2.5.27
ESTIMATING THE SPATIAL VARIATION IN LEAF WETNESS DURATION WITHIN BRUSSELS SPROUTS CANOPY AND ITS EFFECT ON DARK LEAF SPOT INFECTION MODELLING

KJ HARPER and R KENNEDY

Horticulture Research International, Wellesbourne, Warwickshire CV35 9EF, UK

Background and objectives
Dark leaf spot, caused by Alternaria brassicae is an important fungal disease of vegetable brassicas especially Brussels sprouts (Brassica oleracea). The typical symptom is a black lesion the appearance of which reduces the marketability of Brussels sprout buttons. An infection model for A. ;brassicae has been developed at HRI Wellesbourne, which uses leaf wetness duration and temperature to predict infection on Brussels sprouts. A critical period of leaf wetness is required for A. ;brassicae infection of leaves and buttons. Wetness duration is determined by a number of factors, including those involved in the wetting and drying of the canopy [1]. The position of leaves within the canopy may alter the conditions of wetting and drying to which leaves are subjected. Currently, a flat wetness sensor (Skye SKLW900) positioned at approximately 40 ;cm from the ground is used to assess leaf wetness. A threshold output of 200 ;mV is currently used to differentiate between wet and dry leaves. Thus, the objective of this work was to assess whether significant differences in leaf wetness duration occur within the Brussels sprout canopy. An additional objective was to determine the accuracy of flat and cylindrical wetness probes (developed at HRI) in estimating leaf wetness duration of the Brussels sprout canopy.

Materials and methods
Visual observations of leaf wetness have been made on 50 leaves at two levels of a fully expanded Brussels sprout canopy (upper and lower) at regular intervals in an experimental plot during October and November 1997. Cylindrical and flat wetness probes were set at four heights: above (outside the canopy), at the top, middle and lower level of the canopy. Wetness assessments taken visually and compared with wetness sensor output for different wetness events.

Results and conclusions
The leaf wetness of the upper and lower canopy differed depending on the type of wetness event. Dew caused the upper canopy to have longer wetness durations than the lower positions. Rainfall gave more uniform wetness durations. Wind speed affected the wetness duration of the canopy. This occasionally led to large differences between the wetness of the upper and lower canopy. Leaf position within the canopy does therefore have a significant effect on leaf wetness duration. One wetness probe at one height cannot accurately predict the wetness duration of the entire canopy. However, different canopy structures may modify the vertical distribution of wetness duration. Visual observations showed that the wetness duration of the canopy was underestimated by the Skye wetness sensors. This may have been due to differences in evaporation speed owing to different water droplet sizes which formed on the sensors compared with leaves as a result of different surface properties. Results demonstrated that the output wetness threshold of the sensors used to predict leaf wetness should be modified with the type of wetness event. Wetness probes at four heights of the canopy produced different leaf wetness duration estimates owing to vertical variation in the conditions of wetting, drying and water redistribution within the canopy. Use of the A. ;brassicae infection model indicated that this is significant in terms of vertical variation in dark infection in the canopy. Flat and cylindrical wetness probes estimated leaf wetness to be different, for example the onset of wetness was estimated much more slowly by the cylindrical wetness probes than the flat wetness probes. The difference is most likely due to the surface area and angle of the surface available to intercept and retain water. Accurate wetness measurements of Brussels sprout buttons may make it possible to precisely forecast when infection will occur.

References
1. Huber L,Gillespie TJ, 1992. Annual Review Phytopathology 30, 553-77.