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Atlas-based spatiotemporal MRI phenotyping of 3D fungal spread in grapevine wood
Article de revue scientifique   Open Access   Avec comité de lecture

Atlas-based spatiotemporal MRI phenotyping of 3D fungal spread in grapevine wood

Gargee Phukon, Maïda Cardoso, Christophe Goze-Bac, Loïc Le Cunff, Jean‐luc Verdeil, Cédric Moisy et Romain Fernandez
Plant Phenomics, Vol.8(2)
06/2026

Résumé

Magnetic resonance imaging (MRI) Time-lapse tracking Anatomical phenotyping Grapevine trunk diseases (GTDs) Probabilistic atlas cartographic atlas atlas distribution over space and time spatiotemporal distribution perennial crop viticulture quantification method surveillance system monitoring Vitis vinifera three-dimensional image analysis 3D image analysis induced innovation innovation non-invasive method early diagnosis technical management MRI magnetic resonance imaging phenotyping bioimaging biological imaging fungal contamination spatio-temporal analysis grapevine trunk wood disease grapevine trunk disease anatomical trait probabilistic model

In perennial crops, inner wood degradation by pathogens often escapes detection until irreversible damage has occurred. Grapevine trunk diseases (GTDs) are a well-known example in viticulture that alter 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 high-resolution Magnetic Resonance Imaging (MRI) spatial quantification and monitoring of early internal host tissue degradation resulting from fungal pathogen colonization. The pipeline integrates spatiotemporal anatomical alignment and rigid registration; a generalized cylindricalcoordinate transformation; supervised segmentation of water-depleted regions; and population-level statistical analyses, including population mean images, probabilistic atlases, and 3D lesion descriptors. Applied to multiple Vitis vinifera cultivars inoculated with a fungal wood pathogen, our approach enables in vivo time-lapse comparisons between cultivars and treatments. The results reveal reproducible early degradation signals across individuals and cultivar-dependent differences in lesion progression. Overall, this methodological innovation provides a new paradigm for internal plant phenotyping, enabling non-invasive quantification of disease development and comparative spatiotemporal assessment of host responses in woody plants, with strong potential to advance early diagnosis and management of GTDs and internal diseases.

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