昆虫学报 ›› 2025, Vol. 68 ›› Issue (9): 1282-1292.doi: 10.16380/j.kcxb.2025.09.012

• 研究论文 • 上一篇    下一篇

二化螟越冬代成虫羽化动态预测

戴长庚1,2, 钟玉琪1, 程益宇1, 赵兰1, 龚佑辉1,*, 侯茂林1,*   

  1. (1. 中国农业科学院植物保护研究所, 植物病虫害综合治理全国重点实验室, 北京 100193; 2. 贵州省农业科学院植物保护研究所, 贵阳 550006)
  • 出版日期:2024-09-20 发布日期:2025-10-28

Prediction of adult emergence dynamics of the overwintering generation of Chilo suppressalis (Lepidoptera: Crambidae)

DAI Chang-Geng1,2, ZHONG Yu-Qi1, CHENG Yi-Yu1, ZHAO Lan1, GONG You-Hui1,*, HOU Mao-Lin1,*   

  1.  (1. State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China; 2. Institute of Plant Protection, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China)
  • Online:2024-09-20 Published:2025-10-28

摘要: 【目的】二化螟Chilo suppressalis越冬代成虫羽化动态预测对其后代的精准预测和防控至关重要。本研究旨在开展二化螟越冬代成虫羽化动态的模型模拟预测。【方法】为获取模型参数,于2021年2, 3和4月在广西兴安稻田分别采集田间二化螟越冬幼虫种群,在14, 18, 22和26 ℃温度下测定幼期发育历期和成虫羽化率。幼期发育速率(发育历期的倒数)用线性模型和非线性模型拟合,成虫羽化用三参数Weibull方程进行拟合, 用Origin 2022对模型参数进行计算。【结果】从模型拟合度来看,基于3月采集的二化螟越冬幼虫种群的幼期发育历期和成虫羽化率数据所建立的羽化动态的预测更优(Radj2 3月=0.9445, Radj2 2月=0.9083, Radj2 4月=0.8380);但田间观测值表明,基于2月采集的二化螟越冬幼虫种群的非线性幼虫发育Schoolfield模型{V(T)=0.64×T/298.15×exp[47.11/1.99×(1/298.15-1/T)]}和成虫羽化Weibull方程{F∑(V(T))=1-exp[-(∑V(T)+0.04)/1.05)×5.95]}是预测二化螟越冬代成虫羽化动态的最佳模型,预测数据与田间观测值之间偏差1.0~5.3 d。【结论】实际应用时对上述模型输入当地的气温数据获得二化螟越冬代成虫羽化动态预测值,用本研究获得的偏差值进行矫正,从而获得准确的二化螟羽化动态预测数据,为二化螟的精准防控提供决策支撑。

关键词: 二化螟, 越冬代, 发育速率, 羽化动态, 预测模型

Abstract: 【Aim】Prediction of the adult emergence dynamics of the overwintering generation of Chilo suppressalis is crucial for the accurate prediction and control of its offspring generations. This study aims to develop a model simulation for predicting the adult emergence dynamics of the overwintering generation of C. suppressalis.【Methods】To obtain model parameters, the overwintering larval populations of C. suppressalis were collected from the paddy fields in Xing′an, Guangxi, South China in February, March and April 2021 and the developmental duration of immature stages and adult emergence rate were determined at four temperatures (14, 18, 22 and 26 ℃). The developmental rates of immature stages (the reciprocal of developmental duration) were fitted with linear and nonlinear models, and the adult emergence rate was fitted using a three-parameter Weibull equation. Model parameters were calculated using Origin 2022.【Results】From the perspective of model fitting, the model established based on the developmental duration of immature stages and adult emergence rate data of the overwintering larval population of C. suppressalis collected in March performed better (Radj2March=0.9445, Radj2February=0.9083, Radj2April=0.8380). However, the field observation data showed that the nonlinear larval development Schoolfield model {V(T)=0.64×T/298.15×exp[47.11/1.99×(1/298.15-1/T)]} and the adult emergence Weibull equation {F∑(V(T))=1-exp[-(∑V(T)+0.04)/1.05)×5.95]} based on the overwintering larval population collected in February gave the least deviation of adult emergence dynamics between the predicted value and the field-observed value, which was 1.0-5.3 d. 【Conclusion】In practical application, local air temperature data are input into the above models to obtain the predicted adult emergence dynamic values of the overwintering generation of C. suppressalis, which, when corrected by the deviation values obtained in this study, will provide accurate prediction of adult emergence dynamics and aid in the decision-making for the accurate control of C. suppressalis.

Key words:  Chilo suppressalis, overwintering generation, developmental rate, emergence dynamics, prediction model