AgMIP-Wheat

Main Contacts for Initiative

Senthold Asseng, Pierre Martre, Heidi Webber & Frank Ewert

Linked with the program on Wheat Plant and Crop Modelling of the international Wheat Initiative.

 

Brief Description of Activity

AgMIP-Wheat started in 2010 and aims to improve, expand and apply wheat crop models in climate change impact and adaptation assessments by bringing together crop modelers, experimentalists, plant breeders, biostatisticians and climate scientists working with field measurements and future scenarios. We explore applications for point simulations for upscaling and compare methods for impact assessments.

 

List of Participating Models (alphabetical)

  1. AFRCWHEAT2, request from jrp@plen.ku.dk
  2. AQUACROP
  3. APSIM-Next Generation
  4. APSIM-Wheat
  5. CropSyst
  6. DAISY
  7. DSSAT-CERES
  8. DSSAT-CROPSIM
  9. DSSAT-NWheat
  10. EPIC-Wheat
  11. Expert-N – CERES
  12. Expert-N – GECROS
  13. Expert-N – SPASS
  14. Expert-N – SUCROS
  15. GLAM
  16. HERMES
  17. LINTUL
  18. LPJmL
  19. MCWLA-Wheat, request from taofl@igsnrr.ac.cn
  20. MONICA
  21. OLEARY, request from gjoleary@yahoo.com
  22. pyGECROS
  23. SALUS
  24. SIMPLACE
  25. SIRIUS
  26. SiriusQuality
  27. SSM-Wheat, request from bindi@unifi.it
  28. STICS
  29. WHEATGROW, request from yanzhu@njau.edu.cn
  30. WOFOST

Figure 1: Meetings times, location and start of new activities of AgMIP-Wheat. The idea of the AgMIP-Wheat team was conceived in November 2010 at the first Global AgMIP Workshop at Long Beach in California. The AgMIP Wheat Team is organised since 2020 in several specific activities (see table below) with focus on model improvement. AgMIP-Wheat meets regularly to discuss progress, to explore new ideas and to decide on new research agendas. 

Figure 2: Measured (orange) and multi-model ensemble simulated (green) wheat grain protein concentration under different climatic (dry/wet and moderate/hot) and elevated CO2 conditions. After Asseng et al. (2019). Error bars show 1 s.e. of measured and simulated mean.

AgMIP-Wheat Activities and Contacts

Traits

Pierre Martre, Senthold Asseng, Heidi Webber & Frank Ewert

AgMIP-Wheat Traits combines field experiments and crop physiology to quantify the impact of traits, the size of a trait change, and trait combinations on wheat grain yield potential. Simulated trait impact scenarios are created to guide breeding towards the most effective traits and trait combinations for future climate scenarios and wheat across the world. This research has been supported by the International Wheat Yield Partnership (IWYP, grant No. IWYP115).

 

Ozone

 

Website

Waterlogging

Taru Palosuo, Margarita García-Vila, Matthew Harrison, Ke Liu, Rogério de Souza Nóia Júnior,

Murilo Vianna, Tobias Weber & Jin Zhao

AgMIP-Wheat Waterlogging tests with field observations, develops and improves model routines to simulate transient waterlogging and to explore the impact of climate change, particularly of increased rainfall intensity, on crop growth and yield.

 Nitrogen

Enli Wang & Zhigan Zhao

AgMIP-Wheat Nitrogen tests with field observations, develops and improves model routines to simulate crop and soil nitrogen dynamics to explore the impact of climate change on crop nitrogen use, nitrogen losses and crop yield.

Evapotranspiration

Heidi Webber

AgMIP-Wheat Evapotranspiration tests models with field observations and improves model routines related to evapotranspiration in wheat models to explore the impact of climate change on crop water use.

Calibration

 

Website

 

CO2

Davide Cammarano

AgMIP-Wheat CO2 tests models with field observations (FACE experiments) and improves model routines related to cultivar specific response to elevated atmospheric CO2 concentrations and its impact on crop growth and yield under future climate change scenarios. 

