Precision Agriculture Technology and Image Processing for Post-harvest Applications

Precision agriculture is a comprehensive system designed to optimize agricultural production. Using the key elements of information, technology and management, precision agriculture can be used to increase production efficiency, improve product quality and conserve energy. Precision agriculture projects are divided into 2 parts: site specific management (SSM) and postharvest process management (PPM). In present article we used PPM and machine vision technology to sort the tomato into 2 classes. Class A is for fresh using and class B is for processing and making tomato sauce automatically. Knowledge of the physical properties of fruit was necessary. The images of individual tomatoes were captured. Color and textural features of samples were extracted by image processing toolbox of Matlab and were analyzed by statistical software named SPSS. The algorithm was consisted of back ground subtraction, feature extraction and classification. The classification rate was 92% for class A and 100% for class B. The processing speed was 0.67 s