Artificially induced and precise small-scaled infection with Plasmopara viticola on living vines

Grapevine downy mildew, caused by the oomycete Plasmopara viticola, affects most of the world’s finest and widely planted grapevine (Vitis vinifera L.) cultivars and is typically controlled by fungicides, which are often applied in excess. Reducing fungicide use through early pathogen detection is therefore a major goal, which could be supported by emerging optical remote sensing techniques that detect subtle changes in leaf phenotype associated with disease. However, considerable variability in grapevine leaf structures, both within and across varieties, poses a major challenge in the application of optical remote sensing techniques for early downy mildew detection. To address this problem, we present a simple and effective method for the artificial and precise infection of P. viticola on living grapevines, enabling scheduled infections with an average incubation period of five days. This method is non-destructive, highly targeted, and differs from existing techniques by avoiding leaf removal and diffuse infection patterns, while being fast and easy to perform. Restricting infection to small, defined areas on individual leaves enables direct comparisons between healthy and infected tissue within the same leaf, minimising variability effects. This precise infection protocol offers significant advantages for training remote sensing applications, developing pathogen detection models, and supporting detailed analyses of P. viticola development, contributing to improved early detection through normal visualisation methods and emerging optical remote sensing techniques and a potential reduction in fungicide use.