Paper Contents
Abstract
In the modern agricultural and food industry, manual inspection for sorting and grading produce is often inefficient, slow, and prone to human error. This paper presents an automated system for detecting and classifying the quality of fruits and vegetables using image processing and deep learning. By leveraging Convolutional Neural Networks (CNN), the system identifies types, detects colors, estimates sizes, and provides nutritional information such as vitamins, proteins, and carbohydrates. The proposed solution aims to provide a low-cost, high-speed alternative to traditional grading methods, ensuring better handling of produce and compliance with international export standards.
Copyright
Copyright © 2026 Om Shukla, Deval Zade, Darshan Chavhan, Ravish Quadri, Prof. Atul Kapgate, Prof. Jagruti Ghatole, Dr. Sudhir Shelke. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
