A systems approach to apple black spot management in Canterbury
Abstract
Export apple production currently requires large inputs of pesticide which are dominated by the use of black spot fungicides. On average, NZ apple growers were found to make 16 pesticide spray applications per season, of which 85% contained black spot fungicides. A number of problems associated with high levels of black spot fungicides were identified that could be reduced by strategic reductions in the numbers, and types, of fungicides applied. These problems included, consumer and market resistance to pesticide residues on fruit, the threat of control failure in the advent of disease resistance, the risks of inducing fruit russet, disruption to integrated mite control by some fungicides and high costs of disease control.
Observations of the life cycle of the black spot pathogen (Venturia inaequalis (Cke.) Winter) in Canterbury indicated that ascospores arising from the leaf litter were likely to be the only source of primary spring inoculum, and that the maturation and discharge patterns of ascospores were similar to these observed in other parts of New Zealand.
Research was undertaken to assess the potential to integrate a range of black spot management methods to develop a cost effective, low risk, improved disease management system. A literature review and applied research indicated that there was potential in Canterbury to: 1) reduce primary ascospore inoculum in spring using nitrogen applications at leaf fall; 2) monitor ascospore numbers and ascospore maturation stages to permit fungicide use to be tailored to the presence and quantity of ascospore inoculum; and 3) monitor weather conditions to determine when infection could have occurred and schedule eradicant fungicide applications accordingly.
A computer based expert decision support system was proposed as a potential mechanism for the extension and implementation of the black spot management system. Such a system would use personal computers accessed directly by growers, would incorporate automatic weather monitoring facilities and use expert system programmes to deliver decision support information.
Requirements for further research identified included: 1) improving methods for prediction of disease risks based on amounts of ascospore inoculum; 2) improving methods for interpretation of criteria used to define infection periods by ascospores and conidia; 3) quantifying the black spot susceptibilities of different cultivars and apple tissue types and; 4) developing systems to interpret disease risks and provide management decision support to growers.... [Show full abstract]