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Research Article | Open Access

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

Gargee Phukona,bMaïda CardosocChristophe Goze-BaccLoïc Le CunffdJean-Luc Verdeila,bCédric MoisydRomain Fernandeza,b( )
UMR AGAP Institut, INRAE, F-34398, Montpellier, France
CIRAD, UMR AGAP Institut, 34398, Montpellier, France
BNIF University of Montpellier, Place Eugène Bataillon, Montpellier, France
IFV, French Institute of Vine and Wine, IFV, INRAE, UMT Géno-Vigne, Institut Agro, 34398, Montpellier, France
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Abstract

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 cylindrical-coordinate 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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Plant Phenomics
Article number: 100185

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Cite this article:
Phukon G, Cardoso M, Goze-Bac C, et al. Atlas-based spatiotemporal MRI phenotyping of 3D fungal spread in grapevine wood. Plant Phenomics, 2026, 8(2): 100185. https://doi.org/10.1016/j.plaphe.2026.100185

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Received: 19 December 2025
Revised: 05 February 2026
Accepted: 18 February 2026
Published: 30 March 2026
© 2026 The Authors. Nanjing Agricultural University.

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).