{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T19:48:06Z","timestamp":1780516086130,"version":"3.54.1"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2025,10,3]],"date-time":"2025-10-03T00:00:00Z","timestamp":1759449600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,10,3]],"date-time":"2025-10-03T00:00:00Z","timestamp":1759449600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Iran J Comput Sci"],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1007\/s42044-025-00338-5","type":"journal-article","created":{"date-parts":[[2025,10,3]],"date-time":"2025-10-03T08:12:36Z","timestamp":1759479156000},"page":"2663-2673","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["HyFPlantNet: hybrid feature-based plant disease classification network"],"prefix":"10.1007","volume":"8","author":[{"given":"Deepkiran","family":"Munjal","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mrinal","family":"Pandey","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laxman","family":"Singh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,10,3]]},"reference":[{"key":"338_CR1","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1007\/s12571-017-0659-1","volume":"9","author":"S Savary","year":"2017","unstructured":"Savary, S., Bregaglio, S., Willocquet, L., Gustafson, D., Mason D\u2019Croz, D., Sparks, A., Castilla, N., Djurle, A., Allinne, C., Sharma, M., et al.: Crop health and its global impacts on the components of food security. Food Security 9, 311\u2013327 (2017)","journal-title":"Food Security"},{"key":"338_CR2","first-page":"9","volume":"9","author":"TN Liliane","year":"2020","unstructured":"Liliane, T.N., Charles, M.S.: Factors affecting yield of crops. Agronomy-climate change & food security 9, 9\u201324 (2020)","journal-title":"Agronomy-climate change & food security"},{"key":"338_CR3","doi-asserted-by":"publisher","first-page":"100083","DOI":"10.1016\/j.atech.2022.100083","volume":"3","author":"A Ahmad","year":"2023","unstructured":"Ahmad, A., Saraswat, D., Gamal, A.: A survey on using deep learning techniques for plant disease diagnosis and recommendations for development of appropriate tools. Smart Agricultural Technology 3, 100083 (2023)","journal-title":"Smart Agricultural Technology"},{"key":"338_CR4","volume-title":"Plant Diseases","author":"RS Singh","year":"2018","unstructured":"Singh, R.S.: Plant Diseases. Oxford and IBH Publishing, Oxford (2018)"},{"issue":"6","key":"338_CR5","doi-asserted-by":"publisher","first-page":"2342","DOI":"10.3390\/su12062342","volume":"12","author":"\u00c1 Mesterh\u00e1zy","year":"2020","unstructured":"Mesterh\u00e1zy, \u00c1., Ol\u00e1h, J., Popp, J.: Losses in the grain supply chain: causes and solutions. Sustainability 12(6), 2342 (2020)","journal-title":"Sustainability"},{"key":"338_CR6","doi-asserted-by":"crossref","unstructured":"Dutta, A., Munjal, D.: The $$\\lambda $$nf problem. In: International Conference on Cybersecurity in Emerging Digital Era, pp. 327\u2013334 (2022). Springer","DOI":"10.1007\/978-981-99-5080-5_28"},{"key":"338_CR7","doi-asserted-by":"crossref","unstructured":"Kumar, P.K., Munjal, D., Rani, S., Dutta, A., Voumik, L.C., Ramamoorthy, A.: Unified view of damage leaves planimetry & analysis using digital images processing techniques. In: 2023 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES), pp. 100\u2013105 (2023). IEEE","DOI":"10.1109\/CISES58720.2023.10183468"},{"key":"338_CR8","doi-asserted-by":"crossref","unstructured":"Dutta, A., Kumar, P.K.: Aeroponics: An artificial plant cultivation technique. Authorea Preprints (2023)","DOI":"10.22541\/au.167701276.63098263\/v1"},{"key":"338_CR9","doi-asserted-by":"crossref","unstructured":"Dutta, A., Kumar, P.K., De, A., Kumar, P., Harshith, J., Soni, Y.: Maneuvering machine learning algorithms to presage the attacks of fusarium oxysporum on cotton leaves. In: 2023 2nd Edition of IEEE Delhi Section Flagship Conference (DELCON), pp. 1\u20137 (2023). IEEE","DOI":"10.1109\/DELCON57910.2023.10127436"},{"key":"338_CR10","doi-asserted-by":"crossref","unstructured":"Solanki, S., Chouhan, S.S., Dwivedi, A., Singh, U.P., Patel, R.K.: Leveraging deep learning for the identification and categorization of fruit diseases. In: 2024 IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies (INSPECT), pp. 1\u20136 (2024). IEEE","DOI":"10.1109\/INSPECT63485.2024.10896118"},{"key":"338_CR11","doi-asserted-by":"crossref","unstructured":"Jamgaonkar, S., Gowda, J.S., Chouhan, S.S., Patel, R.K., Pandey, A.: An analysis of different yolo models for real-time object detection. In: 2024 4th International Conference on Sustainable Expert Systems (ICSES), pp. 951\u2013955 (2024). IEEE","DOI":"10.1109\/ICSES63445.2024.10763020"},{"key":"338_CR12","doi-asserted-by":"publisher","first-page":"109795","DOI":"10.1016\/j.compeleceng.2024.109795","volume":"120","author":"RK Patel","year":"2024","unstructured":"Patel, R.K., Chaudhary, A., Chouhan, S.S., Pandey, K.K.: Mango leaf disease diagnosis using total variation filter based variational mode decomposition. Comput. Electr. Eng. 120, 109795 (2024)","journal-title":"Comput. Electr. Eng."},{"key":"338_CR13","doi-asserted-by":"crossref","unstructured":"Voumik, L.C., Karthik, R., Ramamoorthy, A., Dutta, A.: A study on mathematics modeling using fuzzy logic and artificial neural network for medical decision making system. In: 2023 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES), pp. 492\u2013498 (2023). IEEE","DOI":"10.1109\/CISES58720.2023.10183534"},{"key":"338_CR14","doi-asserted-by":"crossref","unstructured":"Phiphatkamtorn, P., Jitanan, S.: Enhancing hybrid classification for plant diseases with deep feature selection based on analytical entropy and statistical method. IEEE Access (2025)","DOI":"10.1109\/ACCESS.2025.3569760"},{"key":"338_CR15","doi-asserted-by":"crossref","unstructured":"Shafik, W., Tufail, A., Liyanage De\u00a0Silva, C., Awg Haji Mohd\u00a0Apong, R.A.: A novel hybrid inception-xception convolutional neural network for efficient plant disease classification and detection. Scientific Reports 15(1), 3936 (2025)","DOI":"10.1038\/s41598-024-82857-y"},{"key":"338_CR16","doi-asserted-by":"crossref","unstructured":"Zhou, C., Zhang, X.: Plant disease identification under imbalanced dataset using hybrid deep learning method. Journal of The Institution of Engineers (India): Series A 106(1), 19\u201329 (2025)","DOI":"10.1007\/s40030-024-00851-z"},{"issue":"2","key":"338_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10489-024-05990-1","volume":"55","author":"K Anand","year":"2025","unstructured":"Anand, K., Jain, B., Mittal, H., Yadav, V.K.: Qefs: a novel plant disease prediction approach using quantum-inspired evolutionary feature selection. Appl. Intell. 55(2), 1\u201323 (2025)","journal-title":"Appl. Intell."},{"key":"338_CR18","doi-asserted-by":"crossref","unstructured":"babu Nuthalapati, S., Mathew, M.P., et al.: Swingnet: A hybrid swin transform-googlenet framework for real-time grape leaf disease classification. Procedia Computer Science 258, 1629\u20131639 (2025)","DOI":"10.1016\/j.procs.2025.04.394"},{"issue":"14","key":"338_CR19","doi-asserted-by":"publisher","first-page":"41727","DOI":"10.1007\/s11042-023-16925-2","volume":"83","author":"V Kondekar","year":"2024","unstructured":"Kondekar, V., Bodhe, S.: Automation in plant pathology: optimized attentional capsule_bilstm optimized with chaotic sparrow algorithm for colour feature-based plant disease detection. Multimedia Tools and Applications 83(14), 41727\u201341760 (2024)","journal-title":"Multimedia Tools and Applications"},{"key":"338_CR20","doi-asserted-by":"crossref","unstructured":"Burger, W., Burge, M.J.: Scale-invariant feature transform (sift). In: Digital Image Processing: An Algorithmic Introduction, pp. 709\u2013763. Springer, New York (2022)","DOI":"10.1007\/978-3-031-05744-1_25"},{"key":"338_CR21","doi-asserted-by":"crossref","unstructured":"Saraswathi, D., Sharmila, G., Srinivasan, E.: An automated diagnosis system using wavelet based sfta texture features. In: International Conference on Information Communication and Embedded Systems (ICICES2014), pp. 1\u20135 (2014). IEEE","DOI":"10.1109\/ICICES.2014.7034123"},{"key":"338_CR22","first-page":"160","volume":"11","author":"K Gangadharan","year":"2020","unstructured":"Gangadharan, K., Kumari, G.R.N., Dhanasekaran, D., Malathi, K.: Automatic detection of plant disease and insect attack using effta algorithm. Int. J. Adv. Comput. Sci. Appl. 11, 160\u2013169 (2020)","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"key":"338_CR23","doi-asserted-by":"crossref","unstructured":"Roy, P., Dutta, S., Dey, N., Dey, G., Chakraborty, S., Ray, R.: Adaptive thresholding: A comparative study. In: 2014 