ABSTRACT
This chapter reports on the evolution and performance of machine learning with image processing in detecting plant leaf diseases. Plant leaf diseases and harmful insects pose a significant threat to agriculture. A more reliable and faster prediction of leaf diseases in crops could aid in the development of an early treatment method. Modern advanced developments in Machine Learning and its advancements have allowed to extremely improve the performance and accuracy of object detection and recognition systems. Identification of plant diseases using supervised learning and control of plant diseases, detecting nutrient deficiency, controlled irrigation, and controlled use of fertilizers and pesticides are all part of crop management from the early stages to the mature harvest period. If certain diseases are identified in the initial stage can be cured and the proper pesticide usage can help in the proper plant growth. This cannot be done easily efficiently even by the so experienced farmers, so 225-HMP60A moisture sensor is used for monitoring the moisture levels in the soil because having high moisture makes it vulnerable to pest attack.
