Deep Learning and Machine Learning Techniques for Apple Leaf Disease Recognition: A Systematic Review and Future Directions

The new generations of exploring automated quality assessment of fruits and vegetables in post-harvest processing based on machine vision, hyperspectral imaging and deep learning applications. We examine the technical issues and challenges associated with the implementation of such technologies in quality control systems and their role in achieving efficiency and sustainability. They also pointed out the enabling role of AI, IoT, and big data in scalable, low-cost robotic solutions. This review highlights research gaps that need to be addressed and presents future directions for optimization of automated systems for post-harvest food quality assessment through analysis of the current state of research.