Pest and Diseases

Roberto Ferrise

AgMIP-Wheat Pest and Diseases develops and tests with field observations model routines related to pest and disease impact in wheat models, considering major diseases such as leaf rust, yellow rust, Septoria tritici blotch, and powdery mildew to explore the interplay of climate change scenarios, crop management, and crop protection strategies on disease dynamics and crop performance, to provide insights for designing sustainable cropping systems that explicitly account for the impact of plant diseases under future climatic conditions.

Bias and Correction

 Stefano Galmarini

AgMIP-Wheat Bias and Correction evaluates whether multivariate bias adjustment of cross-correlated climate variables improves crop model performance compared to univariate adjustments using bias adjustment methods applied to several variables across locations, compared to AgMERRA re-analysis as a reference.

New Planned AgMIP-Wheat Activities

 

Crop and biodiversity (not started yet)

Current contact: Senthold Asseng

Risk of yield and leaching 

Yean-Uk Kim, Heidi Webber, Pierre Martre

Sink source relationship

Carolina Rivera-Amado, Senthold Asseng, Pierre Martre, Enli Wang

Overview of Participants

  • ~30 wheat crop modeling groups from 15 countries
  • Field experimentalists and breeders from CIMMYT Mexico, Universidad Austral, Chile, University of Buenos Aires, Argentina, INRAE, France, ARVALIS, France, Crop and Food New Zealand and CSIRO Australia
  • A biostatistician and climate scientists.

Current Research Focus

  • Model improvement across several activities on evapotranspiration, canopy temperature, CO2, N supply, ozone, calibration, extreme events and waterlogging following the AgMIP-Wheat approach outlined by Wang and Martre et al. (2017).
  • exploring new activities on model improvement, risk assessment, source-sink relationship and considering disease interactions and biodiversity.

Figure 3: Cover page of Nature Plants publication on model improvement from AgMIP-Wheat. Temperature functions in models and derived from experiments after Wang and Martre et al. (2017).  

Figure 4: AgMIP-Wheat workshop, Beijing, China, July 2024.

Papers Recently Published

Martre et al., 2024. “Global needs for nitrogen fertilizer to improve wheat yield under climate change.” NATURE PLANTS 10. https://doi.org/10.1038/s41477-024-01739-3.
Wang et al., 2024. “Pathways to identify and reduce uncertainties in agricultural climate impact assessments.” NATURE FOOD 5: 550-556. https://doi.org/10.1038/s43016-024-01014-w.
Guarin et al., 2024. “Modeling the effects of tropospheric ozone on the growth and yield of global staple crops with DSSAT v4.8.0.” Geoscientific Model Development 17 (7): 2547-2567. https://doi.org/10.5194/gmd-17-2547-2024.
Kim et al., 2024. “Mechanisms and modelling approaches for excessive rainfall stress on cereals: Waterlogging, submergence, lodging, pests and diseases.” Agricultural and Forest Meteorology 344. https://doi.org/10.1016/j.agrformet.2023.109819.
Galmarini et al., 2024. “Assessing the impact on crop modelling of multi- and uni-variate climate model bias adjustments.” Agricultural Systems 215. https://doi.org/10.1016/j.agsy.2023.103846.
Nóia et al., 2023. “A call to action for global research on the implications of waterlogging for wheat growth and yield.” Agricultural Water Management 284. https://doi.org/10.1016/j.agwat.2023.108334.
Dueri et al., 2022. “Simulation of winter wheat response to variable sowing dates and densities in a high-yielding environment.” Journal of Experimental Botany 73 (16): 5715-5729. https://doi.org/10.1093/jxb/erac221.
Guarin et al., 2022. “Evidence for increasing global wheat yield potential.” Environmental Research Letters 17 (12). https://doi.org/10.1088/1748-9326/aca77c.

 

Recent Noteworthy Finding: “New wheat varieties can contribute to food security”

Martre et al., 2024. “Global needs for nitrogen fertilizer to improve wheat yield under climate change.” NATURE PLANTS 10. https://doi.org/10.1038/s41477-024-01739-3.

