Developing AI-powered microclimate models and yield forecasting tools for climate-smart agroforestry in Germany

Ahmed M.S. Kheir; Navid Bakhtiary; Juvenal Assou; Maren Langhof; Jörn Strassemeyer; Ashifur Rahman Shawon; Priscilla N. Kephe; Til Feike

doi:10.1016/j.agrformet.2026.111157

journal article Open Access Jun 01, 2026

Developing AI-powered microclimate models and yield forecasting tools for climate-smart agroforestry in Germany

Ahmed M.S. Kheir Navid Bakhtiary Juvenal Assou Maren Langhof Jörn Strassemeyer Ashifur Rahman Shawon

Priscilla N. Kephe Til Feike

Agricultural and Forest Meteorology Vol. 384 pp. 111157 · Elsevier BV

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Published: Jun 01, 2026
Vol/Issue: 384
Pages: 111157
License: View

Authors

Ashifur Rahman Shawon

Julius Kühn Institute (JKI)—Federal Research Centre for Cultivated Plants, Institute for Strategies and Technology Assessment, Stahnsdorfer Damm 81, 14532 Kleinmachnow, Germany

Funding

Bundesministerium für Ernährung und Landwirtschaft Award: FKZ 2822KLI006

Bundesanstalt für Landwirtschaft und Ernährung

Cite This Article

Ahmed M.S. Kheir, Navid Bakhtiary, Juvenal Assou, et al. (2026). Developing AI-powered microclimate models and yield forecasting tools for climate-smart agroforestry in Germany. Agricultural and Forest Meteorology, 384, 111157. https://doi.org/10.1016/j.agrformet.2026.111157

Developing AI-powered microclimate models and yield forecasting tools for climate-smart agroforestry in Germany

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