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Comptes Rendus Biologies|September 15, 2009
[Esca and Black Dead Arm: two major actors of grapevine trunk diseases]Philippe Larignon, Florence Fontaine, Sibylle Farine, et al.
International Journal of Molecular Sciences|February 18, 2017
Defense Responses in Grapevine (cv. Mourvèdre) after Inoculation with the Botryosphaeria Dieback Pathogens Neofusicoccum parvum and Diplodia seriata and Their Relationship with FloweringAlessandro Spagnolo, Vincenzo Mondello, Philippe Larignon, et al.
Journal of Fungi (Basel, Switzerland)|July 2, 2021
Impacts of Sodium Arsenite on Wood Microbiota of Esca-Diseased GrapevinesEmilie Bruez, Philippe Larignon, Christophe Bertsch, et al.
International Journal of Molecular Sciences|June 3, 2014
Flowering as the most highly sensitive period of grapevine (Vitis vinifera L. cv Mourvèdre) to the Botryosphaeria dieback agents Neofusicoccum parvum and Diplodia seriata infectionAlessandro Spagnolo, Philippe Larignon, Maryline Magnin-Robert, et al.
Journal of Plant Physiology|May 31, 2019
Sodium arsenite effect on Vitis vinifera L. PhysiologyAurélie Songy, Julie Vallet, Marie Gantet, et al.
Frontiers in Plant Science|May 8, 2024
Physiological and developmental disturbances caused by Botryosphaeria dieback in the annual stems of grapevineFlorian Moret, Lucile Jacquens, Philippe Larignon, et al.
Plants (Basel, Switzerland)|February 25, 2023
The Combination of Both Heat and Water Stresses May Worsen Botryosphaeria Dieback Symptoms in GrapevineOlivier Fernandez, Christelle Lemaître-Guillier, Aurélie Songy, et al.
Genome Announcements|April 8, 2017
Draft Genome Sequence of Diplodia seriata F98.1, a Fungal Species Involved in Grapevine Trunk DiseasesGuillaume Robert-Siegwald, Julie Vallet, Eliane Abou-Mansour, et al.
Frontiers in Plant Science|May 14, 2023
Sodium arsenite-induced changes in the wood of esca-diseased grapevine at cytological and metabolomic levelsSophie Trouvelot, Christelle Lemaitre-Guillier, Julie Vallet, et al.
Scientific Reports|February 29, 2024
End-to-end multimodal 3D imaging and machine learning workflow for non-destructive phenotyping of grapevine trunk internal structureRomain Fernandez, Loïc Le Cunff, Samuel Mérigeaud, et al.
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