Automated Tomato Maturity Grading System using CNN

India is a country that primarily depends on agriculture for livelihood. Agriculture plays a significant role in economic growth and is also remaining as a common economical source. Tomato is one of India’s leading agricultural crops and is marketed across the country. The tomato is a berry of the plant Solanum, Lycopersicum, belonging to the Solanaceae. The species of tomato have originated in the Western South American region and people of Mexico probably started the cultivation. China is one of the largest producers of tomato followed by India. Overall tomato production in the world is around 1,300 lakh tons. Generally, Tomato classification is done manually. But this method is prone to errors on various uncontrollable factors. This paper has proposed an automated tomato maturity classification system that uses convolution neural network (CNN) as a classifier. In our CNN model, three layers are included for achieving a better classification. The performance of our model is very high when compared to traditional approaches.