# Long-Term and Short-Term Forecasting of Oriental Fruit Moth (Grapholita molesta) Trap Catches from Apple Orchards in South Korea Using Time Series Models

**Authors:** Steven Kim, Seong Heo

PMC · DOI: 10.3390/plants15040624 · 2026-02-16

## TL;DR

This paper uses time series models to forecast oriental fruit moth trap catches in South Korean apple orchards, comparing methods for short- and long-term predictions.

## Contribution

The study evaluates SARIMA, Prophet, and VAR models for forecasting pest occurrences and highlights the limitations of multivariate models with aggregated data.

## Key findings

- Short-term predictions of oriental fruit moth trap catches are more reliable than long-term predictions.
- SARIMA model showed as reliable or better predictive performance than Prophet with aggregated data.
- VAR model performed poorly despite better fit to bimonthly province-level data.

## Abstract

The oriental fruit moth (OFM), also known as Grapholita molesta, is a major agricultural pest causing significant economic loss of apple growers in South Korea. This study demonstrates the application of time series models for describing the national and regional patterns of OFM occurrences in the last decade and for forecasting future OFM occurrences. The seasonal autoregression integrated moving average (SARIMA), Prophet, and vector autoregressive (VAR) models are compared for both long- and short-term predictions. The analysis shows that short-term predictions are more reliable than long-term predictions for the number of OMF trap catches, and the multivariate time series model does not necessarily provide better predictive performance with province-level aggregated data. Though the Prophet and VAR model fits bimonthly province-level data better than the SARIMA model, the VAR model shows poor predictive performance, and the SARIMA model showed as or more reliable predictions than the Prophet model in this study. This study presents both the potential and challenges for establishing a Smart Integrated Pest Management (IPM) system capable of monitoring and predicting OFM occurrences and implementing regional pest control strategies. The usefulness of time series analysis can be leveraged by frequent orchard-level data reporting, pest management records, and precise local environment information.

## Linked entities

- **Species:** Grapholita molesta (taxon 192188)

## Full-text entities

- **Diseases:** fruit tree (MESH:D021184), diseases (MESH:D004194), injury to (MESH:D014947), IPM (MESH:D000081042), fruit tree pests (MESH:D029021), JB (MESH:C537495), OFM (MESH:D016773), fungal rot (MESH:D009181), insect (MESH:C000719201)
- **Chemicals:** (E)-8-dodecenyl acetate (-)
- **Species:** Cydia pomonella (codling moth, species) [taxon 82600], Malus domestica (apple, species) [taxon 3750], Prunus persica (peach, species) [taxon 3760], Adoxophyes orana (summer fruit tortrix moth, species) [taxon 480707], Pyrus communis (pear, species) [taxon 23211], Allium sativum (garlic, species) [taxon 4682], Homo sapiens (human, species) [taxon 9606], Oryza sativa (Asian cultivated rice, species) [taxon 4530], Grapholita lobarzewskii (species) [taxon 568175], Grapholita molesta (oriental fruit moth, species) [taxon 192188], Allium cepa (onion, species) [taxon 4679]

## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12943878/full.md

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Source: https://tomesphere.com/paper/PMC12943878