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

Published online by Cambridge University Press:  19 January 2021

Natalia Riemer Open the ORCID record for Natalia Riemer [Opens in a new window] ,
Manuela Schieler ,
Paolo Racca  and
Helmut Saucke
Natalia Riemer*
Affiliation:
Universitat Kassel, Nordbahnhofstr. 1a, Witzenhausen, Hesse37213, Germany
Manuela Schieler
Affiliation:
Central Institute for Decision Support Systems in Crop Protection (ZEPP), Rüdesheimer Str. 60-68, D-55545Bad Kreuznach, Germany
Paolo Racca
Affiliation:
Central Institute for Decision Support Systems in Crop Protection (ZEPP), Rüdesheimer Str. 60-68, D-55545Bad Kreuznach, Germany
Helmut Saucke
Affiliation:
Central Institute for Decision Support Systems in Crop Protection (ZEPP), Rüdesheimer Str. 60-68, D-55545Bad Kreuznach, Germany
*
Author for correspondence: Natalia Riemer, Email: natalia.riemer@uni-kassel.de
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Abstract

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.

Keywords

Development ratenonlinear modelparameter estimationpest managementphotoperiodtemperature
Type
Research Paper
Information
Bulletin of Entomological Research , Volume 111 , Issue 4 , August 2021 , pp. 402 - 410
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

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