The continuous growth of the global population and rapid scientific advancements have increased the demand for high precision and efficient agricultural practices. Artificial Intelligence (AI) has emerged as a transformative tool to enhance the speed, accuracy, and automation of various agricultural processes. This study reviews the recent applications of AI, particularly image processing and machine vision techniques, in different stages of agricultural production, including planting, plowing, harvesting, and post-harvest operations such as storage, silage preparation, and drying. The findings indicate that AI assisted systems can effectively detect plant diseases, estimate yield, monitor soil and crop conditions, and optimize machinery operations with minimal human interventions. Furthermore, the integration of AI with Internet of Things (IoT) technologies enables real time data collection and intelligent decision making in smart farming systems. Despite the significant process made. Continuous technological development and the emergence of new agricultural challenges highlight the need for further research into advanced image processing algorithms, deep learning models, and data driven optimization approaches. Overall, AI and machine vision technologies have proven to be essential components for achieving sustainable, precise, and intelligent agricultural production.
Moghadam et al. (2025) studied this question.