inSilicow: from digital model to digital twin of dairy cattle farming system
2024
Martin, Olivier | Gaillard, Charlotte | Modélisation Systémique Appliquée aux Ruminants (MoSAR) ; AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Structure et fonctionnement de systemes écologiques - Laboratoire d'Écologie ; Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS) | Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE) ; Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Rennes Angers ; Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro) | Natural Resources Institute Finland - Luke
International audience
显示更多 [+] 显示较少 [-]英语. InSiliCow is an individual-based multi-scale dairy cow simulator. It is based on the integration of several conceptual, mathematical and computer layers ranging from the conceptual representation of the cow physiology to a computer architecture allowing to manage individual models of cows within a virtual herd. As a "digital model", it has reached the level of maturity to become a "digital twin" with a main scientific question in the evolving context of precision livestock farming: can a computer-simulated virtual farm be the basis for a useful decision-making tool for managing a real farm? This project implies: 1) the design and implementation of a computer twinning tool (for simulation and linkage of observed and simulated data), 2) the development of partnerships with candidate experimental farms to provide data and create their digital twin, and 3) the collaboration with partners leading scientific questions that can be addressed using digital twins. As agroecosystems, dairy farms are complex systems subject to the vagaries of changing markets, climate, landscapes and societal expectations. Understanding the drivers of their performance, robustness, efficiency and resiliency abilities are major issues to ensure the future of the dairy sector. The objective of the project is to operationalize the concept of a dairy farm digital twin into an innovating user-friendly online tool, and to establish the proof of concept of its usefulness to study and manage dairy systems.
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