Turkey: artificial intelligence will be used to assess yield of fruit trees

In the provinces of Siirt and Mersin in the southeast of Turkey, artificial intelligence was first used to monitor the yield of gardens.

“The project for monitoring the ripening of fruits and the diagnostics of rot using UAV” Prepared by graduate student Abdurrahman Yyldyrym.

Consulting support was provided by the presenter of the Department of Electrical Engineering and Electronics Faculty of the University of Siiirt (SIU) Melikh Kunjan and teacher of the Department of Electrical Engineering and Electronics of the Faculty of Engineering, Architecture and Design of the University of Bartyn Burak Yyldyrym.

as part of the project to determine the productivity in grenade and apple gardens in the SIIRAT, as well as in banana and orange trees in MERSIN, the software analyzed 2,223 pictures that made drones.

Kunjan told Anadolu that to obtain reliable data, the drone is used on different days, at different angles, under different weather conditions and light.

According to him, the data obtained allow you to very accurately determine the level of ripeness of fruit and identify cases of decay.

Kunjan considers it possible to develop and transfer Product Prototype to farmers for agricultural monitoring.

At the same time, he emphasized that the drones in the agrarian sector are more used now to spray the crop in sections of sown areas where the tractors cannot drive or other familiar equipment.

In the future, farmers will be able to monitor the ripening time, decay and diseases of fruits and vegetables and increase productivity, he believes.

He said that the most useful data with an accuracy of 97 percent was obtained during the monitoring of oranges and grenades, “We plan to get a patent for the project,” Kunjan added.

Yyldyrym noted that the purpose of the project is to increase the yield and quality of fruits.

The author of the software is convinced that in the future the results of his work will be of great benefit to farmers and enterprises.

According to him, ripe and rotten fruits can be identified due to the fact that the software compares the pictures with the drone with those that were in advance in the database.

“Determining the general condition of the fruits and research on the assessment of yields differ depending on the density of trees and the type of fruit. We will continue to develop such projects,” he added.