Semi physical growth model of Lobesia botrana under laboratory conditions for Argentina’s Cuyo region

Lobesia botrana is a quarantine pest from Argentina and other countries in the world. It causes damage to the vine in its different growth stages leading to losses in wine production. To develop pest control strategies based on knowledge of the moth, different mathematical models can be found in spe...

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Main Authors: Aguirre Zapata, Estefania, Morales, Humberto, Dagatti, Carla Vanina, Di Sciascio, Fernando, Amicarelli, Adriana N.
Format: Artículo
Language:Inglés
Published: Elsevier 2021
Subjects:
Online Access:http://hdl.handle.net/20.500.12123/10957
https://www.sciencedirect.com/science/article/abs/pii/S0304380021003483
https://doi.org/10.1016/j.ecolmodel.2021.109803
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author Aguirre Zapata, Estefania
Morales, Humberto
Dagatti, Carla Vanina
Di Sciascio, Fernando
Amicarelli, Adriana N.
author_browse Aguirre Zapata, Estefania
Amicarelli, Adriana N.
Dagatti, Carla Vanina
Di Sciascio, Fernando
Morales, Humberto
author_facet Aguirre Zapata, Estefania
Morales, Humberto
Dagatti, Carla Vanina
Di Sciascio, Fernando
Amicarelli, Adriana N.
author_sort Aguirre Zapata, Estefania
collection INTA Digital
description Lobesia botrana is a quarantine pest from Argentina and other countries in the world. It causes damage to the vine in its different growth stages leading to losses in wine production. To develop pest control strategies based on knowledge of the moth, different mathematical models can be found in specific literature to predict its biological cycle, establish its relationship with environmental variables, describe the voltinism of the pest, among others. Based on the proposed models, it is possible to establish a minimum temperature threshold considering the development of the moth and the number of degrees’ days (DD) that must be accumulated for there to be a change of stage. Many of these models are empirical. They are limited because they do not consider some variables such as growth and mortality rates, also they lack a conceptual basis. This makes that professionals or institutions interested in the development of decision support systems (DSS) may not use them. This also prevents them from being easily extrapolated to other regions of the world. In this work, a semi-physical model based on first principles (FPBSM) is proposed to describe how the different growth stages of the vine moth change quantitatively throughout its normal development time under controlled and specific laboratory conditions for the Cuyo region in Argentina. The proposed model, based on a white box structure, considers important parameters in the development of the moth, such as growth and mortality rates. Opposite to the models reported in the literature, the proposed model is conceptually more simple, easy to calculate or adjust, and Its parameters are interpretable in the model’s application context. The previous characteristics facilitate the proposal model’s use by sectors interested in the development of DSS systems. The reported mathematical model has been validated with experimental data for three different temperature conditions.
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institution Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina)
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spelling INTA109572021-12-21T11:37:37Z Semi physical growth model of Lobesia botrana under laboratory conditions for Argentina’s Cuyo region Aguirre Zapata, Estefania Morales, Humberto Dagatti, Carla Vanina Di Sciascio, Fernando Amicarelli, Adriana N. Vid Lobesia Ciclo Vital Modelos Matemáticos Argentina Grapevines Life Cycle Mathematical Models Región Cuyana Lobesia botrana is a quarantine pest from Argentina and other countries in the world. It causes damage to the vine in its different growth stages leading to losses in wine production. To develop pest control strategies based on knowledge of the moth, different mathematical models can be found in specific literature to predict its biological cycle, establish its relationship with environmental variables, describe the voltinism of the pest, among others. Based on the proposed models, it is possible to establish a minimum temperature threshold considering the development of the moth and the number of degrees’ days (DD) that must be accumulated for there to be a change of stage. Many of these models are empirical. They are limited because they do not consider some variables such as growth and mortality rates, also they lack a conceptual basis. This makes that professionals or institutions interested in the development of decision support systems (DSS) may not use them. This also prevents them from being easily extrapolated to other regions of the world. In this work, a semi-physical model based on first principles (FPBSM) is proposed to describe how the different growth stages of the vine moth change quantitatively throughout its normal development time under controlled and specific laboratory conditions for the Cuyo region in Argentina. The proposed model, based on a white box structure, considers important parameters in the development of the moth, such as growth and mortality rates. Opposite to the models reported in the literature, the proposed model is conceptually more simple, easy to calculate or adjust, and Its parameters are interpretable in the model’s application context. The previous characteristics facilitate the proposal model’s use by sectors interested in the development of DSS systems. The reported mathematical model has been validated with experimental data for three different temperature conditions. EEA Mendoza Fil: Aguirre Zapata, Estefania. Universidad Nacional de San Juan. Instituto de Automática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Automática; Argentina Fil: Aguirre Zapata, Estefania. Universidad Nacional de Colombia. Facultad de Minas. Escuela de Procesos y Energía; Colombia Fil: Morales, Humberto. Universidad Nacional de San Juan. Instituto de Automática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Automática; Argentina Fil: Dagatti, Carla Vanina. Instituto Nacional de Tecnologia Agropecuaria (INTA). Estación Experimental Agropecuaria Mendoza; Argentina Fil: di Sciascio, Fernando. Universidad Nacional de San Juan. Instituto de Automática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Automática; Argentina Fil: Amicarelli, Adriana N. Universidad Nacional de San Juan. Instituto de Automática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Automática; Argentina 2021-12-21T11:29:39Z 2021-12-21T11:29:39Z 2021-12-21 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/10957 https://www.sciencedirect.com/science/article/abs/pii/S0304380021003483 0304-3800 https://doi.org/10.1016/j.ecolmodel.2021.109803 eng info:eu-repo/semantics/restrictedAccess application/pdf Elsevier Ecological Modelling 464 : 109803 (February 2022)
spellingShingle Vid
Lobesia
Ciclo Vital
Modelos Matemáticos
Argentina
Grapevines
Life Cycle
Mathematical Models
Región Cuyana
Aguirre Zapata, Estefania
Morales, Humberto
Dagatti, Carla Vanina
Di Sciascio, Fernando
Amicarelli, Adriana N.
Semi physical growth model of Lobesia botrana under laboratory conditions for Argentina’s Cuyo region
title Semi physical growth model of Lobesia botrana under laboratory conditions for Argentina’s Cuyo region
title_full Semi physical growth model of Lobesia botrana under laboratory conditions for Argentina’s Cuyo region
title_fullStr Semi physical growth model of Lobesia botrana under laboratory conditions for Argentina’s Cuyo region
title_full_unstemmed Semi physical growth model of Lobesia botrana under laboratory conditions for Argentina’s Cuyo region
title_short Semi physical growth model of Lobesia botrana under laboratory conditions for Argentina’s Cuyo region
title_sort semi physical growth model of lobesia botrana under laboratory conditions for argentina s cuyo region
topic Vid
Lobesia
Ciclo Vital
Modelos Matemáticos
Argentina
Grapevines
Life Cycle
Mathematical Models
Región Cuyana
url http://hdl.handle.net/20.500.12123/10957
https://www.sciencedirect.com/science/article/abs/pii/S0304380021003483
https://doi.org/10.1016/j.ecolmodel.2021.109803
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