INVESTIGATING SPATIAL HETEROGENEITY IN POWDERY MILDEW PRESSURE AT THE PLOT SCALE: A PRECISION VITICULTURE APPROACH INVESTIGACIÓN DE LA HETEROGENEIDAD ESPACIAL DE LA SEVERIDAD DE OIDIO A ESCALA PARCELAR: UN ENFOQUE DE VITICULTURA DE PRECISIÓN

WEENS, Valentin1, 2; ZITO, Sébastien1; BOIS, Benjamin1; GARIN, Guillaume2; PAZOS, Valérie2; STOOP, Philippe2; CAFFARRA, Amelia2* 1 CRC, Biogéoscience, Université de Bourgogne Franche Comté, 6 Bld Gabriel, 21000 Dijon, France 2 ITK, Cap Alpha, 2 Avenue de l’Europe, 34830 Clapiers, France * Corresponding author: amelia.caffarra@itk.fr

Abstract: Powdery mildew (Erysiphe necator) (PM) is the most important and impacting fungal disease of grapevine (Vitis vinifera L). This disease remains difficult to model and forecast accurately because (i) the first signs of the disease in the vineyard are hardly noticeable in the first 30- 40 days after the onset of the epidemic (three to four pathogen generations), and (ii) its spatial distribution within or between neighboring plots is heterogeneous. This hetereogeneity is difficult to explain by environmental variables measured at low spatial resolution, such as climate variables averaged over large grid cell. The objective of the present study is to improve current knowledge of the factors and mechanisms triggering PM primary infections at the individual plot-scale in order to refine existing prediction models. In order to do this, we are conducting a detailed field survey on 10 plots in the Beaune area of Bourgogne. Here, weekly detailed observations of disease severity are combined to data on microclimate, topography, spore presence on leaves (harvesting), soil characteristics, grapevine vigor and phenological stage. These surveys will help to improve existing PM models by including new driving variables that will help improve existing precision decision support tools for winegrowers. The comparison between reference weather station data (collected several kilometers away from the monitored plots) and the weather data collected on the plots will allow to upscale models calibrated at the plot level.

Keywords: Erysiphe necator, epidemiology, disease drivers, Burgundy, decision support
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