Wheat is the world’s most important grain. But it has high environmental costs due to the need to fertilize with nitrogen. The AgMIP-Wheat Team has now determined that new wheat varieties produce better crops with the same quantities of fertilizer. It is not always easy to find the right amount of fertilizer for wheat crops. If too little is applied, it is completely used up, but the harvest falls short of its full potential. And if too much is used, the harvest is good but the growing grain does not consume all of the fertilizer. The surplus nitrogen finds its way into the environment and damages ecosystems and the climate. But wheat is essential for satisfying the growing hunger in the world.

To overcome these challenges, we have investigated new wheat cultivars still in the experimental stages. Their results have been published in Nature Plants. The team used data from five experimental fields representing global wheat producing regions with particularly high yields. The fields were included into a simulation model with other fields and analyzed under three climate scenarios: the climate conditions of today and global warming of 1 degree Celsius and 4.8 degrees Celsius. The results show the yields that can be expected from the tested varieties when different quantities of nitrogen fertilizer are applied.

The research showed that the new wheat cultivars achieve 16 % higher yields under current climate conditions than those now used if the same quantities of fertilizer are applied. Through improved utilization of the nitrogen, i.e. greater nitrogen efficiency, the ecological footprint is reduced. However, the team also showed that overall nitrogen needs will increase in the course of global warming if the full yield potential of the plants is to be achieved – although the new cultivars will still use nitrogen more efficiently than current varieties.

We recommend the continued use of the cultivars tested in the model in breeding programs. With improved selective breeding we can close the food gap for the next 20 to 30 years. But new varieties alone will not be sufficient to reconcile the conflicting goals of global food security, environmental protection and cost-effectiveness. What we need is a systemic approach that takes into account agricultural science methods, environmental aspects, socio-economic factors and policy makers.

 

 

