PROVEA Precision Agriculture Decision Support System developed by our company in the context of Grape and Olive products was presented in 2018 as TAGEM project with the participation of Izmir Olive Research Institute and Manisa Vineyard Research Institute. The project called Image Processing and Machine Learning Techniques and the Determination of Yield and Damage in Grape and Olives was accepted by the board.
Within the scope of the Project by using machine learning and image processing techniques, it is aimed to determine yield and damage / disease determination in terms of grape and olive products with the help of remote sensing technologies. During the project, the photographs taken from the vineyards and olive orchards are used with the help of UAVs. Studies are being carried out to realize yield estimation with image processing and machine learning techniques. In addition, the existing damage and disease detection studies in grape and olive fields are carried out. The machine learning techniques and classification algorithms developed as a result of the study. It will enable the establishment of a new precision agricultural technology which will be used for the first time in our country’s agricultural sector.
In order to be able to carry out the tests and analyzes of this developed technology, studies are carried out with Manisa Vineyard Research Institute in 35 different vineyards, and with Izmir Olive Research Institute in 23 different Olive Gardens. The first phenological stage measurements on the land were completed. During this measurement period, the researchers who are experts in the field of ground surveys from the Manisa Viticulture Research Institute and the Izmir Olive Research Institute perform ground measurements. Leaf and soil analyzes are performed and interpreted in trial vineyards and olive groves.
The data obtained by using local measurements and remote sensing technology are interpreted by means of machine learning and statistical methods. The studies are performed to estimate the yield and damage / disease detection. The findings of the first phase of the measurements are analyzed and reported. The studies for the software infrastructure which is developed in the second phase of the study are ongoing.
EXECUTIVE INSTITUTION (AVEO)
Nuri Eray ŞAHİN
Alp Aslan KIRKPINAR