Home Latest Tomorrow’s expertise is being developed right now (Part 1) – Ohio Ag Net | Ohio’s Country Journal

Tomorrow’s expertise is being developed right now (Part 1) – Ohio Ag Net | Ohio’s Country Journal

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Tomorrow’s expertise is being developed right now (Part 1) – Ohio Ag Net | Ohio’s Country Journal

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

As you’re studying this, researchers at The Ohio State University are growing the expertise you’ll be utilizing in your farm tomorrow, due to your Ohio Soybean Check-off. From the usage of Artificial Intelligence and Scouting Drones to simpler sprayer tip choice, your Ohio Soybean Check-off is offering the funds to assist these new applied sciences turn into actuality.

Anyone who has sprayed a soybean crop with a fungicide or insecticide in mid-summer is aware of the problem of getting the spray to penetrate the crop cover. Variable plant top, environmental situations akin to wind pace and course adjustments can impression the effectiveness of the appliance. Dr. Erdal Ozkan is a Professor within the Department of Agricultural Engineering at The Ohio State University. Dr. Ozkan is researching methods to cut back pesticide use and drift whereas growing utility effectiveness via the choice of the correct spray ideas. He can also be evaluating the traits of row spacing and plant inhabitants regarding efficient spray protection. “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,” mentioned Dr. Ozkan. Effectively getting the pesticide to penetrate the cover with the right droplet dimension is essential for a profitable utility. The analysis will embody leaf space index measurements, spray drift assessments and droplet dimension measurements for the varied nozzles, and airflow distribution and turbulence measurements contained in the soybean cover.  

Dr. Sami Khanal is an Assistant Professor within the Department of Agricultural Engineering at The Ohio State University. Her analysis focuses on agricultural distant sensing applied sciences.

Farmers who’ve waded via a subject of waist excessive tangled soybeans to scout for bugs and illness within the late July and early August humidity will respect new analysis within the space of UAV based mostly distant sensing expertise. Dr. Sami Khanal is an Assistant Professor within the Department of Agricultural Engineering at The Ohio State University. Her analysis focuses on agricultural distant sensing applied sciences. Using UAV’s to precisely assess soybean defoliation by bugs and evaluating totally different UAV-mounted sensors. Dr. Khanal is growing fashions on how aerial observations correspond to precise harm within the subject. This can save money and time whereas defending yield.

The use of distant sensing applied sciences (akin to satellites and drones) can present well timed and prices efficient strategies for amassing and monitoring cowl crop well being. This info might be scaled to inside a subject or expanded to a whole watershed. The information collected is being utilized by researchers to determine subject situations that may maximize cereal rye cowl crop biomass and promote soil well being and agricultural productiveness. Dr. Khanal is evaluating the usefulness of this imagery and growing fashions to estimate the cereal rye cowl 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,” mentioned Khanal. This is vital relating to precisely estimating crop top 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,” mentioned Khanal.

Dr. Khanal can also be researching how drone-based options can support within the identification of site-specific components that contribute to excessive soybean yields. Khanal desires to offer high-resolution maps to determine areas that will want handled individually from the remainder of the sector to attain these excessive 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,” mentioned Khanal. “With this information the farmer can create a planting prescription map or other management prescriptions.”

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