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International Journal of Agrochemistry

Comparison of Various Methodologies used for Automating Plant Disease Detection using Image Processing

  1. Divyansh Sharma
  2. Pawan Kumar Patidar

Abstract

In India, major of economy and development depends on agriculture, so plant disease detection becomeimportant for us so that if any crop is destroyed due to diseases is known to us prior and we can overcomethe loss of crops due to plant diseases. It is better to catch the disease in the initial phase so that the largescaledamage of crops can be prevented. Traditionally, the diseases incurred via the naked eyes and thenthere is manual processing on the plants to overcome the diseases. Manual process takes lots of time, andit is expensive and required lots of experience. So in order to increase the testing speed, we automate themethodology. So we are using image processing techniques with the combination of various othertechnologies like deep learning, IoT, etc. to reduce the effort and automate the things. This paper has avision to promote the sustainable development and implies the idea of smart city which includes thecombination of IoT (Internet of things, deep-learning, big data, etc.) in the area of agriculture. This paperincludes the comparison of various plant disease detection methods of various techniques.

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