PESTWIN
An innovative solution for precision agriculture: a biology-informed, AI-based intelligent and adaptive digital twin for prediction and management of infestations of the invasive insect Drosophila Suzukii.
Scheda del progetto
Biocentis srl
Università di Pavia
PESTWIN proposes the development of a digital twin, an advanced simulation model that combines biological and environmental data to facilitate the study of agricultural pests and enable more targeted and effective management. The digital twin will initially be applied to the fruit fly *Drosophila suzukii*, but it will be highly flexible and extendable in the future to other harmful insect species. The simulation environment will integrate biology, mathematics, physics, and artificial intelligence to create a tool capable of informing Integrated Pest Management (IPM) strategies, facilitating increased agricultural productivity and a reduction in the use of chemical insecticides.
Contacts:
Matteo Rucco
matteo.rucco@biocentis.com
Increasing agricultural productivity is a global priority, considering that by 2050, the world population is expected to reach 10 billion, with a projected demand for food and agricultural products rising by at least 50%. The challenge lies in minimising one of the main obstacles to agricultural productivity, which is the losses caused by harmful insects. Precision agriculture represents a promising approach to improving sustainability and agricultural productivity. However, precision agriculture has yet to be fully leveraged to optimise the control of harmful insects.
The project aims to develop the first example of an intelligent, adaptive digital twin that can simulate the behaviour of populations of harmful agricultural insects, such as *Drosophila suzukii* (SWD). The initiative seeks to go beyond the current state of the art by developing software for modelling and simulating the spatial dynamics of insects. The simulator will receive input data of various types—biological, population, and meteorological—and will produce forecasts regarding the dynamics of SWD populations.
The digital twin will provide significant benefits for users, including more efficient pest management, a reduction in chemical pesticides, and customised decision support. This approach would mitigate the economic damage caused by SWD and have positive impacts on food security and the environment, aligning with the Farm to Fork strategy. The transformative effect extends across scientific, economic, social, and environmental levels, promoting integrated pest management and enhancing agricultural sustainability and productivity.