References

Papers

  1. Martre P, Dueri S, Guarin JR, Ewert F, Webber H, Calderini D, Molero G, Reynolds M, Miralles D, Garcia G, Brown H, George M, Craigie R, Cohan JP, Deswarte JC, Slafer G, Giunta F, Cammarano D, Ferrise R, Gaiser T, Gao Y, Hochman Z, Hoogenboom G, Hunt LA, Kersebaum KC, Nendel C, Padovan G, Ruane AC, Srivastava AK, Stella T, Supit I, Thorburn P, Wang E, Wolf J, Zhao C, Zhao Z, Asseng S (2024) Global needs for nitrogen fertilizer to improve wheat yield under climate change. Nature Plants. https://doi.org/10.1038/s41477-024-01739-3
  2. Wang B, Jägermeyr J, O’Leary GJ, Wallach D, Ruane AC, Feng P, Li L, Liu DL, Waters C, Yu Q, Asseng S; Rosenzweig C (2024). Pathways to identify and reduce uncertainties in agricultural climate impact assessments. Nature Food. https://doi.org/10.1038/s43016-024-01014-w
  3. Guarin JR, Jägermeyr J, Ainsworth EA, Oliveira F, Asseng S, Boote K, Elliott J, Emberson L, Foster I, Hoogenboom G, Kelly D, Ruane AC, Sharps K (2024). Modeling the effects of tropospheric ozone on the growth and yield of global staple crops with DSSAT v4.8.0. Geoscientific Model Development. https://doi.org/10.5194/gmd-17-2547-2024
  4. Kim YU, Webber H, Adiku SGK, de S. Nóia Júnior R, Deswarte JC, Asseng S, Ewert F (2024) Mechanisms and modelling approaches for excessive rainfall stress on cereals: Waterlogging, submergence, lodging, pests and diseases. Agricultural and Forest Meteorology. https://doi.org/10.1016/j.agrformet.2023.109819
  5. Galmarini S, Solazzo E, Ferrise R, Kumar Srivastava A, Ahmed M, Asseng S, Cannon AJ , Dentener F, De Sanctis G, Gaiser T, Gao Y, Gayler S, Gutierrez JM, Hoogenboom G, Iturbide M, Jury M, Lange S, Loukos H, Maraun D, Moriondo M, McGinnis S, Nendel C, Padovan G, Riccio A, Ripoche D, Stockle CO, Supit I, Thao S, Trombi G, Vrac M, Weber TKD, Zhao C (2024) Assessing the impact on crop modelling of multi- and uni-variate climate model bias adjustments. Agricultural Systems. https://doi.org/10.1016/j.agsy.2023.103846
  6. de Souza Nóia Júnior R, Asseng S, García-Vila M, Liu K, Stocca V, dos Santos Vianna M, Weber T, Zhao J, Palosuo T ,Harrison M (2023) A call to action for global research on the implications of waterlogging for wheat growth and yield. Agricultural Water Management. https://doi.org/10.1016/j.agwat.2023.108334
  7. Dueri S, Brown H, Asseng S, Ewert F, Webber H, George M, Craigie R, Guarin JR, Pequeno DNL, Stella T, Ahmed1 M, Alderman PD, Basso B, Berger AG, Mujica GB, Cammarano D, Chen Y, DumontB, Rezaei EE, Fereres E, Ferrise R, Gaiser T, Gao Y, Garcia-Vila M, Gayler S, Hochman Z, Hoogenboom G, Kersebaum KC, Nendel C, Olesen JE, Padovan G, Palosuo T, Priesack E, Pullens JWM, Rodríguez A, Rötter RP, Ruiz Ramos M, Semenov MA, Senapati N, Siebert S, Srivastava AK, Stöckle C, Supit I, Tao F, Thorburn P, Wang E, Weber TKD, Xiao L, Zhao C, Zhao J, Zhao Z, ZhuY, Martre P (2022) Simulation of winter wheat response to variable sowing dates and densities in a high-yielding environment. Journal of Experimental Botany. https://doi.org/10.1093/jxb/erac221
  8. Guarin JR, Martre P, Ewert F, Webber H, Dueri S, Calderini D, Reynolds M, Molero G, Miralles D, Garcia G, Slafer G, Giunta F, Pequeno DNL, Stella T, Ahmed M, Alderman PD, Basso B, Berger AG, Bindi M, Bracho-Mujica G, Cammarano D, Chen Y, Dumont B, Rezaei EE, FereresE, Ferrise R, Gaiser T, GaoY, Garcia-Vila M, Gayler S, Hochman Z, HoogenboomG, Hunt LA, Kersebaum KC, NendelC, Olesen JE, Palosuo T, PriesackE, Pullens JWM, Rodríguez A, Rötter RP, Ruiz Ramos M, Semenov MA, Senapati N, Siebert S, Srivastava AK, StöckleC, Supit I, Tao F, Thorburn P, Wang E, T Weber TKD, XiaoL, Zhang Z, Zhao C, Zhao J, Zhao Z, ZhuY, Asseng S  (2022) Evidence for increasing global wheat yield potential. Environmental Research Letters. https://doi.org/10.1088/1748-9326/aca77c  
