Detection and Classification of Diseases in Rice Crops from Its Leaves by Using Machine Learning Algorithm

Diseases and pests are affecting rice crops globally which is becoming a major threat to our food security. Loss of rice crops needs to be prevented to avoid any disruptions in the food supply. Due to the lack of infrastructure in many parts of the world, rapid identification and classification of diseases in rice crops were not possible. But with the advancement of technologies in terms of computer applications such as Machine Learning (ML), Artificial Intelligence (AI), and Smart Computing techniques, diagnosis of diseases in rice crops can be made possible. Technology is getting smarter nowadays, so implementation of these technologies would help the agricultural sector to accept the new changes and move on from its traditional ways. There are instances where manual examination of rice crops are not possible, so these technologies help a lot. In this paper, we have presented a type of supervised machine learning algorithm called Convolution Neural Networking (CNN), which was used for the classification and identification of the diseases affecting the rice crops. Further with the help of Keras, Python and TensorFlow the huge sample dataset collected was helpful in prediction of the diseases.