Research priorities to leverage smart digital technologies for sustainable crop production

Agriculture faces several challenges including climate change and biodiversity loss while, at the same time, the demand for food, feed, biofuels, and fiber is increasing. Sustainable intensification aims to increase productivity and input-use efficiency while enhancing the resilience of agricultural systems to adverse environmental conditions through improved management and technology. Recent advances in sensing, machine learning, modeling, and robotics offer opportunities for novel smart digital technologies to enable sustainable intensification. However, developing smart digital technologies and putting them into agricultural practice, requires closing major research gaps, related in particular to (1) the utilization of multi-scale multi-sensor monitoring in space and time, (2) using artificial intelligence for linking process and data-driven methods, (3) improving decision making and intervention in plant production, and finally (4) modeling conditions and consequences of farmers acceptance. Closing these gaps requires an interdisciplinary approach. Here, we present a research agenda and steps forward to steer research efforts, highlighting research priorities, and identifying required interdisciplinary research collaboration. Following this agenda will leverage the full potential of smart digital technologies for sustainable crop production.

  • Published in:
    European Journal of Agronomy
  • Type:
    Article
  • Authors:
    Storm, Hugo; Seidel, Sabine Julia; Klingbeil, Lasse; Ewert, Frank; Vereecken, Harry; Amelung, Wulf; Behnke, Sven; Bennewitz, Maren; Börner, Jan; Döring, Thomas; Gall, Juergen; Mahlein, Anne-Katrin; McCool, Chris; Rascher, Uwe; Wrobel, Stefan; Schnepf, Andrea; Stachniss, Cyrill; Kuhlmann, Heiner
  • Year:
    2024
  • Source:
    https://www.sciencedirect.com/science/article/pii/S1161030124000996

Citation information

Storm, Hugo; Seidel, Sabine Julia; Klingbeil, Lasse; Ewert, Frank; Vereecken, Harry; Amelung, Wulf; Behnke, Sven; Bennewitz, Maren; Börner, Jan; Döring, Thomas; Gall, Juergen; Mahlein, Anne-Katrin; McCool, Chris; Rascher, Uwe; Wrobel, Stefan; Schnepf, Andrea; Stachniss, Cyrill; Kuhlmann, Heiner: Research priorities to leverage smart digital technologies for sustainable crop production, European Journal of Agronomy, 2024, 156, https://www.sciencedirect.com/science/article/pii/S1161030124000996, Storm.etal.2024a,

Associated Lamarr Researchers

lamarr institute person Behnke Sven - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

Prof. Dr. Sven Behnke

Area Chair Embodied AI to the profile
lamarr institute person Bennewitz Maren - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

Prof. Dr. Maren Bennewitz

Principal Investigator Embodied AI to the profile
lamarr institute person McCool Chris 1 - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

Prof. Dr. Chris McCool

Principal Investigator Embodied AI to the profile
lamarr institute person Wrobel Stefan e1663925461852 - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

Prof. Dr. Stefan Wrobel

Director to the profile
lamarr institute person Stachniss Cyrill e1663922306234 - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

Prof. Dr. Cyrill Stachniss

Principal Investigator Embodied AI to the profile