Dr. Erdal Ozkan is a Professor in the Department of Agricultural Engineering at The Ohio State University. Dr. Ozkan is researching ways to reduce pesticide use and drift.

Tomorrow’s technology is being developed today (Part 1)

By Dusty Sonnenberg, CCA, Field Leader, a project of the Ohio Soybean Council and Soybean Check-off

As you are reading this, researchers at The Ohio State University are developing the technology you will be using on your farm tomorrow, thanks to your Ohio Soybean Check-off. From the use of Artificial Intelligence and Scouting Drones to more effective sprayer tip selection, your Ohio Soybean Check-off is providing the funds to help these new technologies become reality.

Anyone who has sprayed a soybean crop with a fungicide or insecticide in mid-summer knows the challenge of getting the spray to penetrate the crop canopy. Variable plant height, environmental conditions such as wind speed and direction changes can impact the effectiveness of the application. Dr. Erdal Ozkan is a Professor in the Department of Agricultural Engineering at The Ohio State University. Dr. Ozkan is researching ways to reduce pesticide use and drift while increasing application effectiveness through the selection of the proper spray tips. He is also evaluating the characteristics of row spacing and plant population concerning effective spray coverage. “We are trying to find a sweet spot so that we have the spray drift problems taken care of and by choosing the right nozzle, we can improve the efficiency of the application. Disease issues are our first concern followed closely by insect pressure. Diseases and insects both like to reside in the lower part of the canopy,” said Dr. Ozkan. Effectively getting the pesticide to penetrate the canopy with the correct droplet size is critical for a successful application. The research will include leaf area index measurements, spray drift assessments and droplet size measurements for the various nozzles, and airflow distribution and turbulence measurements inside the soybean canopy.  

Dr. Sami Khanal is an Assistant Professor in the Department of Agricultural Engineering at The Ohio State University. Her research focuses on agricultural remote sensing technologies.

Farmers who have waded through a field of waist high tangled soybeans to scout for insects and disease in the late July and early August humidity will appreciate new research in the area of UAV based remote sensing technology. Dr. Sami Khanal is an Assistant Professor in the Department of Agricultural Engineering at The Ohio State University. Her research focuses on agricultural remote sensing technologies. Using UAV’s to accurately assess soybean defoliation by insects and evaluating different UAV-mounted sensors. Dr. Khanal is developing models on how aerial observations correspond to actual damage in the field. This can save time and money while protecting yield.

The use of remote sensing technologies (such as satellites and drones) can provide timely and costs effective methods for collecting and monitoring cover crop health. This information can be scaled to within a field or expanded to an entire watershed. The data collected is being used by researchers to identify field conditions that can maximize cereal rye cover crop biomass and promote soil health and agricultural productivity. Dr. Khanal is evaluating the usefulness of this imagery and developing models to estimate the cereal rye cover crop biomass and nutrient composition. “The satellite imagery is only visible and near infrared. The drone sensors create images that are very sensitive and multispectral,” said Khanal. This is important when it comes to accurately estimating crop height and biomass.

“The desired outcome of the project is to generate a very detailed map that allows us to pinpoint high and low cereal rye cover crop biomass and correlate that with images of the soybean crop. We want to estimate the impact of cereal rye biomass on soybean productivity. The preliminary models have 87% accuracy,” said Khanal.

Dr. Khanal is also researching how drone-based solutions can aid in the identification of site-specific factors that contribute to high soybean yields. Khanal wants to provide high-resolution maps to identify areas that may need treated separately from the rest of the field to achieve those high yields.

“The ultimate goal is to develop AI models and a support tool that integrates data from drones and ground scouting that will be used to assist the farmer in decision making based on the cover crop biomass maps,” said Khanal. “With this information the farmer can create a planting prescription map or other management prescriptions.”

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