Rotten Fruit Disease Detection and Treatment Using Recommended Pesticides

Rotten Fruit Disease Detection and Treatment Using Recommended Pesticides

Sachin Patil, Prajkta Koparkar, Bhagyashri Bajulge, Vinayak Urit, Suyog Chavan
1Professor, Dept. of Computer Engineering, Zeal College of Engineering and Research, Maharashtra, India.

2,3,4,5 Dept. of Computer Engineering, Zeal College of Engineering and Research, Maharashtra, India.

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Abstract - India's largest industry is the fruit industry. The fruit disease causes large losses in productivity, quality, and quantity due to lack of care and improper human inspection. The manual examination is a time-consuming and arduous operation. Using multiple color, texture, and shape feature combinations, an image processing strategy is given for apple fruit disease identification and categorization. Image segmentation, feature extraction (color, texture, and shape), feature combining, and finally, Fruit Disease Detection using Conventional Neural Network (CNN) where Fruits are classified into diseased or normal classes, are the basic steps of the suggested approach. Fruit diseases pose a server threat to agriculture industry production and economic loss. The presence of Illness in the fruit might cause a fruit’s quality and yield to decline too much. Monitoring fruit health and identifying diseases that are present is essential. In agricultural applications, such as disease detection, categorization, and grading, advanced computational approaches have been applied to assist farmers in routine Farm activities with more precision, efficiency, productivity, and cost savings, the classification of disease that improves defect segmentation and fuses color, texture, and shape- based information.

Key Words: CNN, Pesticides, Neural.