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A multi-seasonal model of plant-nematode interactions and its use to identify optimal plant resistance deployment strategies

Abstract : • Root-knot nematodes (RKNs) are soil-borne polyphagous pests with major impact on crop yield worlwide. Resistant crops efficiently control avirulent RKNs, but favour the emergence of virulent forms. Virulence being associated with fitness costs, susceptible crops counter-select virulent RKNs. In this study we identify optimal rotation strategies between susceptible and resistant crops to control RKNs and maximize crop yield. • We developed an epidemiological model describing the within-season dynamics of avirulent and virulent RKNs on susceptible or resistant plant root-systems, and their between-season survival. The model was fitted to experimental data and used to predict yield-maximizing rotation strategies, with special attention to the impact of epidemic and genetic parameters. • Crop rotations were found to be efficient under realistic parameter ranges. They were characterised by low ratios of resistant plants, and were robust to parameter uncertainty. Rotations provide significant gain over resistant-only strategies, especially under intermediate fitness costs and severe epidemic contexts. • Switching from the current general deployment of resistant crops to custom rotation strategies could not only maintain or increase crop yield, but also preserve the few and valuable R-genes available to us. 1 All rights reserved. No reuse allowed without permission. (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.
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Submitted on : Wednesday, December 4, 2019 - 11:16:19 AM
Last modification on : Thursday, August 4, 2022 - 4:57:00 PM
Long-term archiving on: : Thursday, March 5, 2020 - 5:23:55 PM


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Samuel Nilusmas, Mathilde Mercat, Thomas Perrot, Caroline Djian-Caporalino, Philippe Castagnone-Sereno, et al.. A multi-seasonal model of plant-nematode interactions and its use to identify optimal plant resistance deployment strategies. 2019. ⟨hal-02393028⟩



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