# Thermal variation associated stress response regulates the growth and reproductive potential of soybean looper

## TL;DR

Extreme temperatures negatively affect the growth and reproduction of soybean loopers, reducing their population and potential crop damage.

## Contribution

This study reveals how thermal stress impacts soybean looper life cycle and population dynamics through life table and enzyme analysis.

## Key findings

- Extreme temperatures extended developmental periods and reduced oviposition in soybean loopers.
- Thermal stress increased antioxidant levels, which hindered growth and reduced plant damage.
- Population simulations showed fewer soybean loopers during extreme temperature events.

## Abstract

The soybean looper (SBL) is one of the most damaging insect pests of soybean and other economically important crops worldwide. Although temperature has been reported to be a critical predictor of pest growth and development, very little is known about how temperature variations influence SBL population dynamics, which may aid in predicting SBL population outbreaks and dispersal. To examine this, we analysed the life table parameters of SBL by the age-stage, two-sex method under different temperature conditions. We also performed comparative analysis of antioxidant enzymes and total protein concentration from SBL larvae to unfold the enzymatic stress levels. Life table analysis revealed a significant extension in the developmental periods, and oviposition performance was adversely affected under extreme (extended) temperature conditions. Additionally, temperature stress elevated the antioxidant level, which negatively affected the growth and development of SBL, resulting in reduced plant damage. Population projections over an 80-day timescale simulation indicated that total SBL numbers would be significantly reduced during extreme temperature events compared to optimal temperatures. Overall, our findings suggest that extreme thermal stress had a negative effect on SBL growth and population progression, which could be used to meticulously predict SBL outbreaks and facilitate the development of a more efficient and sustainable management strategy.

The online version contains supplementary material available at 10.1038/s41598-026-36978-1.