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Early Prediction of Potato Leaf Diseases using ANN Classifier


Affiliations
1 Department of Computer Science & Information Technology, Sam Higginbottom University of Agriculture, Technology & Sciences, Prayagraj-211007, India
2 Krishi Vigyan Kendra, Saharsa-852201, India
 

Potatoes are cultivated in several states of India. Potatoes provides a low-cost energy in human diet. Potatoes are used in industry for making dried food products. Early blight and Late blight are major disease of potato leaf. It is estimated that the major loss occurred in potato yield due to these diseases. In this research, we have collected sample of potato leaf images from Plant Villagedataset. This dataset contains 2152 images of potato leaf. It has 3 class of sample of Healthy Leaf, Early Blight and Late Blight. The 76 features are extracted from these images regarding color, texture and area. The extracted features are used to develop a classifier. The developed classifier is based on neural network for prediction and classification of potato image samples. The Feed Forward Neural Network (FFNN) Model is used for prediction and classification of unknown leaf. The accuracy of model is achieved 96.5%. Classifier is helpful in early and accurate prediction of the leaf diseases of potato crop.

Keywords

Classification; Disease; Image Processing, Feature Extraction, Potato.
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  • Al-Hiary, H., Bani-Ahmad S., Reyalat, M., Braik, M., ALRahamneh , Z. (2011). Fast and Accurate Detection and Classification of Plant Diseases. International Journal of Computer Applications, Volume- 17, No.1, 0975 – 8887.

  • Athanikar, G.,Badar, P.(2016). Potato Leaf Diseases Detection and Classification System, International Journal of Computer Science and Mobile Computing, Vol. 5, Issue. 2, pg.76 – 88.

  • Chahar, R., Soni, P. (2015). A Study of Image Processing in Agriculture for Detect the Plant Diseases, IJCSMC, Vol. 4, Issue. 7, pg.581 – 587.

  • Dacal-Nieto, A., Vazquez-Fernandez, E., Formella, A., Martin, F., Torres-Guijarro, S., González-Jorge, H., (2009). A genetic algorithm approach for feature selection in potatoes classification by computer vision. IEEE, Spain, 2009, 1955-1960.

  • Dickson, M.A., and Bausch, W.C. (1997). Plant recognition using a neural network classifier with size and shape descriptors”, Transactions of the ASAE, vol. 1, pp. 97-102.

  • Durga, N. K., Anuradha, G. (2019). Plant Disease Identification Using SVM and ANN Algorithms, International Journal of Recent Technology and Engineering, Volume-7, Issue5S4, pp. 471-473

  • Mirchandani, S., Pendse, M., Rane, P., Vedula, A. (2018). Plant Disease Detection and Classification Using Image Processing and Artificial Neural Networks. International Research Journal of Engineering and Technology, Volume: 05 Issue: 06, 2859-2864

  • Mohanty, S. P., Hughes, D. P., Salathe, M. (2016). Using Deep Learning for Image-Based Plant Disease Detection. Frontiers in Plant Science. 7:1-10.

  • Patil, J. K., Kumar, R. (2011). Advances in Image Processing for Detection of Plant Diseases. Journal of Advanced Bioinformatics Applications and Research. 2(2):135-141.

  • Raut, S., Fulsunge, A. (2017). Plant Disease Detection in Image Processing Using MATLAB, International Journal of Innovative Research in Science, Engineering and Technology, Vol. 6, Issue 6, 10373-10381.

  • Rowe, R. C., Davis, J. R., Powelson, M. L., Rouse D. I. (1987). Potato Early Dying: Causal Agents and Management. The American Phytopathological Society, Plant Disease. 71 (6): 482-489.


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  • Early Prediction of Potato Leaf Diseases using ANN Classifier

Abstract Views: 211  |  PDF Views: 1

Authors

Kumar Sanjeev
Department of Computer Science & Information Technology, Sam Higginbottom University of Agriculture, Technology & Sciences, Prayagraj-211007, India
Narendra Kumar Gupta
Department of Computer Science & Information Technology, Sam Higginbottom University of Agriculture, Technology & Sciences, Prayagraj-211007, India
W. Jeberson
Department of Computer Science & Information Technology, Sam Higginbottom University of Agriculture, Technology & Sciences, Prayagraj-211007, India
Suneeta Paswan
Krishi Vigyan Kendra, Saharsa-852201, India

Abstract


Potatoes are cultivated in several states of India. Potatoes provides a low-cost energy in human diet. Potatoes are used in industry for making dried food products. Early blight and Late blight are major disease of potato leaf. It is estimated that the major loss occurred in potato yield due to these diseases. In this research, we have collected sample of potato leaf images from Plant Villagedataset. This dataset contains 2152 images of potato leaf. It has 3 class of sample of Healthy Leaf, Early Blight and Late Blight. The 76 features are extracted from these images regarding color, texture and area. The extracted features are used to develop a classifier. The developed classifier is based on neural network for prediction and classification of potato image samples. The Feed Forward Neural Network (FFNN) Model is used for prediction and classification of unknown leaf. The accuracy of model is achieved 96.5%. Classifier is helpful in early and accurate prediction of the leaf diseases of potato crop.

Keywords


Classification; Disease; Image Processing, Feature Extraction, Potato.

References





DOI: https://doi.org/10.13005/ojcst13.0203.11