Current knowledge and future research opportunities for modeling annual crop mixtures. A review
No\'emie Gaudio, Abraham J. Escobar-Guti\'errez, Pierre Casadebaig,, Jochem B. Evers, Fr\'ed\'eric G\'erard, Ga\"etan Louarn, Nathalie Colbach,, Sebastian Munz, Marie Launay, H\'el\`ene Marrou, Romain Barillot, Philippe, Hinsinger, Jacques-Eric Bergez, Didier Combes

TL;DR
This review discusses the current state and future research directions for modeling annual crop mixtures, emphasizing the suitability of crop and individual-based models for understanding and designing diverse cropping systems.
Contribution
It provides a comprehensive assessment of existing crop modeling approaches for annual mixtures and offers guidance on selecting appropriate models based on research questions.
Findings
Few crop models are adapted for mixtures.
Models mainly address management and larger-scale integration.
Individual-based models help identify traits and ecological processes.
Abstract
Growing mixtures of annual arable crop species or genotypes is a promising way to improve crop production without increasing agricultural inputs. To design optimal crop mixtures, choices of species, genotypes, sowing proportion, plant arrangement, and sowing date need to be made but field experiments alone are not sufficient to explore such a large range of factors. Crop modeling allows to study, understand and ultimately design cropping systems and is an established method for sole crops. Recently, modeling started to be applied to annual crop mixtures as well. Here, we review to what extent crop simulation models and individual-based models are suitable to capture and predict the specificities of annual crop mixtures. We argued that: 1) The crop mixture spatio-temporal heterogeneity (influencing the occurrence of ecological processes) determines the choice of the modeling approach…
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