Research Article

A Transfer Learning-Based Efficient Model for the Detection of Plant Leaf Diseases

Volume: 31 Number: 4 September 30, 2025
  • Zunaira Zainab
  • Rabbia Mahum *
  • Emad Abouel Nasr
  • Mohammad Shehab
  • Haseeb Hassan
  • Mohammed El-meligy

A Transfer Learning-Based Efficient Model for the Detection of Plant Leaf Diseases

Abstract

Plant disease control is necessary in agriculture since it can result in considerable crop yield losses. To reduce damage, quick diagnosis and categorization of plant leaf diseases is required; unfortunately, this process takes a lot of time and needs human efforts. To deal with these issues, a novel computerized approach for fast observation and categorization is required. There exist methodologies based on Deep Learning (DL) techniques that make use of an easily accessible dataset, namely The Plant Village Dataset. However, they may fail to recognize the diseases on unseen data due to less diverse feature extraction. Therefore, this research proposed a plant disease detector based on Deep Learning model using images of leaves and can identify several plant diseases. First, we perform image preprocessing operations. Second, Convolutional Neural Network (CNN) having several convolution and pooling layers is employed and the results are evaluated with existing DL models with varying hyper-parameters. After training, the model is carefully evaluated to validate the findings. We conducted several trials using the proposed model and attained testing accuracy of 97.6%

Keywords

References

  1. Afsharpour P, Zoughi T, Deypir M & Zoqi M J (2024). Robust deep learning method for fruit decay detection and plant identification: enhancing food security and quality control. Frontiers in Plant Science, 15, 1366395.
  2. Albahar M (2023). A survey on deep learning and its impact on agriculture: Challenges and opportunities. Agriculture 13(3): 540
  3. Altieri M A (1995). Agroecology: the science of sustainable agricultura. Boulder: Westview Press Inc. 433 pp
  4. Anand R, Veni S & Aravinth J (2016). An application of image processing techniques for detection of diseases on brinjal leaves using k-means clustering method. Paper presented at the 2016 international conference on recent trends in information technology (ICRTIT).
  5. Bajpai C, Sahu R & Naik K J (2023). Deep learning model for plant-leaf disease detection in precision agriculture. International Journal of Intelligent Systems Technologies and Applications 21(1): 72-91
  6. Biswas S, Jagyasi B, Singh B P & Lal M (2014). Severity identification of potato late blight disease from crop images captured under uncontrolled environment. Paper presented at the 2014 IEEE Canada international humanitarian technology conference-(IHTC).
  7. Brahimi M, Boukhalfa K & Moussaoui A (2017). Deep learning for tomato diseases: classification and symptoms visualization. Applied Artificial Intelligence 31(4): 299-315
  8. Brahimi M, Mahmoudi S, Boukhalfa K & Moussaoui A (2019). Deep interpretable architecture for plant diseases classification. Paper presented at the 2019 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA).

Details

Primary Language

English

Subjects

Agricultural Biotechnology Diagnostics

Journal Section

Research Article

Authors

Zunaira Zainab This is me
Pakistan

Emad Abouel Nasr This is me
Saudi Arabia

Mohammad Shehab This is me
Jordan

Haseeb Hassan This is me
China

Mohammed El-meligy This is me
Jordan

Publication Date

September 30, 2025

Submission Date

February 8, 2025

Acceptance Date

May 21, 2025

Published in Issue

Year 2025 Volume: 31 Number: 4

APA
Zainab, Z., Mahum, R., Nasr, E. A., Shehab, M., Hassan, H., & El-meligy, M. (2025). A Transfer Learning-Based Efficient Model for the Detection of Plant Leaf Diseases. Journal of Agricultural Sciences, 31(4), 981-997. https://doi.org/10.15832/ankutbd.1635917
AMA
1.Zainab Z, Mahum R, Nasr EA, Shehab M, Hassan H, El-meligy M. A Transfer Learning-Based Efficient Model for the Detection of Plant Leaf Diseases. J Agr Sci-Tarim Bili. 2025;31(4):981-997. doi:10.15832/ankutbd.1635917
Chicago
Zainab, Zunaira, Rabbia Mahum, Emad Abouel Nasr, Mohammad Shehab, Haseeb Hassan, and Mohammed El-meligy. 2025. “A Transfer Learning-Based Efficient Model for the Detection of Plant Leaf Diseases”. Journal of Agricultural Sciences 31 (4): 981-97. https://doi.org/10.15832/ankutbd.1635917.
EndNote
Zainab Z, Mahum R, Nasr EA, Shehab M, Hassan H, El-meligy M (September 1, 2025) A Transfer Learning-Based Efficient Model for the Detection of Plant Leaf Diseases. Journal of Agricultural Sciences 31 4 981–997.
IEEE
[1]Z. Zainab, R. Mahum, E. A. Nasr, M. Shehab, H. Hassan, and M. El-meligy, “A Transfer Learning-Based Efficient Model for the Detection of Plant Leaf Diseases”, J Agr Sci-Tarim Bili, vol. 31, no. 4, pp. 981–997, Sept. 2025, doi: 10.15832/ankutbd.1635917.
ISNAD
Zainab, Zunaira - Mahum, Rabbia - Nasr, Emad Abouel - Shehab, Mohammad - Hassan, Haseeb - El-meligy, Mohammed. “A Transfer Learning-Based Efficient Model for the Detection of Plant Leaf Diseases”. Journal of Agricultural Sciences 31/4 (September 1, 2025): 981-997. https://doi.org/10.15832/ankutbd.1635917.
JAMA
1.Zainab Z, Mahum R, Nasr EA, Shehab M, Hassan H, El-meligy M. A Transfer Learning-Based Efficient Model for the Detection of Plant Leaf Diseases. J Agr Sci-Tarim Bili. 2025;31:981–997.
MLA
Zainab, Zunaira, et al. “A Transfer Learning-Based Efficient Model for the Detection of Plant Leaf Diseases”. Journal of Agricultural Sciences, vol. 31, no. 4, Sept. 2025, pp. 981-97, doi:10.15832/ankutbd.1635917.
Vancouver
1.Zunaira Zainab, Rabbia Mahum, Emad Abouel Nasr, Mohammad Shehab, Haseeb Hassan, Mohammed El-meligy. A Transfer Learning-Based Efficient Model for the Detection of Plant Leaf Diseases. J Agr Sci-Tarim Bili. 2025 Sep. 1;31(4):981-97. doi:10.15832/ankutbd.1635917

Journal of Agricultural Sciences is published as open access journal. All articles are published under the terms of the Creative Commons Attribution License (CC BY).