Identification of Corresponding Environmental Factors for Fruit Diseases

Abstract

There are various types of pathogens that occur in plants, due to the fact of climate changes, weather changes, seasons changes and the significance of environmental (temperature, humidity, rainfall, etc.) changes. The consequence of plant disease affects our agriculture industry and agriculture sector. It affects our plant growth, production growth, and economic growth throughout the world. So, to prevent the diseases, necessary to understand weather conditions and also identify corresponding environmental factors in plant diseases. Therefore, in this study, analysis of the different types of plant diseases and identification of corresponding environmental factors in plum data using the artificial neural network. Using neural network model to identify the environmental factors and the purpose of the correlation method is to find out the relationship between two variables (the actual value of diseases and the predicted value of diseases). Finally, in result explained detailed to identify the environmental factors in plum data.