The ongoing journey of modelling intercropping systems: A conceptual resource sharing intercomparison from model developers and expert users
6
Issued Date
2026-06-01
Resource Type
ISSN
03784290
eISSN
18726852
Scopus ID
2-s2.0-105037123595
Journal Title
Field Crops Research
Volume
343
Rights Holder(s)
SCOPUS
Bibliographic Citation
Field Crops Research Vol.343 (2026)
Suggested Citation
Adam A.M., Adam M., Asch F., Boote K.J., Chimonyo V.G.P., Christina M., Corbeels M., Couëdel A., De Freitas M., Della Chiesa T., Ewert F., Falconnier G.N., Fuchs K., Gaiser T., Giller K.E., Hoogenboom G., Huth N., Jibrin J.M., Justes E., Kamara A.Y., Kermah M., Khongdee N., Koomson E., Kraus D., Lana M., Laub M., Lusiana B., Marohn C., Moreno-Cadena P., Nendel C., Pansak W., Pavan W., Fils Pierre J., Poffenbarger H.J., Eyshi Rezaei E., Ruane A.C., Salmerón M., Scheer C., Seidel S.J., Simwaka P., Singh U., Six J., Srivastava A.K., van Noordwijk M., Volk J., Yu J., Cadisch G. The ongoing journey of modelling intercropping systems: A conceptual resource sharing intercomparison from model developers and expert users. Field Crops Research Vol.343 (2026). doi:10.1016/j.fcr.2026.110491 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/116538
Title
The ongoing journey of modelling intercropping systems: A conceptual resource sharing intercomparison from model developers and expert users
Author(s)
Adam A.M.
Adam M.
Asch F.
Boote K.J.
Chimonyo V.G.P.
Christina M.
Corbeels M.
Couëdel A.
De Freitas M.
Della Chiesa T.
Ewert F.
Falconnier G.N.
Fuchs K.
Gaiser T.
Giller K.E.
Hoogenboom G.
Huth N.
Jibrin J.M.
Justes E.
Kamara A.Y.
Kermah M.
Khongdee N.
Koomson E.
Kraus D.
Lana M.
Laub M.
Lusiana B.
Marohn C.
Moreno-Cadena P.
Nendel C.
Pansak W.
Pavan W.
Fils Pierre J.
Poffenbarger H.J.
Eyshi Rezaei E.
Ruane A.C.
Salmerón M.
Scheer C.
Seidel S.J.
Simwaka P.
Singh U.
Six J.
Srivastava A.K.
van Noordwijk M.
Volk J.
Yu J.
Cadisch G.
Adam M.
Asch F.
Boote K.J.
Chimonyo V.G.P.
Christina M.
Corbeels M.
Couëdel A.
De Freitas M.
Della Chiesa T.
Ewert F.
Falconnier G.N.
Fuchs K.
Gaiser T.
Giller K.E.
Hoogenboom G.
Huth N.
Jibrin J.M.
Justes E.
Kamara A.Y.
Kermah M.
Khongdee N.
Koomson E.
Kraus D.
Lana M.
Laub M.
Lusiana B.
Marohn C.
Moreno-Cadena P.
Nendel C.
Pansak W.
Pavan W.
Fils Pierre J.
Poffenbarger H.J.
Eyshi Rezaei E.
Ruane A.C.
Salmerón M.
Scheer C.
Seidel S.J.
Simwaka P.
Singh U.
Six J.
Srivastava A.K.
van Noordwijk M.
Volk J.
Yu J.
Cadisch G.
Author's Affiliation
ETH Zürich
Commonwealth Scientific and Industrial Research Organisation
Universität Bonn
Université de Montpellier
Wageningen University & Research
Universidad de Buenos Aires
Karlsruher Institut für Technologie
Sveriges lantbruksuniversitet
Herbert Wertheim College of Engineering
Universität Potsdam
Chiang Mai University
BOKU University
CIRAD
Universität Hohenheim
University of Zimbabwe
Julius Kühn-Institut - Federal Research Centre for Cultivated Plants
University of Kentucky College of Agriculture, Food and Environment
Bayero University
Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF) e. V.
