Semi physical growth model of Lobesia botrana under laboratory conditions for Argentina’s Cuyo region - Aguirre Zapata, Estefania (2021)
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.