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

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.

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Publication Details

Journal
PLoS ONE
Published
2026-04-22
DOI
https://doi.org/10.1371/journal.pone.0347667
Primary Topic
Insect Pheromone Research and Control
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Sunghoon Baek, DongGeun Choi, Seonwoong Nah, Hyeon-Ji Yang et al.
PLoS ONE
Insect Pheromone Research and Control
article

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

Sunghoon Baek, DongGeun Choi, Seonwoong Nah, Hyeon-Ji Yang, Hyunjung Kim
article en

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.

PLoS ONEVol. 21(4)
Korea Environment Institute (KR), Jeonbuk Agricultural Research & Extension Services (KR), Jeonbuk National University (KR)
Rural Development Administration
Climate action
Openalex Percentile: Top 14%
Insect Pheromone Research and Control
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Forecasting model of Grapholita molesta (Lepidoptera: Tortricidae) in apple orchards — Sunghoon Baek, DongGeun Choi, et al. · PLoS ONE (2026) | TGRS Research Map | TGRS