{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T17:47:43Z","timestamp":1791395263546,"version":"4.3.3"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,7,5]],"date-time":"2026-07-05T00:00:00Z","timestamp":1783209600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T00:00:00Z","timestamp":1791158400000},"content-version":"vor","delay-in-days":92,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100004242","name":"Princess Nourah Bint Abdulrahman University","doi-asserted-by":"publisher","award":["PNURSP2026R760"],"award-info":[{"award-number":["PNURSP2026R760"]}],"id":[{"id":"10.13039\/501100004242","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-026-60523-9","type":"journal-article","created":{"date-parts":[[2026,7,5]],"date-time":"2026-07-05T14:15:16Z","timestamp":1783260916000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Automatic prediction of cotton leaf\u2019s diseases using deep learning techniques"],"prefix":"10.1038","volume":"16","author":[{"given":"Muhammad","family":"Naeem","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad","family":"Ibrahim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8681-6382","authenticated-orcid":false,"given":"Nadeem","family":"Sarwar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oumaima","family":"Saidani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0594-5877","authenticated-orcid":false,"given":"Asma","family":"Irshad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad Shadab Alam","family":"Hashmi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad Tayyab","family":"Qammar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,5]]},"reference":[{"key":"60523_CR1","doi-asserted-by":"publisher","unstructured":"Memon, M. S., Kumar, P. & Iqbal, R. Meta Deep Learn Leaf Disease Identification Model for Cotton Crop. Computers 11 (7). https:\/\/doi.org\/10.3390\/computers11070102 (Jul. 2022).","DOI":"10.3390\/computers11070102"},{"key":"60523_CR2","unstructured":"Abade, A. S., Ferreira, P. A. & Vidal, F. B. Plant Diseases recognition on images using Convolutional Neural Networks: A Systematic Review, Sep. [Online]. (2020). Available: http:\/\/arxiv.org\/abs\/2009.04365"},{"key":"60523_CR3","unstructured":"Sarwar, R. et al. Acta Scientific AGRICULTURE (ISSN: 2581-365X) Detection and Classification of Cotton Leaf Diseases Using Faster R-CNN on Field Condition Images."},{"key":"60523_CR4","doi-asserted-by":"publisher","unstructured":"Vishnoi, V. K., Kumar, K. & Kumar, B. A comprehensive study of feature extraction techniques for plant leaf disease detection. Multimed Tools Appl. 81 (1), 367\u2013419. https:\/\/doi.org\/10.1007\/s11042-021-11375-0 (Jan. 2022).","DOI":"10.1007\/s11042-021-11375-0"},{"key":"60523_CR5","doi-asserted-by":"publisher","unstructured":"Pan, S. J. & Yang, Q. A survey on transfer learning, (2010). https:\/\/doi.org\/10.1109\/TKDE.2009.191","DOI":"10.1109\/TKDE.2009.191"},{"key":"60523_CR6","doi-asserted-by":"publisher","unstructured":"Islam, M. M. et al. A deep learning model for cotton disease prediction using fine-tuning with smart web application in agriculture. Intell. Syst. Appl. 20 https:\/\/doi.org\/10.1016\/j.iswa.2023.200278 (Nov. 2023).","DOI":"10.1016\/j.iswa.2023.200278"},{"key":"60523_CR7","doi-asserted-by":"publisher","unstructured":"Azath, M., Zekiwos, M. & Bruck, A. Deep Learning-Based Image Processing for Cotton Leaf Disease and Pest Diagnosis, Journal of Electrical and Computer Engineering, vol. 2021, (2021). https:\/\/doi.org\/10.1155\/2021\/9981437","DOI":"10.1155\/2021\/9981437"},{"key":"60523_CR8","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/9367778","author":"BM Patil","year":"2021","unstructured":"Patil, B. M. & Burkpalli, V. A Perspective View of Cotton Leaf Image Classification Using Machine Learning Algorithms Using WEKA. Hindawi Ltd. https:\/\/doi.org\/10.1155\/2021\/9367778 (2021).","journal-title":"Hindawi Ltd."