A new approach to modelling the dynamics of oospore germination in Plasmopara viticola

Abstract

Oospores, the only overwintering structures of Plasmopara viticola, the causal agent of grapevine downy mildew, are the unique source of inoculum for primary infections in vineyards. We show that their germination dynamics depend on both climatic and endogenous factors. In particular, overwintering in controlled conditions suggests that low temperatures prolong the oospore germinability, while constant or gradually alternating water availability increases germination rates. However, wide fluctuations in germination percentage, observed both in naturally overwintered oospores, and under controlled conditions, indicate an important role for endogenous factors in the germination frequency. Ad hoc experimental assays and microscopic observations highlight an important role for calcium in the germination process. However, for a profound understanding of the biological mechanisms underlying oospore germination, mathematical models of the germination dynamics are needed. But, classical differential models of germination dynamics are, with current knowledge, prohibitive due both to the complexity of the underlying processes and knowledge incompleteness. Then, we propose a hybrid method derived from the integration of qualitative differential models and fuzzy systems.

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Acknowledgements

The Authors would like to thank dr. Simona Rodighiero, CIMAINA—Università degli Studi di Milano for her technical assistance during confocal observations.

Research funded by ARPAV, Project “Biologia e epidemiologia di Plasmopara viticola”, and Regione Lombardia Project n. 1042, “Monitoraggio e simulazione delle epidemie di Plasmopara viticola nei vigneti lombardi”, Piano per la ricerca e lo sviluppo 2007.

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Correspondence to Annamaria Vercesi.

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Vercesi, A., Toffolatti, S.L., Zocchi, G. et al. A new approach to modelling the dynamics of oospore germination in Plasmopara viticola . Eur J Plant Pathol 128, 113–126 (2010). https://doi.org/10.1007/s10658-010-9635-8

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Keywords

  • Downy mildew
  • Calcium signalling
  • Grapevine
  • Mathematical modelling
  • System identification