ABSTRACT
The recent changes in global weather caused by rising surface temperature had a significant effect on the agricultural sector. Rapid changes in the local climate have to lead to a global rise in crop disease and pest epidemics. Crop disease and pests do a great deal of harm to agricultural produce and often impact the livelihood of farming families in a developing county like India where agriculture is an economic backbone. Effective estimation of climatic factors like temperature, humidity, rainfall, and wind speed can often be used to predict the presence of crop disease and pest. An early forecast of disease and pest epidemic often helps in preparing farmers in dealing with a disease outbreak. It also encourages farmers to efficiently use pesticides and fertilizers which when put in excess often lead to water contamination through soil erosion. In this paper, we have surveyed various research work done in the space of crop disease and pest management using machine learning technology; we have also studied about important environmental factors which contribute to the development of disease epidemics and pest attacks.
