDVI and disease severity at DLREC, but it is not consistent with the other location that the crop showed symptoms later in the growth stage and we were not able to fly to collect data.