Atlas-Based Spatio-temporal MRI Phenotyping of 3D Fungal Spread in Grapevine Wood

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Authors: Gargee Phukon, Maida Cardoso, Christophe Goze‐Bac, Loïc Le Cunff, Jean‐Luc Verdeil, Cédric Moisy, Romain Fernandez
Cited by: 0
References: 28

Abstract

Abstract In perennial crops, inner wood degradation by pathogens often escapes detection until irreversible damage has occurred. Grapevine trunk disease (GTD) is a well-known example in viticulture that alters plants from within, years before foliar symptoms arise, making early assessment difficult. To overcome this limitation, we present a novel non-destructive 3D + t pipeline for Magnetic Resonance Imaging (MRI) spatial quantification and monitoring of early internal tissue degradation resulting from fungal colonization. This pipeline integrates (i) anatomical alignment and rigid time-series registration of volumetric MRI scans, (ii) a generalized cylindrical coordinate transformation for cross-sectional trunk anatomy normalization, (iii) supervised classification to segment water-depleted (diseased/non-functional) regions, and (iv) population-level statistical analyses including construction of population mean images, probabilistic atlases of lesions, and 3D lesion descriptors. Applied to multiple Vitis vinifera cultivars inoculated with a fungal trunk pathogen, our approach enables time-lapse comparisons between cultivar and treatment in vivo. The results reveal consistent early degradation signals across individuals and cultivar-dependent lesion differences. By combining high-resolution MRI with advanced image processing and statistical atlas tools, this method provides a new paradigm for 3D plant phenotyping of internal disease progression. This methodological innovation allows non-invasive quantification of disease development and comparative assessment of host responses in woody plants, demonstrating its potential to advance understanding and management of GTDs.

Fields of Study & Subjects

Horticultural and Viticultural Research Plant Pathogens and Fungal Diseases Spectroscopy and Chemometric Analyses

Publication details

Journal / source
bioRxiv (Cold Spring Harbor Laboratory)
Publication date
5 January 2026
Document type
Preprint