Potato Leaf Disease Detection Method is based on a CNN model with a Genetic Algorithm
DOI:
https://doi.org/10.70454/JRICST.2025.20107Keywords:
Potato leaf diseases, Convolutional Neural Networks, Disease prediction, Genetic AlgorithmAbstract
This paper puts forward an approach that combines Convolutional Neural Networks (CNNs) and Genetic Algorithm (GA) to detect accurately and quickly the diseases that affect potato leaves swiftly and accurately. The model of the CNN is employed for automated feature extraction from the images of leaves which are pivotal in differentiating between the healthy and the infected leaves. Optimization of CNN hyper parameters, like learning rate, the number of layers, and dimensions of filters, is not only time-consuming but also challenging to find optimal values, and genetic algorithms for the optimal values of the parameters of the Convolutional Neural Network. A genetic algorithm uses an iterative search process that aims to optimize a population of models of Convolutional Neural Networks over several generations. It achieves this through the use of optimal models to perform crossover and mutation hence efficiently searching for the optimal configuration of hyperparameters. The above combine will improve the performance of the model which leads to better performance in detecting the variety of diseases attacking the potato leaves, such as early blight and late blight. In this paper CNN model utilizing a genetic algorithm attains an accuracy of 98.3% in 50 epochs.
References
[1] Angayarkanni D, Jayasimman L , Recognition of Disease in Leaves Using Genetic Algorithm and Neural Network Based Feature Selection. Indian Journal of Science and Technology.. 2023, 16(19): 1444-1452. https://doi.org/10.17485/IJST/v16i19.218
[2] H. Ghosh, I. S. Rahat, K. Shaik, S. Khasim, and M. Yesubabu, “Potato Leaf Disease Recognition and Prediction using Convolutional Neural Networks”, EAI Endorsed Scal Inf Syst, vol. 10, no. 6, Sep. 2023.
[3] Gülmez, B. A Comprehensive Review of Convolutional Neural Networks based Disease Detection Strategies in Potato Agriculture. Potato Res. (2024). https://doi.org/10.1007/s11540-024-09786-1
[4] Chittabarni Sarkar, Deepak Gupta, Umesh Gupta, Barenya Bikash Hazarika, Leaf disease detection using machine learning and deep learning: Review and challenges, Applied Soft Computing, Volume 145,2023, 110534, ISSN 1568-4946, https://doi.org/10.1016/j.asoc.2023.110534.
[5] Demilie, W.B. Plant disease detection and classification techniques: a comparative study of the performances. J Big Data 11, 5 (2024). https://doi.org/10.1186/s40537-023-00863-9
[6] R. Thilagavathy, Daksh Chanchlani, Tushar Krishna; Potato leaf disease detection using CNN. AIP Conf. Proc. 29 July 2024; 3075 (1): 020005. https://doi.org/10.1063/5.0217672
[7] Vengaiah, C. ., & Konda, S. R. . (2023). A Review on Tomato Leaf Disease Detection using Deep Learning Approaches . International Journal on Recent and Innovation Trends in Computing and Communication, 11(9s), 647–664. https://doi.org/10.17762/ijritcc.v11i9s.7479
[8] Munjal, Deepkiran, et al. "A Systematic Review on the Detection and Classification of Plant Diseases Using Machine Learning." IJSI vol.11, no.1 2023: pp.1-25. http://doi.org/10.4018/IJSI.315657
[9] Pasalkar J, Gorde G, More C, Memane S, Gaikwad V. Potato Leaf Disease Detection Using Machine Learning. Curr Agri Res 2023; 11(3). doi : http://dx.doi.org/10.12944/CARJ.11.3.23
[10] A. Srivastava, B. S. Rawat, P. Bajpai and S. A. Dhondiyal, "Potato Leaf Disease Detection Method Based on the YOLO Model," 2024 4th International Conference on Data Engineering and Communication Systems (ICDECS), Bangalore, India, 2024, pp. 1-5, doi: 10.1109/ICDECS59733.2023.10502511.
[11] P. Patil, N. Yaligar and S. M. Meena, "Comparision of Performance of Classifiers - SVM, RF and ANN in Potato Blight Disease Detection Using Leaf Images," 2017 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), Coimbatore, India, 2017, pp. 1-5, doi: 10.1109/ICCIC.2017.8524301.
[12] Manna, S, V Jalodia, K Kumar, V Tripathi, S Sharma, and D Arora, ‘Predicting Preeminent Machine Learning Approach on Stars’, in Proceedings of International Conference on Technological Advancements in Computational Sciences, ICTACS 2022, 2022, pp. 587–91
[13] Pant, J, R P Pant, M Kumar Singh, D Pratap Singh, and H Pant, ‘Analysis of Agricultural Crop Yield Prediction Using Statistical Techniques of Machine Learning’, Materials Today: Proceedings, 46 (2021), 10922–26
[14] Nazir, T.; Iqbal, M.M.; Jabbar, S.; Hussain, A.; Albathan, M. EfficientPNet—An Optimized and Efficient Deep Learning Approach for Classifying Disease of Potato Plant Leaves. Agriculture 2023, 13, 841. https://doi.org/10.3390/agriculture13040841
[15] Chowdhury, M.E.H.; Rahman, T.; Khandakar, A.; Ayari, M.A.; Khan, A.U.; Khan, M.S.; Al-Emadi, N.; Reaz, M.B.I.; Islam, M.T.; Ali, S.H.M. Automatic and Reliable Leaf Disease Detection Using Deep Learning Techniques. AgriEngineering 2021, 3, 294-312. https://doi.org/10.3390/agriengineering3020020
[16] R. Kumar, A. Chug, A. P. Singh, and D. Singh, “A Systematic Analysis of Machine Learning and Deep Learning Based Approaches for Plant Leaf Disease Classification: A Review,” Journal of Sensors, vol. 2022, pp. 1–13, Jul. 2022, doi: 10.1155/2022/3287561.
[17] Shafik, W., Tufail, A., De Silva Liyanage, C. et al. Using transfer learning-based plant disease classification and detection for sustainable agriculture. BMC Plant Biol 24, 136 (2024). https://doi.org/10.1186/s12870-024-04825-y
[18] Hatice Catal Reis and Veysel Turk. 2024. Potato leaf disease detection with a novel deep learning model based on depthwise separable convolution and transformer networks. Eng. Appl. Artif. Intell. 133, PC (Jul 2024). https://doi.org/10.1016/j.engappai.2024.108307
[19] Vengaiah, C. ., & Konda, S. R. . (2023). A Review on Tomato Leaf Disease Detection using Deep Learning Approaches . International Journal on Recent and Innovation Trends in Computing and Communication, 11(9s), 647–664. https://doi.org/10.17762/ijritcc.v11i9s.7479
[20] Munjal, Deepkiran, et al. "A Systematic Review on the Detection and Classification of Plant Diseases Using Machine Learning." IJSI vol.11, no.1 2023: pp.1-25. http://doi.org/10.4018/IJSI.315657
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Vikash Sawan, Renu Kumari, Kumari Jugnu (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