  9. Wallach D, Palosuo T, Thorburn P, Hochman Z, Gourdain E, Andrianasolo F, Asseng S, BassoB, Buis S, Crout N, Dibari C, Dumont B, Ferrise R, Gaiser T, Garcia C, Gayler S, Ghahramani A, Hiremath S, Hoek S, Horan H, Hoogenboom G, Huang M, Jabloun M, Jansson PE, Jing Q, Justes E, Kersebaum KC, Klosterhalfen A, Launay M, Lewan E, Luo Q, Maestrini B, Mielenz H, Moriondo M, Zadeh HN, Padovan G, Olesen JE, Poyda A, Priesack E, Pullens JWM, Qian B, Schütze N, Shelia V, Souissi A, Specka X, Srivastava AK, Stella T, Streck T, Trombi G, Wallor E, Wang J, Weber TKD, Weihermüller L, de Wit A, Wöhling T, Xiao L, Zhao C, Zhu Y, Seidel SJ (2021) The chaos in calibrating crop models: Lessons learned from a multi-model calibration exercise. Environmental Modelling & Software. https://doi.org/10.1016/j.envsoft.2021.105206   
  10. Asseng S, Martre P, Maiorano A, Rötter RP, O’Leary GJ, Fitzgerald GJ, Girousse C, Motzo R, Giunta F, Babar MA, Reynolds MP, Kheir AMS, Thorburn PJ, Waha K, Ruane AC, Aggarwal PK, Ahmed M, Balkovič J, Basso B, Biernath C, Bindi M, Cammarano D, Challinor AJ, De Sanctis G, Dumont B, Eyshi Rezaei E, Fereres E, Ferrise R, Garcia-Vila M, Gayler S, GaYo, Horan H, Hoogenboom G, Izaurralde RC, Jabloun  M, Jones CD, Kassie BT, Kersebaum KC, Klein C, Koehler AK, Liu B, Minoli S, Montesino San Martin M, Müller C, Naresh Kumar S, Nendel C, J  OlesenJE, Palosuo T, Porter JR, Priesack E, Ripoche D, Semenov MA, Stöckle C, Stratonovitch P, Streck T, Supit I, Tao F, Van der Velde M, Wallach D, Wang E, Webber H, Wolf J, Xiao L, Zhang Z, Zhao Z, Zhu Y, Ewert F (2019) Climate change impact and adaptation for wheat protein. Global Change Biology. https://doi.org/10.1111/gcb.14481   
  11. Liu B, Martre P, Ewert F, Porter JR, Challino AJr, Müller C, Ruane AC, Waha K, Thorburn PJ, Aggarwal PK, Ahmed M, Balkovič J, Basso B, Biernath C, Bindi B, Cammarano D, De Sanctis G, Dumont B, Espadafor M, Eyshi Rezaei E, Ferrise R, Garcia-Vila M, Gayler S, Gao Y, Horan H, Hoogenboom G, Izaurralde RC, Jones CD, Kassie BT, Kersebaum KC, Klein C, Koehler AK, Maiorano A, Minoli S, Montesino San Martin M, Naresh Kumar S, Nendel C, O’Leary GJ, Palosuo T, Priesack E, Ripoche D, Rötter RP, Semenov MA, Stöckle C, Streck T, Supit I, Tao F, Van der Velde M, Wallach D, Wang E, Webber H, Wolf J, Xiao L, Zhang Z, Zhao Z, Zhu Y, Senthold Asseng (2018) Global wheat production with 1.5 and 2.0°C above  pre‐industrial warming. Global Change Biology. https://doi.org/10.1111/gcb.14542   
  12. Wallach D, Martre P, Liu B, Asseng S, Ewert F, Thorburn PJ, van Ittersum M, Aggarwal PK, Ahmed M, Basso B, Biernath C, Cammarano D, Challinor AJ, De Sanctis G, Dumont B, Eh Rezaei EE, Fereres E, Fitzgerald GJ, Gao Y, Garcia-Vila M, Gayler S, Girousse C, Hoogenboom G, Horan H, Izaurralde RC, Jones CD, Kassie BT, Kersebaum KC, Klein C, Koehler AK, Maiorano A, Minol Si, Müller C, Naresh Kumar S, Nendel C, O’Leary GJ, PalosuTo, Priesack E, Ripoche D, Rötter RP, Semenov MA, Stöckle C, Stratonovitch P, Streck T, Supit I, Tao F, Wolf J, Zhang Z  (2018) Multimodel ensembles improve predictions of crop–environment–management interactions. Global Change Biology. https://doi.org/10.1111/gcb.14411