NASA Goddard Institute for Space Studies
International Institute of Tropical Agriculture
Centro Internacional de Agricultura Tropical
Institut Amélioration Génétique et Adaptation des Plantes méditerranéennes et Tropicales (AGAP Institut)
Faculty of Environment and Resource Studies, Mahidol University
International Maize and Wheat Improvement Center, Harare
Agroécologie et Intensification Durable des Cultures Annuelles (AIDA)
International Center for Soil Fertility and Agricultural Development
International Institute of Tropical Agriculture
International Institute of Tropical Agriculture (IITA)
Center for International Forestry Research and World Agroforestry (CIFOR-ICRAF)
Research Institute of Organic Agriculture (FiBL)
Commonwealth Scientific and Industrial Research Organisation
Universität Bonn
Université de Montpellier
Wageningen University & Research
Universidad de Buenos Aires
Karlsruher Institut für Technologie
Sveriges lantbruksuniversitet
Herbert Wertheim College of Engineering
Universität Potsdam
Chiang Mai University
BOKU University
CIRAD
Universität Hohenheim
University of Zimbabwe
Julius Kühn-Institut - Federal Research Centre for Cultivated Plants
University of Kentucky College of Agriculture, Food and Environment
Bayero University
Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF) e. V.
NASA Goddard Institute for Space Studies
International Institute of Tropical Agriculture
Centro Internacional de Agricultura Tropical
Institut Amélioration Génétique et Adaptation des Plantes méditerranéennes et Tropicales (AGAP Institut)
Faculty of Environment and Resource Studies, Mahidol University
International Maize and Wheat Improvement Center, Harare
Agroécologie et Intensification Durable des Cultures Annuelles (AIDA)
International Center for Soil Fertility and Agricultural Development
International Institute of Tropical Agriculture
International Institute of Tropical Agriculture (IITA)
Center for International Forestry Research and World Agroforestry (CIFOR-ICRAF)
Research Institute of Organic Agriculture (FiBL)
Corresponding Author(s)
Other Contributor(s)
Abstract
Context: The global shift toward sustainable agriculture has increased interest in using process-based models to design and optimize intercropping systems. However, these models differ fundamentally in how they represent trade-offs (competition for light, water, and nutrients) and synergies (facilitation, complementarity) in resource sharing between species. This conceptual variation creates uncertainty in model selection and application, particularly since most models were originally developed for monoculture and subsequently adapted for intercropping. Objective: In this study, we describe how current crop models represent interspecies resource-sharing mechanisms, analyse their structural differences, and synthesize findings from existing validation studies to understand how their structural differences affect model performance. The models examined include APSIM (APSIM-Canopy, APSIM-Micromet, APSIM-Strip, APSIM-Alternating, APSIM-APSwim, APSIM-SoilArbitrator), DayCent, DSSAT-Mixed, DSSAT-MPI, LandscapeDNDC, LUCIA, MONICA, SIMPLACE Lintul5-Intercrop, STICS-Big-Leaf, STICS-Multilayer, and WaNuLCAS. Methods: Through the Agricultural Model Intercomparison and Improvement Project (AgMIP) platform, we engaged with model developers and expert users to collect detailed information on how crop models represent intercropping systems using structured interviews and questionnaires. We then developed a framework that groups models by their core conceptual approaches to simulating resource sharing. Finally, we synthesize findings from existing quantitative validation studies to connect conceptual intercomparison to predictive performance across different intercrop characteristics and environments. Results and Conclusions: Our analysis identifies six distinct conceptual approaches for simulating light sharing and four for belowground resource (water and nutrient) competition. Intercrop models show greater structural divergence in canopy than in belowground representation. Furthermore, competitive trade-offs (light, water, and nutrients) are widely represented while facilitative and other complex processes like N₂-fixation, plasticity (shoot and root), microclimate effects or hydraulic lift are often simplified or omitted. Our analysis of model validation studies reveals a critical trade-off: structurally complex models often perform well in simulating intercropping when calibration is done on sole crops, whereas simpler models require extensive intercrop-specific calibration to achieve better prediction performance. This distinction is vital for model application in data-scarce environments, as more complex architectures can leverage existing sole-crop data to effectively simulate intercrop systems. The classification of the structural resource capture differences in combination with the evaluated model performance analysis allowed us to devise an evidence-based model selection criteria framework useful also for for non-specialist, while the unique detailed description provided are highly valuable for the model research community. Significance: This study establishes a conceptual framework that provides the necessary foundation for a meaningful quantitative intercomparison of intercrop models, as structural understanding enables the interpretation of numerical differences in model outputs. It also guides hypothesis testing, model choice, priorities in model development and improvements.