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT), pp. 1182\u20131186 (2014). IEEE","DOI":"10.1109\/ICCICCT.2014.6993140"},{"key":"338_CR24","doi-asserted-by":"publisher","first-page":"536","DOI":"10.7717\/peerj-cs.536","volume":"7","author":"N Iqbal","year":"2021","unstructured":"Iqbal, N., Mumtaz, R., Shafi, U., Zaidi, S.M.H.: Gray level co-occurrence matrix (glcm) texture based crop classification using low altitude remote sensing platforms. PeerJ Computer Science 7, 536 (2021)","journal-title":"PeerJ Computer Science"},{"issue":"4","key":"338_CR25","doi-asserted-by":"publisher","first-page":"392","DOI":"10.12928\/biste.v6i4.9286","volume":"6","author":"H Nugroho","year":"2024","unstructured":"Nugroho, H., Pramudito, W.A., Laksono, H.S., et al.: Gray level co-occurrence matrix (glcm)-based feature extraction for rice leaf diseases classification. Buletin Ilmiah Sarjana Teknik Elektro 6(4), 392\u2013400 (2024)","journal-title":"Buletin Ilmiah Sarjana Teknik Elektro"},{"issue":"17","key":"338_CR26","doi-asserted-by":"publisher","first-page":"50381","DOI":"10.1007\/s11042-023-17446-8","volume":"83","author":"MA Khan","year":"2024","unstructured":"Khan, M.A., AlGhamdi, M.A.: An intelligent and fast system for detection of grape diseases in rgb, grayscale, ycbcr, hsv and l* a* b* color spaces. Multimedia Tools and Applications 83(17), 50381\u201350399 (2024)","journal-title":"Multimedia Tools and Applications"},{"key":"338_CR27","unstructured":"Hughes, D., Salath\u00e9, M., et al.: An open access repository of images on plant health to enable the development of mobile disease diagnostics. arXiv preprint arXiv:1511.08060 (2015)"},{"key":"338_CR28","doi-asserted-by":"publisher","first-page":"106410","DOI":"10.1016\/j.compag.2021.106410","volume":"190","author":"R Gao","year":"2021","unstructured":"Gao, R., Wang, R., Feng, L., Li, Q., Wu, H.: Dual-branch, efficient, channel attention-based crop disease identification. Comput. Electron. Agric. 190, 106410 (2021)","journal-title":"Comput. Electron. Agric."},{"key":"338_CR29","unstructured":"Lee, S., Park, B., Kim, D., Seo, K.: Artificial intelligence-based heritage tree disease diagnosis using transfer learning: A case study of zelkova serrata. HCI, 211\u2013219 (2024)"},{"key":"338_CR30","doi-asserted-by":"crossref","unstructured":"Dutta, A., Kumar, P.K., Lakshmanan, K., Ghosh, S.: Sadak: Simple, and automatic detection of accidents on roads using kolmogorov-arnold networks. International Journal of Information Technology, 1\u20138 (2025)","DOI":"10.1007\/s41870-024-02381-0"},{"issue":"6","key":"338_CR31","doi-asserted-by":"publisher","first-page":"951","DOI":"10.3390\/electronics11060951","volume":"11","author":"H-C Chen","year":"2022","unstructured":"Chen, H.-C., Widodo, A.M., Wisnujati, A., Rahaman, M., Lin, J.C.-W., Chen, L., Weng, C.-E.: Alexnet convolutional neural network for disease detection and classification of tomato leaf. Electronics 11(6), 951 (2022)","journal-title":"Electronics"},{"issue":"6","key":"338_CR32","doi-asserted-by":"publisher","first-page":"1633","DOI":"10.3390\/agronomy13061633","volume":"13","author":"SR Shah","year":"2023","unstructured":"Shah, S.R., Qadri, S., Bibi, H., Shah, S.M.W., Sharif, M.I., Marinello, F.: Comparing inception v3, vgg 16, vgg 19, cnn, and resnet 50: a case study on early detection of a rice disease. Agronomy 13(6), 1633 (2023)","journal-title":"Agronomy"}],"container-title":["Iran Journal of Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42044-025-00338-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s42044-025-00338-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42044-025-00338-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T09:09:30Z","timestamp":1765357770000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s42044-025-00338-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,3]]},"references-count":32,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["338"],"URL":"https:\/\/doi.org\/10.1007\/s42044-025-00338-5","relation":{},"ISSN":["2520-8438","2520-8446"],"issn-type":[{"value":"2520-8438","type":"print"},{"value":"2520-8446","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,3]]},"assertion":[{"value":"19 April 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 September 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 October 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}