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Variability Among Forecast Models for the Apple Sooty Blotch/Flyspeck Disease Complex.

Daniel R Cooley1, David A Rosenberger2, Mark L Gleason3

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Disease forecast models for apple sooty blotch and flyspeck (SBFS) show significant variability in predictions due to differences in leaf wetness duration (LWD) thresholds and data acquisition methods. Improving these models requires addressing epidemiological factors and horticultural considerations for better SBFS management.

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Area of Science:

  • Plant Pathology
  • Agricultural Meteorology
  • Horticultural Science

Background:

  • Empirical disease forecast models are used for managing apple sooty blotch and flyspeck (SBFS).
  • These models typically rely on leaf wetness duration (LWD) from a biofix near petal fall to time fungicide applications.
  • Existing SBFS models exhibit considerable variation in biofix timing and LWD thresholds.

Purpose of the Study:

  • To investigate the sources of variability among different SBFS forecast models.
  • To identify factors influencing the consistency and accuracy of SBFS disease prediction.
  • To highlight areas for improvement in developing more reliable SBFS management strategies.

Main Methods:

  • Comparison of multiple SBFS forecast models using a single dataset.
  • Analysis of leaf wetness (LW) data acquisition methods (on-site vs. remote sensing).
  • Examination of horticultural and orchard site factors influencing SBFS risk.

Main Results:

  • Model recommendations for initial fungicide applications varied by up to five weeks.
  • Leaf wetness (LW) measurement methods (sensor type, placement, remote estimation) significantly impact model inputs.
  • Discrepancies exist between model thresholds and data acquisition methods, potentially leading to application failures.

Conclusions:

  • Inconsistencies in SBFS models stem from variable LWD thresholds and data collection methods.
  • Horticultural factors (tree size, canopy density, cultivar) and site factors (inculum proximity) require integration into forecast models.
  • Further research is needed on the epidemiology of diverse SBFS fungi to enhance model development and adoption.