ABSTRACT Banana and plantain ( Musa spp. L.) are fundamental to food security and rural livelihoods across sub‐Saharan Africa, yet production is severely constrained by multiple diseases, with Banana bunchy top virus (BBTV) representing the most devastating viral threat. Inadequate diagnostic infrastructure limits effective management, particularly for asymptomatic infections disseminated through the informal exchange of planting material. This study presents an integrated diagnostic framework combining loop‐mediated isothermal amplification (LAMP) molecular diagnostics with deep learning‐based computer vision for rapid, scalable disease detection under field conditions. A four‐primer LAMP assay targeting the BBTV coat protein gene was developed using conserved sequences from diverse African isolates and validated with a simplified alkaline extraction protocol that eliminates conventional nucleic acid purification. The assay achieved 100% specificity and concordant detection with polymerase chain reaction (PCR) and real‐time PCR, while reducing total diagnostic time from 4–6 h to 60 min. In‐house production of the recombinant protein Geobacillus stearothermophilus deoxyribonucleic acid polymerase, large fragment demonstrated comparable enzymatic performance to commercial alternatives, with projected per‐reaction cost reductions of 70%–80%. Concurrently, a Single Shot MultiBox Detector Lite MobileNetV2 object detection model was developed through 17 iterative training cycles on 17,703 field‐collected images spanning 22 disease and physiological stress classes. The final model achieved per class accuracies of 92.5% for BBTV, 91.0% for banana xanthomonas wilt (BXW), and 98.1% for healthy leaf classification, with deployment via the PlantVillage mobile application enabling real‐time offline diagnostics. A Quick Response (QR) code‐based metadata system links each artificial intelligence (AI) phenotypic assessment to its corresponding molecular confirmation result, enabling georeferenced surveillance that tracks both symptomatic and asymptomatic infections. Together, these complementary tools broad‐scale AI screening for rapid field survey and LAMP molecular confirmation for pre‐symptomatic detection providing an accessible, cost‐effective diagnostic framework for safeguarding banana production across sub‐Saharan Africa.
Ouedraogo et al. (Fri,) studied this question.