Journal of Contemporary Issues in Business and Government

Abstract

The identification and classification of the crop leaf diseases plays an essential role in the
cultivation. Plants are the livelihood. Peoples depend entirely on crops for the breathing of
their daily lives. Thus, suitable crop caring should take place. Most research suggests that
the quality of agricultural commodities can be restricted depending on different factors. Crop
diseases include microorganisms and pathogens. The leaf diseases not only reduce crop
growth, the cultivation is also destroyed. Several researchers have been identified crop
leaf diseases using image processing algorithms but it take more time for detection.
Therefore, advanced algorithms are required to identify and classify the crop leaf diseases
automatically with higher accuracy. There are different deep learning algorithms using crop
leaf images developed for automatically detecting the crop leaf diseases in an efficient
manner. In this article, a survey on different deep learning algorithms using image processing
for detecting and classifying the crop or plant leaf diseases is presented. Also, the merits and
demerits of the surveyed algorithms for crop leaves diseases identification are addressed in a
tabular form. Finally, a comprehensive analysis is concluded and future directions are
suggested to increase the accuracy of leaf diseases classification.