1. Use of Phenology Models for Insect Management in Southeastern Tree Fruits Jim Walgenbach Department of Entomology NC State University MHCREC, Mills River, NC

2. Raleigh Mills River Charlotte

3. Direct Insect Pests of Apples and Peaches in NC San Jose Scale Plum Curculio Stink Bugs Oriental Fruit Moth Tufted Apple Bud Moth Codling Moth Comstock Mealybug Apple Maggot

4. Attributes of Insect Phenology Models in Tree Fruits Temperature-driven Models predict biological events important in management –Adult emergence, egg hatch, etc. Predominately used to optimize –Insecticide use –Scouting resources

5. Factors Contributing to Use of Phenology Models by Grower Community Host range and mobility of pest Common vs. sporadic pest Consequences of over-spraying –Cost, resistance development Availability, efficiency and ease of monitoring tools Simplicity of outputs

6. Direct Insect Pests of Apples and Peaches in NC San Jose Scale Plum Curculio Stink Bugs Oriental Fruit Moth Tufted Apple Bud Moth Codling Moth Comstock Mealybug Apple Maggot

7. Tufted Apple Bud Moth (Playnota idaeusalis) APR MAY JUN JUL AUG SEP OCT 2nd Generation

8. Moths/trap% Egg hatch 0 25 50 75 100 % Cumulative egg hatch TABM Pheromone Trap Catches and % Cumulative Egg Hatch APR MAY JUNJULAUGSEPOCT 0 25 50 75 100 125 150 Moths/trap 01000 2000 3000 4000 DD Biofix

9. Codling Moth (Cydia pomonella) APR MAY JUN JUL AUG SEP

10. Codling Moth Degree-Day Model Riedl et al. 1976. Can. Entomol. Predicts percentage of adult emergence and egg hatch of first and second generations. Degree-day accumulations begin at biofix, defined as first emergence of male moth. In practice, first sustained capture of male moth in pheromone trap is biofix. Insecticide applications are recommended at initial egg hatch.

11. Codling Moth Phenology Biofix 250DD 350DD 0 10 20 30 40 Moths per trap 0 20 40 60 80 100 AdultsPredicted Egg Hatch APR MAY JUN JUL AUG SEP 1250DD 1350DD

12. Impact of Resistance Development on Phenological Models

13. Developmental Rate of Insecticide-Resistant Codling Moth Populations is Slower than Susceptible Populations E. Lue. 2005. Trade-offs between insecticide resistance and development time in codling moth. http://socrates.berkeley.edu/~es196/projects/2005final/Lue.pdf –Development from egg-adult was 10% greater for a Guthion-resistant resistant compared to a susceptible codling moth population Boivin, T., J. Chadoeuf, J.C. Bouvier, D. Beslay, and B. Saupanor. 2005. Modeling the interaction between phenology and insecticide resistance genes in the codling moth, Cydia pomonella. Pest Manag. Sci. 61: 53-67. –Pheromone trapping studies validated a model that predicted delayed emergence of insecticide resistant codling moth, and segregation of susceptible and resistant individuals increased with the frequency of resistance.

14. 2007 First Generation Trap Captures vs. Degree-Days Accumulations MHCRS Orchard H1 Orchard L1 Orchard P1 OP-Susceptible Orchards OP-Resistant Orchards

15. Predicted vs Actual Percentage Catch of 1 st Generation Codling Moth Mean deviation (d) from model Orchard L1 -10.6 (±6.3) MHCRS + 4.8 (±3.3) Mean deviation (d) from model Orchard H1 + 27.7 (±5.4) Orchard P1 + 19.2 (±1.9)

16. 0 20 40 60 80 100 02004006008001000 DD from biofix Moths per trap 2006 First Generation Codling Moth Pheromone Trap Captures – Orchard H1 May June

17. -2-1.5-0.500.51 Dose (log ppm) % Mortality (probit scale) Lab Orchard H1 5 10 20 30 40 50 60 70 80 90 95 Dose-Response of Codling Moth Populations to Azinphosmethyl May June 0.41 0.77

18. Codling Moth Phenology - 2009 Biofix 250DD 350DD 0 10 20 30 40 Moths per trap 0 20 40 60 80 100 AdultsPredicted Egg Hatch APR MAY JUN JUL AUG SEP Percentage egg hatch 1250 DD

19. Predicted vs. Actual Emergence of Codling Moth Based on DD Accumulations - 2009 0 20 40 60 80 100 % Cumulative moths PredictedActual APR MAY JUN JUL AUG SEP 410DD

20. In-Orchard Monitoring and Information Delivery