A mobile - based Mango Sizing Application II. METHODOLOGY using an Image Processing was developed to address the challenges of manual fruit grading methods in the A. Application Overview agricultural industry. Traditional manual grading is time - consuming and often inconsistent due to human Our Mango Sizing Application — affectionately subject ivity. This application automates mango grading called Mangrade — was built using Cordova and based on size, color, and weight using image processing Android Studio to make it accessible on smartphones. and linear regression models. The application captures It’s designed to be user - friendly: users simply snap a mango images, processes them to extract relevant photo of a mango, and the app does the rest. Behind the features, and classifies them into pr edefined size grades. scenes, it analyzes the image to detect key features like Evaluated using ISO 25010 software quality standards, color and pixel dimensions. Using a linear regression the application scored high in functionality, efficiency, model, the app then estimates the mango’s weight and usability, maintainability, and security. The proposed automatically classifies it into size categories such as solution offers a reliable, fast, and consistent method for Grade A, B, or C. mango c lassification, providing a practical alternative to traditional methods. B . Image Processing and Feature Extraction