Powdery mildew on strawberry (Podosphaera aphanis) leaf and fruit is one of the most important diseases in strawberry. Mildew in strawberry depends on the number of spores in the air leading to infection, on the microclimate around the plant and on the variety. Germination of spores and mycelium growth takes place in the boundary layer close to leaf and fruit. This project looked at the influence of the microclimate in the boundary layer of leaf and fruit on mildew infection and how this may contribute to a management strategy of mildew. First, the thickness of the boundary layer was determined. Subsequently, the microclimate in this boundary layer was measured and climate data were compared with the greenhouse. With these data, a model of the microclimate was drawn up based on measured climate values in the surrounding greenhouse air, leading to a good predictability (R2=0.98). This makes it possible to calculate the microclimate in the boundary layer of leaves and fruits based on measured climate values in the surrounding greenhouse air without the need for specific microclimate sensors. Data from mildew incidence were collected and linked to the microclimate in the boundary layer. Microclimate settings that appeared to inhibit or promote mildew development were then tested in climate chamber experiments measuring mildew germination and mycelium development. It appeared that germination of mildew spores on young leaves is higher than on old leaves, that germination increases with an increase in relative humidity and that temperatures above 30oC inhibit germination. Mycelium development immediately after inoculation was not linked to the microclimate, while outwardly visible mycelium increased two weeks after inoculation at higher relative humidity. This shows that for mildew development, relative humidity appears to be a more important factor for the microclimate than temperature. Based on these data, a first model for the prediction of mildew germination depending on the microclimate was set up leading to a reasonable predictability (R2=0.79).
|Name||Rapport / Stichting Wageningen Research, Wageningen Plant Research, Business unit Open teelten|