Proceedings of the 2025 2nd International Symposium on Agricultural Engineering and Biology (ISAEB 2025)

Study on Response of Meteorological Factors to Occurrence and Disappearance of Wheat Aphids in Shihezi City and its Forecasting Model

Authors
Xiaotian Wang1, 2, Yu Gao1, 2, Haoyi Xu1, 3, *
1Shihezi Meteorological Bureau, Xinjiang Uygur Autonomous Region, Shihezi, China
2Wulanwusu Ecology and Agrometeorology Observation and Research Station of Xinjian, Shihezi, China
3Meteorological Information Center of Xinjiang Uygur Autonomous Region, Urumqi, China
*Corresponding author. Email: 343292407@qq.com
Corresponding Author
Haoyi Xu
Available Online 15 December 2025.
DOI
10.2991/978-94-6463-910-0_20How to use a DOI?
Keywords
wheat aphids; meteorological factors; prediction model; correlation analysis
Abstract

To explore how meteorological conditions regulate the occurrence and disappearance of wheat aphids in Shihezi City, Xinjiang, this study analyzed aphid observation data and corresponding meteorological records spanning 30 years (1992–2021). Using correlation analysis and stepwise regression, it examined the associations between wheat aphid dynamics (occurrence, peak activity, and population decline) and meteorological factors across multiple time scales, and developed predictive models for pest activity.

Results indicated that wheat aphids in Shihezi emerge and proliferate under favorable early-season temperature and moisture conditions, with migration (dis-appearance) coinciding with wheat maturation. Key factors influencing the initial occurrence period include March average temperature, mid-to-late April average temperature, late March–early April average maximum temperature, and mid-March–early April precipitation. The peak period is significantly affected by May–early June average temperature and late April–mid May precipitation, while April average minimum temperature, early-to-mid May average temperature, and early-to-mid May precipitation strongly influence peak population density.

The regression models for initial occurrence period, peak period, and peak population density achieved forecasting accuracies of 75%–80%. Compared with existing methods such as wavelet neural networks (which require complex computational frameworks) and regional index models (with limited adaptability), these models offer greater practical value for integrated pest management due to their simplicity, cost-effectiveness, and alignment with local conditions. Acknowledging limitations, this study did not incorporate factors like natural enemies, agricultural practices, or wheat varieties, which should be addressed in future research. The findings provide critical support for local wheat pest control, disaster prevention, and the development of a meteorological index system for pest monitoring and risk assessment.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2025 2nd International Symposium on Agricultural Engineering and Biology (ISAEB 2025)
Series
Advances in Biological Sciences Research
Publication Date
15 December 2025
ISBN
978-94-6463-910-0
ISSN
2468-5747
DOI
10.2991/978-94-6463-910-0_20How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Xiaotian Wang
AU  - Yu Gao
AU  - Haoyi Xu
PY  - 2025
DA  - 2025/12/15
TI  - Study on Response of Meteorological Factors to Occurrence and Disappearance of Wheat Aphids in Shihezi City and its Forecasting Model
BT  - Proceedings of the 2025 2nd International Symposium on Agricultural Engineering and Biology (ISAEB 2025)
PB  - Atlantis Press
SP  - 183
EP  - 193
SN  - 2468-5747
UR  - https://doi.org/10.2991/978-94-6463-910-0_20
DO  - 10.2991/978-94-6463-910-0_20
ID  - Wang2025
ER  -