Models Applied to Grapevine Pests: A Review

Abstract

This paper reviews the existing predictive models concerning insects and mites harmful to grapevine. A brief conceptual description is given on the definition of a model and about different types of models: deterministic vs. stochastics, continuous vs. discrete, analytical vs. computer-based, and descriptive vs. data-driven. The main biological aspects of grapevine pests covered by different types of models are phenology, population growth and dynamics, species distribution, and invasion risk. A particular emphasis is put on forecasting epidemics of plant disease agents transmitted by insects with sucking-piercing mouthparts. The most investigated species or groups are the glassy-winged sharpshooter Homalodisca vitripennis (Germar) and other vectors of Xylella fastidiosa subsp. fastidiosa, a bacterium agent of Pierce’s disease; the European grape berry moth, Lobesia botrana (Denis and Schiffermuller); and the leafhopper Scaphoideus titanus Ball, the main vector of phytoplasmas agents of Flavescence dorée. Finally, the present and future of decision-support systems (DSS) in viticulture is discussed.

Predicting the incidence and severity of wheat aphids and development of a web-enabled forewarning system in India

“…However, here weather data collected from the time of sowing until the time of the aphids' first appearance were integrated to develop informative weather indices. This approach may also take care of various biological phenomenons of the pests (like life cycle) as well as of the crops (Lessio and Alma, 2021) . Kumar et al: Forewarning system for wheat aphids (2019) also found temperature and humidity as key contributing exogenous factors in their prediction models to determine the abundance of Trialeurodes vaporariorum in greenhouses.…”

Metodología para el modelado y la estimación de parámetros del proceso de crecimiento de Lobesia botrana

“…Así pues, se encuentran en la literatura modelos, como el presentado por Touzeau en el año 1981 (Touzeau, 1981), y que se ha constituido como uno de los modelos más utilizados para representar el proceso de crecimiento de Lobesia botrana con relación a la temperatura. Trabajos más recientes, como los presentados por Lessio y Alma en (Lessio and Alma, 2021), presentaron un panorama amplio con relación al modelado de L. botrana y otras plagas que afectan el desarrollo de la vid, destacando que, si bien los modelos de caja negra o derivados del ajuste de datos, son utilizados para predecir el comportamiento o aparición de la polilla para ciertas condiciones climáticas dadas, carecen de una base conceptual que facilite su uso por parte de viticultores, enólogos, profesionales de soporte técnico, servicios fitosanitarios y otras partes interesadas. Para dar solución a lo anterior, se encuentran en la literatura, modelos semi físicos basados en primeros principios (FPBSM -por sus siglas en inglés) como el presentado en (Aguirre-Zapata et al, 2022).…”

A general ODE-based model to describe the physiological age structure of ectotherms: Description and application to Drosophila suzukii

“…This is due to at least two reasons: i) in agriculture measuring is economically expensive, and for many crops probably it will likely never be realistic to perform a continuous monitoring of all plants; ii) in order to plan effective treatments is important not only to measure the current status of the farm, but also to predict the future evolution of the infestations. Accordingly, in parallel with the technological research, it is fundamental to develop mathematical models able to describe and predict the evolution of the infestations [8].…”

“…Many scientists around the world are currently working on the mathematical modelling of insect pests population dynamics [8,9,10,11]. Pest population models are particularly important when pest management is performed through the release of natural enemies, the use of which is rapidly growing among farmers and is one of the core aspects of the so-called Integrated Pest Management (IPM) framework.…”

“…Insects, like most ectotherms, progress through their life stages with development speeds that are highly dependent on the environmental parame-ters, temperature mainly [13]. This concept is well known by entomologists [8], at the point that several authors provided mathematical expressions to describe the development rate as a function of the temperature [14,15,16] (and references therein). The proliferation of mathematical expressions describing the relationship between ectotherms and environmental parameters such as temperature laid the foundations for the so-called "physiologicallybased models".…”