Unverified paper record
Characterising Multi-Pathogen Grapevine Dieback in Subtropical Australia: Field Symptomatology and Fungal Morphology Reveal Dominance of Botryosphaeriaceae and Phomopsis Species
Applied and Computational Engineering · 20 Jan 2026 · 10.54254/2755-2721/2026.31380
Abstract
Grapevine trunk diseases in subtropical climates show complex patterns of multi-pathogen co-infection and spatial clustering, while current diagnosis still relies mainly on expert judgement with limited quantification and functional testing. This study investigated an 18-acre vineyard in south-eastern Queensland and used 7,440 vine records from 744 plots to build quantitative indices for symptoms and cross-section necrosis, followed by comprehensive characterisation of 46 fungal isolates through isolation, microscopy, physiological assays and greenhouse pathogenicity tests. Analyses identified three spatial disease regions, with wedge- and semi-ring-shaped necrosis strongly enriched in high-disease plots, and showed that Botryosphaeriaceae and Phomopsis groups dominated the pathogen community and had much higher composite pathogenicity indices than other fungi. Even without molecular data, the integrated pipeline of disease quantification, microscopic and physiological traits, pathogenicity testing and computational analysis allowed robust identification of dominant pathogen combinations in a subtropical vineyard and provided a methodological basis for regional risk assessment and targeted management.
Plant phenotyping relevance
ブドウ樹の症状と壊死を定量化する指標および統合解析パイプラインが研究の中心で、植物の病害状態を直接測定・評価しているため。
abstractused 7,440 vine records from 744 plots to build quantitative indices for symptoms and cross-section necrosis
abstractthe integrated pipeline of disease quantification, microscopic and physiological traits, pathogenicity testing and computational analysis allowed robust identification
Code and data availability
The article describes field disease indices, isolate trait matrices, ImageJ cross-section analysis, and R/Python PCA and k-means workflows, but contains no data availability statement, repository deposit, or author URL for datasets, images, code, or models. The only URL present is the CC-BY 4.0 license notice, which is
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