Keywords : Crop disease
European Journal of Molecular & Clinical Medicine,
2020, Volume 7, Issue 9, Pages 1168-1183
Almost all over the world, the economy mainly depends on the production of food.
Computer vision technology plays a pivotal role in the field of agriculture. The dream of this
research is to produce successful crops in the agricultural sector. Successful farming can
increase crop production in terms of both quality and quantity. The farming performs eight
major phases which begin from crop selection to harvesting. At any of these phases, the
disease and pest may destroy plants. However, the leaves are found to be the most damaged
part in disease identification. A lot of articles are taken out for the survey that endorses the
mechanism of image processing and deep learning for the detection and classification of
diseases from the crop leaves. This survey provides an overview of the pros and cons of all
such articles on various research aspects. The effectiveness of state-of-the-art methods is
explored to identify the techniques that seem to work well across different crops. This paper
indicates that algorithms like Support Vector Machine and Neural Network play an important
role in the crop disease identification and classification.