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

Autores
Aguirre Zapata, Estefania; Álvarez, Hernán; Dagatti, Carla Vanina; di Sciascio, Fernando; Amicarelli, Adriana N.
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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.
EEA Mendoza
Fil: Aguirre Zapata, Estefania. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). Instituto de Automática; Argentina
Fil: Aguirre Zapata, Estefania. Universidad Nacional de San Juan (UNSJ). Instituto de Automática; Argentina
Fil: Aguirre Zapata, Estefania. Universidad Nacional de Colombia. Facultad de Minas. Escuela de Procesos y Energía; Colombia
Fil: Álvarez, Hernán. Universidad Nacional de Colombia. Facultad de Minas. Escuela de Procesos y Energía; Colombia
Fil: Dagatti, Carla Vanina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Mendoza; Argentina
Fil: di Sciascio, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). Instituto de Automática; Argentina
Fil: di Sciascio, Fernando. Universidad Nacional de San Juan (UNSJ). Instituto de Automática; Argentina
Fil: Amicarelli, Adriana N. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). Instituto de Automática; Argentina
Fil: Amicarelli, Adriana N. Universidad Nacional de San Juan (UNSJ). Instituto de Automática; Argentina
Fuente
Ecological Modelling 482 : 110407. (August 2023)
Materia
Modelos Matemáticos
Análisis del Ciclo de Duración
Lobesia botrana
Crecimiento
Mathematical Models
Life Cycle Analysis
Growth
Growth Kinetics Equations
Nivel de accesibilidad
acceso restringido
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/25853
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spelling Parametric interpretability of growth kinetics equations in a process model for the life cycle of Lobesia botranaAguirre Zapata, EstefaniaÁlvarez, HernánDagatti, Carla Vaninadi Sciascio, FernandoAmicarelli, Adriana N.Modelos MatemáticosAnálisis del Ciclo de DuraciónLobesia botranaCrecimientoMathematical ModelsLife Cycle AnalysisGrowthGrowth Kinetics EquationsModeling 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.EEA MendozaFil: Aguirre Zapata, Estefania. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). Instituto de Automática; ArgentinaFil: Aguirre Zapata, Estefania. Universidad Nacional de San Juan (UNSJ). Instituto de Automática; ArgentinaFil: Aguirre Zapata, Estefania. Universidad Nacional de Colombia. Facultad de Minas. Escuela de Procesos y Energía; ColombiaFil: Álvarez, Hernán. Universidad Nacional de Colombia. Facultad de Minas. Escuela de Procesos y Energía; ColombiaFil: Dagatti, Carla Vanina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Mendoza; ArgentinaFil: di Sciascio, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). Instituto de Automática; ArgentinaFil: di Sciascio, Fernando. Universidad Nacional de San Juan (UNSJ). Instituto de Automática; ArgentinaFil: Amicarelli, Adriana N. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). Instituto de Automática; ArgentinaFil: Amicarelli, Adriana N. Universidad Nacional de San Juan (UNSJ). Instituto de Automática; ArgentinaElsevier2026-04-17T14:26:19Z2026-04-17T14:26:19Z2023-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/25853https://www.sciencedirect.com/science/article/pii/S0304380023001382?via%3Dihub0304-3800 (impresa)1872-7026 (online)https://doi.org/10.1016/j.ecolmodel.2023.110407Ecological Modelling 482 : 110407. (August 2023)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/restrictedAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2026-05-07T11:53:17Zoai:localhost:20.500.12123/25853instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2026-05-07 11:53:18.59INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Parametric interpretability of growth kinetics equations in a process model for the life cycle of Lobesia botrana
title Parametric interpretability of growth kinetics equations in a process model for the life cycle of Lobesia botrana
spellingShingle Parametric interpretability of growth kinetics equations in a process model for the life cycle of Lobesia botrana
Aguirre Zapata, Estefania
Modelos Matemáticos
Análisis del Ciclo de Duración
Lobesia botrana
Crecimiento
Mathematical Models
Life Cycle Analysis
Growth
Growth Kinetics Equations
title_short Parametric interpretability of growth kinetics equations in a process model for the life cycle of Lobesia botrana
title_full Parametric interpretability of growth kinetics equations in a process model for the life cycle of Lobesia botrana
title_fullStr Parametric interpretability of growth kinetics equations in a process model for the life cycle of Lobesia botrana
title_full_unstemmed Parametric interpretability of growth kinetics equations in a process model for the life cycle of Lobesia botrana
title_sort Parametric interpretability of growth kinetics equations in a process model for the life cycle of Lobesia botrana
dc.creator.none.fl_str_mv Aguirre Zapata, Estefania
Álvarez, Hernán
Dagatti, Carla Vanina
di Sciascio, Fernando
Amicarelli, Adriana N.
author Aguirre Zapata, Estefania
author_facet Aguirre Zapata, Estefania
Álvarez, Hernán
Dagatti, Carla Vanina
di Sciascio, Fernando
Amicarelli, Adriana N.
author_role author
author2 Álvarez, Hernán
Dagatti, Carla Vanina
di Sciascio, Fernando
Amicarelli, Adriana N.
author2_role author
author
author
author
dc.subject.none.fl_str_mv Modelos Matemáticos
Análisis del Ciclo de Duración
Lobesia botrana
Crecimiento
Mathematical Models
Life Cycle Analysis
Growth
Growth Kinetics Equations
topic Modelos Matemáticos
Análisis del Ciclo de Duración
Lobesia botrana
Crecimiento
Mathematical Models
Life Cycle Analysis
Growth
Growth Kinetics Equations
dc.description.none.fl_txt_mv 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.
EEA Mendoza
Fil: Aguirre Zapata, Estefania. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). Instituto de Automática; Argentina
Fil: Aguirre Zapata, Estefania. Universidad Nacional de San Juan (UNSJ). Instituto de Automática; Argentina
Fil: Aguirre Zapata, Estefania. Universidad Nacional de Colombia. Facultad de Minas. Escuela de Procesos y Energía; Colombia
Fil: Álvarez, Hernán. Universidad Nacional de Colombia. Facultad de Minas. Escuela de Procesos y Energía; Colombia
Fil: Dagatti, Carla Vanina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Mendoza; Argentina
Fil: di Sciascio, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). Instituto de Automática; Argentina
Fil: di Sciascio, Fernando. Universidad Nacional de San Juan (UNSJ). Instituto de Automática; Argentina
Fil: Amicarelli, Adriana N. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). Instituto de Automática; Argentina
Fil: Amicarelli, Adriana N. Universidad Nacional de San Juan (UNSJ). Instituto de Automática; Argentina
description 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.
publishDate 2023
dc.date.none.fl_str_mv 2023-08
2026-04-17T14:26:19Z
2026-04-17T14:26:19Z
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12123/25853
https://www.sciencedirect.com/science/article/pii/S0304380023001382?via%3Dihub
0304-3800 (impresa)
1872-7026 (online)
https://doi.org/10.1016/j.ecolmodel.2023.110407
url http://hdl.handle.net/20.500.12123/25853
https://www.sciencedirect.com/science/article/pii/S0304380023001382?via%3Dihub
https://doi.org/10.1016/j.ecolmodel.2023.110407
identifier_str_mv 0304-3800 (impresa)
1872-7026 (online)
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/restrictedAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv restrictedAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv Ecological Modelling 482 : 110407. (August 2023)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
_version_ 1864547145562980352
score 13.1485815

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