Cotton Leaf Disease Classification Using Deep Learning based Novel Approach

In India, one of the essential professions in agriculture. Cotton is the best crop out of several and is very important to the nation's agricultural economy. Six million farmers in India depend directly on cotton, while 40-50 million people are employed in the cotton trade and cotton processing. Over the past few decades, the cotton leaf disease has become a significant issue, causing losses in harvests, agricultural activities, and financial resources. Farmers may find it challenging to find a solution if they cannot accurately identify the characteristics of the crop's actual disorder at the outset. This study intended to develop a model to aid in the detection of cotton leaf pests and diseases. In this study, we propose a hybrid strategy based on deep learning. On a data set of 1710 images, the presented model accurately discovers Leaf Curl Disease and Fusarium wilt in cotton plants with an accuracy of 98.9%.