Modern Approach Towards Crop Disease Prediction


  • Sumit Latiyan
  • Harendra Singh Negi
  • Sushil Chandra Dimri
  • Himanshu Kargeti


Agriculture, Accuracy, Disease, Yield, Clustering


India is a large country. India has a very large dependence on agriculture. Government and farmers in India keep on trying and implementing new techniques for increasing crop production and the yield of the available crop. Machine learning along with AI are one of the most common and popular technologies that are being used by our government and private firms for making predictions of various things in various sectors like automobile, agriculture, healthcare. The yield of the crops is largely dependent on factors like weather, fertilizer, pesticide, soil and rain. A plant can be affected by a disease any time from the time of harvesting and sowing. This paper discusses how implementation of machine learning in various fields like agriculture can be largely beneficial. We can find a disease from which a plant is suffering using the dataset of images and machine learning techniques. This work will help farmers
who are new and will guide them towards recognition of disease so that effective measures could be taken to prevent its spread. 




How to Cite

Sumit Latiyan, Harendra Singh Negi, Sushil Chandra Dimri, & Himanshu Kargeti. (2023). Modern Approach Towards Crop Disease Prediction . Elementary Education Online, 20(3), 3795–3802. Retrieved from




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