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Rapid detection and precise interventions are essential for sustainable production. We present an AI-driven framework integrating deep learning diagnostics, precision fungicide application, and a digital decision support system (DSS) for field-level SCLB management. Thirteen machine learning (ML) and deep learning (DL) algorithms were evaluated, with VGG16 achieving the highest performance (accuracy 97.0%, precision 0.98, recall 0.96, F1-score\u2009\u2265\u20090.97, AUC-ROC\u2009=\u20091.00). Feature extraction analysis highlighted VGG16\u2019s ability to capture hierarchical disease-specific patterns (score\u2009=\u20090.95), and error- and variance-based assessment confirmed minimal prediction errors (MAE\u2009=\u20090.06, RMSE\u2009=\u20090.16, Explained Variance\u2009=\u20090.90, MBD = \u2212\u20090.02). Confusion matrix analysis revealed only a small number of misclassifications (4 false negatives and 9 false positives), demonstrating excellent generalization. Grad-CAM heatmaps, t-SNE visualization, and learning curves confirmed lesion-focused predictions and feature separability. Two-year field trials (2023 and 2024) validated precision fungicide application (Azoxystrobin 18.2% + Difenoconazole 11.4% SC), reducing disease severity to \u2248\u200910% PDI (86.2% reduction) and increasing grain yield to 83.7 q\/ha (C: B ratio 1:2.41). The Streamlit-based DSS provides actionable, real-time advisories, offering a scalable AI platform for automated disease detection and precision agriculture in maize. The proposed framework can be extended to other foliar diseases and integrated with IoT-based sensing for region-wide advisory systems.\n                  <\/jats:p>","DOI":"10.1038\/s41598-026-38151-0","type":"journal-article","created":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T06:54:11Z","timestamp":1770792851000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Digital decision support integrated with diagnostics and precision fungicide application for Southern Corn Leaf Blight in maize"],"prefix":"10.1038","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5998-0937","authenticated-orcid":false,"given":"G.","family":"Jadesha","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anurag","family":"Dhole","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7194-463X","authenticated-orcid":false,"given":"D.","family":"Deepak","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manjunath","family":"Hubballi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,2,11]]},"reference":[{"issue":"5","key":"38151_CR1","doi-asserted-by":"publisher","first-page":"1295","DOI":"10.1007\/s12571-022-01288-7","volume":"14","author":"O Erenstein","year":"2022","unstructured":"Erenstein, O., Mottaleb, K., Prasanna, B. 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