Crop Leaf Disease Detection in Soybean Crop Using Deep Learning Technique

Agriculture is the backbone of human life. The basic and essential needs of humans are fulfilled by agriculture. Soybean is grown on a large scale in the East Asia region. Now it is also grown in other parts of the world with modern methods. But it is affected by many unpredicted diseases which may lead to a reduction in yields. So, it is essential to identify soybean crop diseases and protect from unpredicted diseases at earlier stages. Most of the farmers are not able to find accurate diseases. Hence, we have developed a mobile application for soybean crop leaf disease detection using Deep Learning. The deep learning Model is built using a Deep Belief Network. We have built a model which can detect mainly three types of diseases of soybean. These diseases are frog eye leaf spots, powdery mildew, and septoria brown spot. After training the model using different CNN architectures, our model got a maximum accuracy of 99%. This application is user-friendly and can detect the disease and also suggest treatment for that disease. This will helpful to farmers save their soybean crops from diseases with minimum effort and maximum accuracy.