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Review

Integrated Management of Rose Downy Mildew (Peronospora sparsa): Linking Epidemiology to Disease Control.

Jul 2026 · Plant Disease · 0 citations
Medicine

TL;DR

This review synthesizes recent advances in rose downy mildew research with emphasis on linking infection dynamics to actionable control strategies and proposes an integrated disease management framework that combines environmental monitoring, infection risk assessment, and optimized fungicide use to improve control efficacy in both field and protected systems.

Abstract

Downy mildew, caused by the oomycete Peronospora sparsa, is a major constraint in rose (Rosa spp.) production, particularly under conditions of prolonged leaf wetness and high humidity. Although substantial progress has been made in understanding pathogen biology, fungicide performance, and detection methods, the translation of epidemiological knowledge into practical disease management remains poorly developed. This review synthesizes recent advances (2020-2025) in rose downy mildew research, with emphasis on linking infection dynamics to actionable control strategies. Cultural practices that regulate canopy microclimate such as ventilation, irrigation timing, and plant spacing together with targeted fungicide applications, remain the most reliable control measures. In contrast, biological control agents and host resistance strategies show promise but lack consistent validation under commercial production conditions. Recent molecular studies have improved understanding of host pathogen interactions, although their direct application in management remains limited. Based on current evidence, we propose an integrated disease management framework that combines environmental monitoring, infection risk assessment, and optimized fungicide use to improve control efficacy in both field and protected systems. Key research priorities include the development of predictive models and validation of integrated strategies under diverse production conditions. In particular, integrating epidemiological thresholds such as leaf wetness duration and humidity into decision-based management frameworks is essential for improving the timing and effectiveness of disease control interventions.

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