ABSTRACT: Tree physiology and condition are closely correlated with the immediate environment and therefore is linked to climate effects in that environment. Automatic seed, plant disease identification and recognition tools have proved to be a valuable source of data that assist decision making in farms. Artificial intelligence tools like Deep learning and Convolutional Neural Network (CNN) are gaining popularity in this field as they provide optimum solution for plant disease identification. Earlier, pest detection was done by manual observation. This method is arduous and prone to error. Several plant diseases cannot be recognized by bare human eyes. Because early disease occurrences are minute in nature. At the same time due to fear of attack of pest/disease, farmer uniformly sprays pesticides/fertilizers in whole farm which may lead to damage of soil as well as plants and also infected to humans as well. In order to improve the quality of production and yield in plants, it is essential to identify the symptoms in their initial stages and treat the diseases. The crop stress index is calculated to indicate plant water status using ambient temperature. In the end we are going to implement this process to prevent the human lives from harmful effects caused by pesticides.
| DOI: 10.17148/IJARCCE.2022.11678