UGA researchers make use of AI to identify early diseases for Vidalia onion production

It’s the Vidalia onion. It is loved across the nationin such a way that it earned an estimated $200 million in farm gate value in 2022 however, it is only grown in twenty counties that surround Vidalia. Vidalia located in southeast Georgia with special soil conditions produce a delicious onion, which is sweeter.

The climate conditions that make this region suitable for growth are ideal for the control of a variety of diseases and pests that affect plants. The onion diseases that can be found in the fields of production can result in severe economic loss to the onion farmers as they reduce the quantity and quality of the onions that are sold.

“Georgians are extremely pleased with the Vidalia onion. Its growers are having tremendous success using the latest management strategies and techniques However, with newer technology, we could improve the quality of life even more,” said Luan Oliveira who is an assistant professor within the Department of Horticulture at the University of Georgia College of Agricultural and Environmental Sciences (CAES).

An inter-disciplinary team comprised of UGA researchers is aiming to improve the productivity of Vidalia onion farmers in Georgia by giving them the capability to detect onions diseases earlier, which will allow them to take management decisions about their crops at crucial moment. The ability, according to researchers are likely to result in an increase in production and quality of the marketable onions, as well as an rise in efficiency and production.

“What that makes this particular project fascinating is the collaboration with CAES as well as the College of Engineering that is supported by an initiative called the UGA Institute for Integrative Precision Agriculture and the team that is integrated that includes research and Extension County agents, faculty and farmers the application of AI for detecting onion disease,” said George Vellidis who is a professor at the CAES Department of Crop and Soil Sciences and Institute faculty.

The process of identifying and detecting diseases poses numerous problems for Georgia’s Vidalia cultivators. The farmers and their advisors can detect and recognize diseases by strolling through the fields. As many fields are vast and have many rows, the task of scouting each row can be the biggest challenge to efficiency. The majority of producers scout smaller portions of a field in order to speed up the process, however this approach leaves the majority of the fields unrestricted.

In the event of a diagnosis of a disease the sprays- either preventive or curative are sprayed across the surface as a measure of precaution as the scope of the disease’s spread is not easily ascertained.

Lu and his research team, together with three of the top Vidalia sweet onion cultivators are using machine learning and artificial intelligence to develop a set of decision-support tools (DSTs) designed for Vidalia sweet onions. Vidalia sweet onion.

“Our DSTs for disease management are a mix of smartphone applications to robot solutions that allow growers and consultants to rapidly scout the entire field and then target curative and prophylactic sprays at areas within the field where disease might have emerged or is emerging,” Lu said.

The growers and their advisors are able to utilize SmartDetect, a mobile application that allows growers and their consultants to use SmartDetect app to spot illnesses that are difficult to identify without specialist skills or equipment. These include the onions, and pink root smut.

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Matthew Agvent

CAES Newswire

Tel: +995 7702387216

Email: [email protected]

www.newswire.caes.uga.edu