Orchardist: David and Sue Finger

Situation:

• Codling moth and scab are under control but treatments may be impacting biocontrol agents (specialist and generalist) that would otherwise be maintaining pests below economic levels. A staff member trained in scouting is providing regular data on pest and disease incidence. RIMPRO is used for guidance on spray timing but does not account for pest pressure.

Mission:

• To capitalise on the low pest and disease population and attempt to further reduce pesticide use while maintaining effective control and confidence in the approach being taken.

Execution:

• Implement codling moth trapping grid to ground-truth RIMPRO predictions and use trap results to determine need to spray when model predicts egg hatch should be occurring.
• Convert mite monitoring results to CLIDs to gain a better understanding of the risk associated with mite infestation.
• Continue approach of using “softer” products to reduce side effects on non-target species
• Trial planting nectar sources amongst inter-row sward to enhance performance and survival of parasitoids

Administration

• David Finger to develop pre-plan for responding to issues that may develop.
• Steve Leeves to monitor pests and diseases, David Finger to monitor traps
• Ask an Expert facility in IPDM website is available additional support and expertise
• David Williams is available for technical advice

Safety

• Experiments can be stressful but no useful results will occur unless the participants maintain their nerve
• Stress can be reduced by setting realistic targets that stretch comfort zones without creating major financial risks
• Over-use of chemical applications will create residue issues, pest resistance issues, possible mite flare, and potential health issues for staff
• Stress can be reduced by taking the time to seek expert advice on the problem, either in the planning phase or before the problem gets out of control, rather than making knee-jerk decisions
• Regular assessments of pest and disease populations and damage levels will allow timely changes to approach before significant damage occurs
• Use of prediction models based on local data will provide early indications of potential danger periods