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Parametric interpretability of growth kinetics equations in a process model for the life cycle of Lobesia botrana

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  • Aguirre-Zapata, Estefania
  • Alvarez, Hernan
  • Dagatti, Carla Vanina
  • di Sciascio, Fernando
  • Amicarelli, Adriana N.

Abstract

Modeling processes span multiple disciplines and aim to generate new knowledge about a given process or system for subsequent analysis or control. Mathematical models are representations of these systems using mathematical equations and parameters, which may or may not be interpretable depending on their application or use. In the specific case of the life cycle of L. botrana, the goal of the mathematical model is to develop a model-based decision support system (MB-DSS) that enables experts to monitor the evolution of the pest using predictive models. Based on these predictions, timely decisions can be made to control and eradicate the pest. The interpretability of model parameters is critical to the design of MB-DSS systems. This paper analyzes the response of the growth model of L. botrana under laboratory conditions and proposes a new structure that considers two limiting factors of growth: temperature and relative humidity. The proposed analysis seeks to determine the best growth kinetics while preserving the compromise between the model’s fit to experimental data, interpretability, identifiability, and sensitivity of the model parameters. The results show an improvement in the fit, descriptive capacity, and number of inputs considered by the model.

Suggested Citation

  • Aguirre-Zapata, Estefania & Alvarez, Hernan & Dagatti, Carla Vanina & di Sciascio, Fernando & Amicarelli, Adriana N., 2023. "Parametric interpretability of growth kinetics equations in a process model for the life cycle of Lobesia botrana," Ecological Modelling, Elsevier, vol. 482(C).
    • Handle: RePEc:eee:ecomod:v:482:y:2023:i:c:s0304380023001382
    DOI: 10.1016/j.ecolmodel.2023.110407
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    References listed on IDEAS

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    1. Castex, V. & García de Cortázar-Atauri, I. & Calanca, P. & Beniston, M. & Moreau, J., 2020. "Assembling and testing a generic phenological model to predict Lobesia botrana voltinism for impact studies," Ecological Modelling, Elsevier, vol. 420(C).
    2. Aguirre-Zapata, Estefania & Morales, Humberto & Dagatti, Carla V. & di Sciascio, Fernando & Amicarelli, Adriana N., 2022. "Semi physical growth model of Lobesia botrana under laboratory conditions for Argentina’s Cuyo region," Ecological Modelling, Elsevier, vol. 464(C).
    3. Gilioli, Gianni & Pasquali, Sara & Marchesini, Enrico, 2016. "A modelling framework for pest population dynamics and management: An application to the grape berry moth," Ecological Modelling, Elsevier, vol. 320(C), pages 348-357.
    4. Pasquali, S. & Soresina, C. & Marchesini, E., 2022. "Mortality estimate driven by population abundance field data in a stage-structured demographic model. The case of Lobesia botrana," Ecological Modelling, Elsevier, vol. 464(C).
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