Plant Disease Identification Using Deep Learning: A Systematic Review

Agriculture contributes majorly in the Indian economy being the most important aspect of it. Often the plants suffer from many diseases which may be dependent on climatic conditions and pests which further degrades the quality of the crop. Early and accurate detection of disease in plants is very crucial step in depicting the overall yield of the crop, as this can increase the yield and productivity of the crop by a great margin. In the current climatic conditions, to obtain the superior quality crop is getting difficult day by day as the plants suffer from different diseases. To solve the problem of early and accurate detection image processing has come up with various techniques to find best and suitable ways. This paper presents a review to examine the power of these techniques in detection for plant diseases and add in the agriculture advancement. This survey enfolds larger scope of deep learning in the future research while detecting plant diseases along with improvised performance and accuracy. This paper also states certain challenges which still exist in the detection of diseases in plants and opens some areas of research for the researchers. Various problems in the field of dataset collection have been addressed. Some possible solutions also have been suggested which can help the accuracy to increase for a model.