Evidence map›Paper›PMID 42018582›Full record

ArticlePloS one2026

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

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

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Hyunjung KimHorticulture Division, Jeonbuk State Agricultural Research & Extension Services, Iksan-Si, Jeonbuk, Republic of Korea.
Seonwoong NahAgro-environment Research Institute, Epinet Co., Ltd., Anyang-Si, Gyeonggi, Republic of Korea.
Hyeon-Ji YangAgro-environment Research Institute, Epinet Co., Ltd., Anyang-Si, Gyeonggi, Republic of Korea.
DongGeun ChoiDepartment of Horticulture, Jeonbuk National University, Jeonju-Si, Jeonbuk, Republic of Korea.
Sunghoon BaekAgro-environment Research Institute, Epinet Co., Ltd., Anyang-Si, Gyeonggi, Republic of Korea.ORCID https://orcid.org/0000-0002-0455-3345

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

LepidopteraMalusMothsAnimalsClimate ChangeForecastingRepublic of KoreaSeasonsTemperature

Identifiers

PMID42018582
PMCPMC13102221

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.