The technical processes emerged in line with the technological advances contribute to the economical, sustainable and productive industry, which are the goals of plant and animal production. Image processing techniques have become an important tool in facilitating agricultural operations and in bringing alternative solutions to the problems that need to be solved or improved. Thanks to the developed algorithms and software, numerous studies have been carried out by researchers on disease, harmful and weed detection, plant identification and detection, determination of plant stresses, yield estimation, determination of obstacles, determination of distances between the rows and row-tops, classification of soil and land cover, estimation of botanical composition, evaluation of vegetation indexes, green area index, determination of plant growth variability, follow-up of product development, followup of root development, modeling of irrigation management practices, determination of soil moisture in plant production, and monitoring of animal development in a herd, movement skill scoring, measurement of body characteristics, determination of body condition score, monitoring body weight, lameness detection, determination of pain locations, body temperature monitoring, location determination in animal production. Examples of these studies are shown in Table 1. the development of real-time and automated expert systems, autonomous tractors or agricultural machines and agricultural robotics applications have been realized, by applying the experience gained during the implementation of image processing techniques in agriculture together with the machine learning, deep learning, artificial intelligence, modeling and simulation applications (Table 2). For this reason, image processing techniques will continue to be one of the most important agricultural research topics in the present and future. Increasing the quality and productivity of crops in agricultural activities depends on the monitoring the growing plants well and carrying out the necessary operations at the right time. Drone systems, which have a simple technical structure and are easy to use, offer farmers an opportunity to make plans in agricultural activities using their embedded sensors and cameras, providing high quality and 3D images [1]. Image processing techniques are used to extract information from a moving or fixed image captured
