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Adapting physics-informed neural networks to improve ODE optimization in mosquito population dynamics

  • Writer: Angeliki Milioti
    Angeliki Milioti
  • Mar 10
  • 1 min read

Updated: 7 minutes ago

We are pleased to announce that a scientific paper developed in the context of the TALLHEDA project has been published in the peer-reviewed journal PLOS ONE, under the title:"Mapping the European research and innovation landscape on digital transformation in agriculture."


This publication represents a significant contribution to understanding the current dynamics, gaps, and opportunities in digital transformation within the European agricultural sector. It aligns closely with the mission of TALLHEDA to promote evidence-based research, knowledge exchange, and strategic policy alignment in the context of digital innovation in agriculture.


📚 About the Paper

The study provides a comprehensive mapping and bibliometric analysis of research and innovation activities related to digital agriculture across Europe. Using advanced data analysis methods, the authors evaluate:

  • The evolution of digital agriculture research output in Europe

  • Key thematic clusters such as precision farming, agri-data, robotics, and sustainable practices

  • Country-level performance, highlighting both leading and Widening countries

  • The role of EU funding frameworks, including Horizon Europe, in supporting digital transformation

  • Gaps in current research and opportunities for future collaboration and investment

One of the paper’s important findings is the identification of a growing divide between countries with high research intensity in digital agriculture and those with emerging capacity—a divide TALLHEDA directly addresses through its capacity-building and alliance-building efforts.

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TALLHEDA
EU

Project coordination

Prof. Konstantinos Demestichas

cdemest@aua.gr

Agricultural University of Athens

Project communication

MSc Angeliki Milioti

angeliki@smartagrohub.gr

Smart Agro Hub

Project Framework

TALLHEDA has received funding from the European Union's Horizon Europe research and innovation programme under Grant Agreement No. 101136578.

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency (REA). Neither the European Union nor the granting authority can be held responsible for them.

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