Modelling of post-diapause development and spring emergence of Cydia nigricana (Lepidoptera: Tortricidae)

The prediction of the post-diapause emergence is the first step towards a comprehensive decision support system that can contribute to a considerable reduction of pesticide use by forecasting a precise spraying date. The cumulative field emergence can be described as a function of the cumulative dev...

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Bibliographic Details
Published in:Bulletin of entomological research 2021-08, Vol.111 (4), p.402-410
Main Authors: Riemer, Natalia, Schieler, Manuela, Racca, Paolo, Saucke, Helmut
Format: Article
Language:English
Subjects:
Animal behavior
Butterflies & moths
Decision support systems
Diapause
Emergence
Experiments
Humidity
Laboratories
Mathematical models
Parameters
Peas
Pesticide use reduction
Pesticides
Pheromone traps
Pheromones
Photoperiods
Rain
Research Paper
Spraying
Temperature data
Variance analysis
Weather
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Summary:The prediction of the post-diapause emergence is the first step towards a comprehensive decision support system that can contribute to a considerable reduction of pesticide use by forecasting a precise spraying date. The cumulative field emergence can be described as a function of the cumulative development rate. We investigated the impact of seven constant temperatures and five light regimes on post-diapause development in laboratory experiments. Development rate depended significantly on temperature but not on photoperiod. We therefore fit non-linear thermal performance curves, a better and more modern approach over past linear models, to describe the development rate as a function of temperature. The four parameter Brière function was the most suitable and was subsequently applied to temperature data from 36 previous pea fields, where pea moth emergence was measured with pheromone traps in Northern Hesse (Germany). In order to describe the variation in development times between individuals, we fit five nonlinear distribution models to the cumulative development rate as a function of cumulative field emergence. The three parameter Gompertz model was selected as the best fitted model. We validated the model performance with an independent field data set. The model correctly predicted the first moth in the trap and the peak emergence in 81.82% of cases, with an average deviation of only 2.00 and 2.09 days respectively.
ISSN:0007-4853
1475-2670
DOI:10.1017/S0007485320000772