S U M M A R YBacterial blight of kiwifruit (Actinidia deliciosa) is caused by Pseudomonas viridifava. Symptoms are rot of floral buds and flowers, and spots on leaves. Buds and flowers nearest the ground are most likely to be affected. Isolations made from healthy buds, flowers and leaves suggest that the pathogen is an epiphyte on vines throughout the year. Disease incidence fluctuates between seasons, and varies between orchards. A relationship between disease incidence and rainfall in spring is indicated.

A weather-based disease prediction model for bacterial canker of kiwifruit (known worldwide as Psa; Pseudomonas syringae pv. actinidiae biovar 3) was developed using a new mechanistic scheme for bacterial disease forecasters, the multiplication and dispersal concept. Bacterial multiplication is estimated from a temperature function, the M index, accumulated from hourly air temperature over 3 days for hours when the leaf canopy is wet. Rainfall provides free water to move inoculum to infection sites, and the daily risk indicator, the R index, is the 3-day accumulation of the M index output on days with total rainfall >1 mm; otherwise, R is zero. The model was field-tested using potted kiwifruit trap plants exposed for discrete periods in infected kiwifruit orchards to identify when leaf infection occurred. In a 9-week study during spring, the R index predicted leaf-spot intensity with high accuracy (R = 93%) and, in an 82-week seasonal accuracy study, prediction of infection incidence was most accurate from spring to late summer and lower during other times. To implement the risk model for the New Zealand kiwifruit industry, a modified risk index, R', used relative humidity (RH) >81% instead of wetness, so that 2- and 6-day weather forecasts of RH could be used. Risk index values were affected by the shape of the temperature function and an alternative 'low temperature' function for the M index was identified that could be used in climates in which high temperatures are known to limit Psa development during some parts of the year. This study has shown how infection risk for bacterial diseases can be conceptualized as separate processes for temperature-dependent bacterial multiplication and rain-dependent dispersal and infection. This concept has potentially wide application for bacterial disease prediction in the same way that the infection monocycle concept has had for fungal disease prediction.

A study of the ecology and epidemiology of kiwifruit blossom blight, believed to be caused by the bacterium Pseudomonas viridiflava. was made at the Horticulture and Food Research Institute's Kumeu Research Orchard during spring 1991. Populations of Pseudomonas species, progression of disease symptoms, and micrometeorological conditions were monitored during fiowering. No correlations were found between disease progress and the climate variables measured. The rate of increase in disease incidence changed with the transition of buds to flowers. Changes in the rate of increase, logit transformed, were compared with climate variables using cross-correlation. Populations of P. viridiflava were related to the number of diseased blossoms remaining on the vine. The population of a saprophytic bacterium, P. fluorescens, increased as flowering progressed and as dead flower parts became available for colonization. Other Pseudomonas species were only present in low numbers. The population of P. viridiflava and the rate of disease progress decreased at fruit set. A comparison of simulated disease progress curves (calculated using disease model formulae) with disease progress curves from real data suggested that the epidemic was polycyclic, and observations suggested that disease was spreading to unopened buds. pathogens. Zentralbtatt fur Bakteriotogie Parasitenkunde Infektionskrankheiten und Hygiene 2 Abt 100, 177-93. Henshall WR, Snelgar WP, 1989. A small unaspirated screen for air temperature measurement. New Zeatand Journal of Crop and Horticultural Science 17, 103-7. King EO, Ward MK, Raney DE, 1954. Two simple media for the demonstration of pyocyanin and fluorescin. Journal of Laboratory and Clinical Medicine U,30\-l. Ulliott RA, BilUng E, Hayward AC, 1966. A determinative scheme for the fluorescent plant pathogenic pseudomonads. Journat of Apptied Bacteriotogy 29, 470-89. Neher DA, Campbell CL, 1992. Underestimation of disease progress rates with the logistic, monomolecular, and Gompertz models when maximum disease intensity is less than 100 percent. Phytopathotogy %l,i\\-^. Pennycook SR, Triggs CM, 1991. Bacterial blossom blight of kiwifruit-a 5-year survey. Acta Horticulturae 297, 559-65.

The time required for potato late blight lesions, caused by Phytophthora infestans (Mont.) de Bary, to produce sporangia during periods of continuous leaf wetness, and for inoculations to produce lesions bearing sporangia, was determined over a temperature range of 5-24°C. Equations were derived relating time to sporulate with temperature. A 2-h break in leaf wetness, initiated at any time within the first 3 h of incubation after inoculation, markedly reduced lesion numbers. When the break was initiated later it had less effect, except at the lowest temperature tested (9°C).

To improve the implementation of weatherbased disease risk models a spatial interpolation method was investigated to provide weather estimates for specific sites Two sites in the HortResearch horticultural weather station network one in Marlborough and one in Hawkes Bay were selected as validation sites Interpolated weather data were estimated for these sites from November to March in 200304 and 200405 using actual weather data from nearby stations that were selected as natural neighbours using the geometrical technique Voronoi tessellation Wetness duration was also estimated using interpolated weather data as inputs to an empirical wetness model Air temperature estimates were comparable to actual measurements but wetness duration was overestimated When interpolated and actual data were used as inputs to the grape botrytis model Bacchus predicted risks were comparable to each other for short periods rather than the whole growing season This suggests that risk of botrytis bunch rot could be predicted reliably at a specific site using the spatial interpolation method