The Need

Unmanned Aerial Systems (UAS) allow agricultural producers to generate high-resolution crop health data over large areas. UAS generate this data by imaging the upper canopy while flying above row crops. However, most crop health problems originate below the upper portion of the canopy. Most causes of biotic and abiotic stress appear first in the lower canopy, which overhead UAS cannot detect. For this reason, UAS use indirect measures that correlate with disease to make diagnoses instead of directly observing pests and diseased crops. This means that when UAS identify diseased crops it is often too late to take action. Instead, data from UAS are mostly used to quantify post-mortem yield losses. Therefore, the industry standard in reliable stress diagnosis remains in-person scouting. Crop scouts, who inspect crops on foot, can detect pests and disease before the problem is visible in the upper canopy. However, while crop scouts are trained experts, human error and bias result in missed observations. Additionally, scouts visit a relatively small number of sites, resulting in a low-resolution description of diseased areas. This leads to over-application of corrective agents, which places a preventable economic burden on the producer. Furthermore, crop scouts make treatment recommendations based on inspections that are limited to the rows near a field’s border. This results in missed infections, which frequently begin further inside the fields.

The Technology

Dr. Scott Shearer and colleagues from the Ohio State University's College of Food, Agricultural, and Environmental Sciences (CFAES) have developed a camera and sampling probe-equipped UAS and image-processing technology in order to improve crop disease surveillance. Our camera and probe are fastened to an arm that extends down from the UAS body, extending the reach of UAS observation to the crop’s lower canopy. This permits UAS to inspect the lower canopy, which was previously limited to on-foot crop scouting. Therefore, with this technology we have combined the physical advantage of crop scouts with the high-throughput data collection of UAS technology. Additionally, following data collection the technology employs AI-guided image-processing algorithms that accurately identify biotic and abiotic stressors. These processing algorithms are able to quickly diagnose diseases and describe the affected areas. In turn, this facilitates targeted action plans to treat crop malnutrition and disease at unprecedented levels of both speed and precision.

Commercial Applications

• Commercial growers looking to measure crop health

Benefits/Advantages

• Reduces costs associated with applying corrective measures to diseased crops
• Increases the speed of identifying crop diseases
• Reduces yield loss associated with crop diseases
• Combines reliability of in-person crop scouting with high-throughput UAS surveillance