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An Innovative Approach for Crop Disease Detection using Image Processing Technique and Pesticide Suggestion for Effective Crop Cultivation

Parashuram Baraki, Kadukar Dhanashri Mallikarjun, Prema Chougala, Sanmesh Ghongade, Shruthika Narvekar

Abstract


The yield of the crop is important as the farmers are the back bone of our country India. The bacterial attack is going to ruin the early detection of these diseases on leaf and the pomegranate fruit. The proposed framework automatically grades the disease on leaves of crops. The system efficiently instructs Information and Communication Technology (ICT) in Agriculture and hence contributes to Precision Agriculture. Currently, plant pathologists mostly trust on nude eye forecast and a sickness notching scale to mark the ailment. This manual categorizing is not only time taking but also not feasible. Hence, we are proposing an image processing-based approach to automatically grade the disease spread on plant leaves by employing SVM( Support Vector Machine ) classifier to make the decisions. The results are simulated in the Mat lab and it has shown that it has successfully detected the leaf or crop disease and names it. The proposed system can be reliably implemented on the real time scenario.

Keywords: Crop disease, detection, Image Processing, effective crop cultivation

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References


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DOI: https://doi.org/10.37628/ijosct.v4i2.444

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