Survey on Plant Diseases Prediction using Machine learning for better Crop Yield

Abstract

Agriculture is a process of growing crops, soil cultivating, it provides food and fabric and helps for growing country's economy. In India more than 50% of people directly and indirectly depend on the agriculture. For developing agriculture, main interceptions are weather hazards and the crop diseases. Weather hazards cannot be prevented, but the loss that occurs due to crop diseases can be reduced. This can be achieved by identifying the crop disease as early as possible and it is also important to identify the type of crop diseases for preventing the spreading of the disease. In India, we have 160 million hectares of arable land and it is second largest country after the United States. Identifying the crop diseases by human action manually is practically difficult and it is hard to identify the type of crop diseases. So, many researchers involved in to identify the crop diseases based on the image processing for helping the real-time gadgets which can be used to identify the crop disease and its types. This survey focuses on the investigation on the different surveys carried out and work related to the crop disease identification and detection based on the image processing. Computer vision and image processing-based work will help to detect of crop diseases along with many practical based applications like drones, IoT based devices etc. In recent studies most of the works are depending on the machine learning and deep learning-based image processing on various studies of predictions. After analyzing the related work on crop detection based on image processing, most of the works achieved better results based on deep learning algorithms compared to the machine learning algorithms.