},{"key":"60523_CR9","doi-asserted-by":"publisher","unstructured":"Peyal, H. I. et al. Cotton Leaf Disease Detection and Classification Using Lightweight CNN Architecture, in 12th International Conference on Electrical and Computer Engineering, ICECE, Institute of Electrical and Electronics Engineers Inc., 2022, pp. 413\u2013416., Institute of Electrical and Electronics Engineers Inc., 2022, pp. 413\u2013416. (2022). https:\/\/doi.org\/10.1109\/ICECE57408.2022.10088570","DOI":"10.1109\/ICECE57408.2022.10088570"},{"issue":"2","key":"60523_CR10","first-page":"550","volume":"11","author":"A Bin Naeem","year":"2023","unstructured":"Bin Naeem, A. et al. Deep Learning Models for Cotton Leaf Disease Detection with VGG-16. Int. J. Intell. Syst. Appl. Eng. 11 (2), 550\u2013556 (2023).","journal-title":"Int. J. Intell. Syst. Appl. Eng."},{"key":"60523_CR11","doi-asserted-by":"publisher","unstructured":"Nazeer, R. et al. Detection of cotton leaf curl disease\u2019s susceptibility scale level based on deep learning. J. Cloud Comput. 13 (1). https:\/\/doi.org\/10.1186\/s13677-023-00582-9 (Dec. 2024).","DOI":"10.1186\/s13677-023-00582-9"},{"key":"60523_CR12","doi-asserted-by":"publisher","unstructured":"Nadeem, R. M. Machine Learning Model of Plant Disease Prediction: Cotton Leaf Curl Virus (CLCV) on Cotton Crop, Quaid-e-Awam University Research Journal of Engineering, Science & Technology, vol. 20, no. 2, pp. 1\u201310, Dec. (2022). https:\/\/doi.org\/10.52584\/qrj.2002.01","DOI":"10.52584\/qrj.2002.01"},{"key":"60523_CR13","unstructured":"Pechuho, N., Khan, Q. & Kalwar, S. Cotton Crop Disease Detection using Machine Learning via Tensorflow."},{"key":"60523_CR14","doi-asserted-by":"publisher","unstructured":"Shakeel, W., Ahmad, M. & Mahmood, N. Early Detection of Cercospora Cotton Plant Disease by Using Machine Learning Technique, in 30th International Conference on Computer Theory and Applications, ICCTA 2020 - Proceedings, Institute of Electrical and Electronics Engineers Inc., Dec. pp. 44\u201348. (2020). https:\/\/doi.org\/10.1109\/ICCTA52020.2020.9477693","DOI":"10.1109\/ICCTA52020.2020.9477693"},{"key":"60523_CR15","doi-asserted-by":"publisher","first-page":"805","DOI":"10.1109\/JRFID.2022.3206841","volume":"6","author":"Y Tao","year":"2022","unstructured":"Tao, Y. et al. Cotton Disease Detection Based on ConvNeXt and Attention Mechanisms. IEEE J. Radio Freq. Identif. 6, 805\u2013809. https:\/\/doi.org\/10.1109\/JRFID.2022.3206841 (2022).","journal-title":"IEEE J. Radio Freq. Identif."},{"key":"60523_CR16","doi-asserted-by":"publisher","unstructured":"Caldeira, R. F., Santiago, W. E. & Teruel, B. Identification of cotton leaf lesions using deep learning techniques. Sensors 21 (9). https:\/\/doi.org\/10.3390\/s21093169 (May 2021).","DOI":"10.3390\/s21093169"},{"key":"60523_CR17","doi-asserted-by":"publisher","unstructured":"Amin, J., Anjum, M. A., Sharif, M., Kadry, S. & Kim, J. Explainable Neural Network for Classification of Cotton Leaf Diseases, Agriculture (Switzerland), vol. 12, no. 12, Dec. (2022). https:\/\/doi.org\/10.3390\/agriculture12122029","DOI":"10.3390\/agriculture12122029"},{"key":"60523_CR18","doi-asserted-by":"publisher","unstructured":"Tahir, M. S., Yaqoob, A., Hamid, H. & Latif, R. M. A. A Methodology of Customized Dataset for Cotton Disease Detection Using Deep Learning Algorithms, in Proceedings\u2009\u2013\u20092022 International Conference on Frontiers of Information Technology, FIT 2022, Institute of Electrical and Electronics Engineers Inc., pp. 77\u201381. (2022). https:\/\/doi.org\/10.1109\/FIT57066.2022.00024","DOI":"10.1109\/FIT57066.2022.00024"},{"key":"60523_CR19","doi-asserted-by":"publisher","unstructured":"Anwar, S., Kolachi, A. R., Baloch, S. K. & Soomro, S. R. Bacterial Blight and Cotton Leaf Curl Virus Detection Using Inception V4 Based CNN Model for Cotton Crops, in 5th IEEE International Image Processing, Applications and Systems Conference, IPAS, Institute of Electrical and Electronics Engineers Inc., 2022., Institute of Electrical and Electronics Engineers Inc., 2022. (2022). https:\/\/doi.org\/10.1109\/IPAS55744.2022.10052835","DOI":"10.1109\/IPAS55744.2022.10052835"},{"key":"60523_CR20","doi-asserted-by":"publisher","unstructured":"Abdul Majid et al. Forecasting Cotton Whitefly Population Using Deep Learning. J. Comput. Biomedical Inf. 4 (01). https:\/\/doi.org\/10.56979\/401\/2022\/67 (Dec. 2022).","DOI":"10.56979\/401\/2022\/67"},{"key":"60523_CR21","unstructured":"Jenifa, R. R. V. R. A. Cotton Leaf Disease Classification using Deep Convolution Neural Network for Sustainable Cotton Production."},{"key":"60523_CR22","unstructured":"Bin Naeem, A. et al. International Journal of Intelligent Systems and Applications in Engineering Deep Learning Models for Cotton Leaf Disease Detection with VGG-16. [Online]. Available: www.ijisae.org."