In viticulture, direct protection against downy and powdery mildews relies on the preventive application of fungicides, requiring growers to anticipate infection events. Decision-making is mainly supported by forecasting models driven by weather predictions. However, these decisions are inherently uncertain, as some treatments ultimately prove unnecessary, although this information only becomes available retrospectively from observed conditions. This study explores the integration of an advanced spore detection device to better target fungicide applications in vineyards, aiming to reduce the use of phytosanitary products while maintaining high grape quality. The stand-alone device uses digital holography combined with artificial intelligence (AI) for detecting and classifying airborne spores of both downy and powdery mildew. It enables the tracking of disease dynamics as well as the assessment of environmental conditions and treatment effects on spore counts. Two case studies with real-time data access in Changins, Switzerland and Château le Puy, France, are presented and revealed promising strategies for substantial reductions in fungicide use while maintaining effective disease control.