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Forecasting model of Grapholita molesta (Lepidoptera: Tortricidae) in apple orchards

Author

Listed:
  • Hyunjung Kim
  • Seonwoong Nah
  • Hyeon-Ji Yang
  • DongGeun Choi
  • Sunghoon Baek

Abstract

One of the most notorious pests, Grapholita molesta, has caused serious economic damage in apples. However, its phenology model with a defined equation during whole apple crop season has not been developed yet. Therefore, this study was conducted to develop a phenology model of G. molesta adult to predict its current and future occurrence patterns. The 1,087 occurrence data sets of G. molesta adults from 2013 to 2023 were collected from the Rural Development Administration in Korea. Temperature data of each occurrence data set of G. molesta were collected from the Korea Meteorological Administration. The phenology model of G. molesta adults were developed with the data sets from 2013 to 2023 with four-peaked Weibull functions. When validated with independent 2024 data, the model developed in this study accurately predicted adult occurrence and reduced prediction errors (in days) for G. molesta in Korean commercial apple orchards compared to previous studies. The model predicts that G. molesta adults will emerge earlier under climate change scenarios compared to current conditions. In conclusion, this study provides valuable information for controlling G. molesta populations in apple orchards.

Suggested Citation

  • Hyunjung Kim & Seonwoong Nah & Hyeon-Ji Yang & DongGeun Choi & Sunghoon Baek, 2026. "Forecasting model of Grapholita molesta (Lepidoptera: Tortricidae) in apple orchards," PLOS ONE, Public Library of Science, vol. 21(4), pages 1-11, April.
    • Handle: RePEc:plo:pone00:0347667
    DOI: 10.1371/journal.pone.0347667
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