},{"key":"60523_CR23","doi-asserted-by":"publisher","unstructured":"Adhao, A. S. & Pawar, V. R. Automatic Cotton Leaf Disease Diagnosis and Controlling Using Raspberry Pi and IoT, in Lecture Notes in Networks and Systems, vol. 19, Springer, 157\u2013167. doi: https:\/\/doi.org\/10.1007\/978-981-10-5523-2_15. (2018).","DOI":"10.1007\/978-981-10-5523-2_15"},{"key":"60523_CR24","unstructured":"Rahman, A. et al. Cotton Leaf Disease Detection: An Integration of CBAM with Deep Learning Approaches, [Online]. (2025). Available: https:\/\/data.mendeley.com\/datasets\/b3jy2p6k8w\/2"},{"key":"60523_CR25","unstructured":"Naeem, M. Cotton-Leaf-Diseases Dataset (2024). https:\/\/github.com\/mnaeem303\/Cotton-Leaf_Disease-Dataset), Feb."},{"key":"60523_CR26","unstructured":"cotton leaf disease dataset. Accessed: May 21. [Online]. (2024). Available: https:\/\/www.kaggle.com\/datasets\/seroshkarim\/cotton-leaf-disease-dataset\/data"},{"key":"60523_CR27","unstructured":"Simonyan, K. & Zisserman, A. Very deep convolutional networks for large-scale image recognition, 3rd International Conference on Learning Representations, ICLR 2015 - Conference Track Proceedings, pp. 1\u201314, (2015)."},{"key":"60523_CR28","unstructured":"Loukadakis, M., Cano, J. & O\u2019Boyle, M. Accelerating deep neural networks on low power heterogeneous architectures. In 11th International Workshop on Programmability and Architectures for Heterogeneous Multicores (MULTIPROG-2018). (2018), January."},{"issue":"2","key":"60523_CR29","doi-asserted-by":"publisher","first-page":"190","DOI":"10.1080\/02564602.2022.2068681","volume":"40","author":"L Singh","year":"2023","unstructured":"Singh, L., Janghel, R. R. & Sahu, S. P. An Empirical Review on Evaluating the Impact of Image Segmentation on the Classification Performance for Skin Lesion Detection. IETE Tech. Rev. (Institution Electron. Telecommunication Eng. India). 40 (2), 190\u2013201. https:\/\/doi.org\/10.1080\/02564602.2022.2068681 (2023).","journal-title":"IETE Tech. Rev. (Institution Electron. Telecommunication Eng. India)"},{"key":"60523_CR30","doi-asserted-by":"publisher","unstructured":"Zheng, Y., Yang, C. & Merkulov, A. Breast cancer screening using convolutional neural network and follow-up digital mammography. Proc. SPIE 10669, Computational Imaging III, 1066905 (14 May 2018); (2018)., May https:\/\/doi.org\/10.1117\/12.2304564","DOI":"10.1117\/12.2304564"},{"key":"60523_CR31","doi-asserted-by":"publisher","unstructured":"Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J. & Wojna, Z. Rethinking the Inception Architecture for Computer Vision, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2016-Decem, pp. 2818\u20132826, (2016). https:\/\/doi.org\/10.1109\/CVPR.2016.308","DOI":"10.1109\/CVPR.2016.308"},{"key":"60523_CR32","doi-asserted-by":"publisher","unstructured":"Tursunov, J. & Memonova, G. Detection of Cotton Plant Disease Using CNN, in International Conference on Information Science and Communications Technologies (ICISCT), IEEE, Sep. 2022, pp. 1\u20134., IEEE, Sep. 2022, pp. 1\u20134. (2022). https:\/\/doi.org\/10.1109\/ICISCT55600.2022.10146785","DOI":"10.1109\/ICISCT55600.2022.10146785"},{"key":"60523_CR33","doi-asserted-by":"crossref","unstructured":"Pechuho, N., Khan, Q. & Kalwar, S. Cotton Crop Disease Detection using Machine Learning via Tensorflow, PakJET, vol. 3, no. 2, pp. 126\u2013130, Sep. (2020).","DOI":"10.51846\/vol3iss2pp126-130"}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-60523-9","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-60523-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-60523-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T00:09:29Z","timestamp":1791158969000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-60523-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,5]]},"references-count":33,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["60523"],"URL":"https:\/\/doi.org\/10.1038\/s41598-026-60523-9","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,5]]},"assertion":[{"value":"12 August 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 June 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 July 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"30818"}}