  13. Webber H, White JW, Kimball BA, Ewert F, Asseng S, Rezaei EE, Pinter Jr. PJ, Hatfield JL, Reynolds MP, Ababaei B, Bindi M, Doltra J, Ferrise R, Kage H, Kassie BT, Kersebaum KC, Luig A, Olesen JE, Semenov MA, Stratonovitch P, Ratjen AM, LaMorte RL, Leavitt SW,. Hunsaker DJ, Wall GW, Martre P (2018) Physical robustness of canopy temperature models for crop heat stress simulation across environments and production conditions. Field Crops Research. https://doi.org/10.1016/j.fcr.2017.11.005
  14. Zhao C, Liu B, Piao S, Xuhui Wang, Lobell DB, Huang Y, Huang M, Yao Y, Bassu S, Ciais P, Durand JL, Elliott J, Ewert F, Janssens IA, Li T, Lin E, Liu Q, Martre P, Müller C, Peng S, Peñuelas J, Ruane AC, Wallach D, Wang T, Wu D, Liu Z, Zhu Y, Zhu Z, Asseng S (2017) Temperature increase reduces global yields of major crops in four independent estimates. PNAS. https://doi.org/10.1073/pnas.1701762114
  15. Maiorano A, Martre P, Asseng S, Ewert F, Müller C, Rötter RP, Ruane AC, Semenov MA, Wallach D, Wang E, Alderman PD, Kassie BT, Biernath C, Basso B, Cammarano D, Challinor AJ, Doltra J, Dumont B, Rezaei EE, Gayler S, Kersebaum KC, Kimball BA, Koehler AK, Liu B, O’Leary GJ, Olesen JE, Ottman MJ, Priesack E, Reynolds M, Stratonovitch P, Streck T, Thorburn PJ, Waha K, Wall GW, White r, Zhigan Zhao JW, Zhu Y (2017) Crop model improvement reduces the uncertainty of the response to temperature of multi-model ensembles. Field Crops Research. https://doi.org/10.1016/j.fcr.2016.05.001   
  16. Webber H, Martre P, Asseng S, Kimball B, White J, OttmanM, Wall GW, De Sanctis G, Doltra J, Grant R, Kassie B, Maiorano A, Olesen JE, Ripoche D, Rezaei EE, Semenov MA, Stratonovitch P, Ewert F (2017) Canopy temperature for simulation of heat stress in irrigated wheat in a semi-arid environment: A multi-model comparison. Field Crops Research. https://doi.org/10.1016/j.fcr.2015.10.009
  17. Wang E, Martre P, Zhao Z, Ewert F, Maiorano A, Rötter RP, Kimball BA, Ottman MJ, Wall GW, White JW, Reynolds MP, Alderman PD, Aggarwal PK, Anothai J, Basso B, Biernath C, Cammarano D, Challinor AJ, De Sanctis G, Doltra J, Dumont B, Fereres E, Garcia-Vila M, Gayler S, Hoogenboom G, Hunt LA, Izaurralde RC, Jabloun M, Jones CD, Kersebaum KC, Koehler AK, Liu L, Müller C, Naresh Kumar S, Nendel C, O’Leary G, E. Olesen J, Palosuo T, Priesack E, Rezaei EE, Ripoche D, Ruane AC, MSemenov MA, Shcherbak I, Stöckle C, Stratonovitch P, Streck T, Supit I, Tao F, Peter Thorburn, Waha K, Wallach D, Wang Z, Wolf J, Zhu Y, Asseng S (2017) The uncertainty of crop yield projections is reduced by improved temperature response functions. Nature Plants. https://doi.org/10.1038/nplants.2017.102
  18. Liu B, Asseng S, Müller C, Ewert F, Elliott J, Lobell DB, Martre P, Ruane AC, Wallach D, Jones JW, Rosenzweig C, Aggarwal PK, Alderman PD, Anothai J, Basso B, Biernath C, Cammarano D, Challinor A, Deryng D, De Sanctis G, Doltra J, Fereres E, Folberth C, Garcia-Vila M, Gayler S, Hoogenboom G, Hunt LA, Izaurralde RC, Jabloun M, Jones CD, Kersebaum KC, Kimball BA, Koehler AK, Naresh Kumar S, Nendel C, O’Leary GJ, Olesen JE, Ottman MJ, Palosuo T, Vara Prasad PV, Priesack E, Pugh TAM, Reynolds M, Rezaei EE, Rötter RP, Schmid E, Semenov MA, Shcherbak I, Stehfest E, Stöckle CO, Stratonovitch P, Streck T, Supit I, Tao F, Thorburn P, Waha K, Wall GW, Wang E, White JW, Wolf J, Zhao Z, Zhu Y (2016) Similar estimates of temperature impacts on global wheat yield by three independent methods. Nature Climate Change. https://doi.org/10.1038/nclimate3115
  19. Ruane AC, Hudson NI, Asseng S, Cammarano D, Ewert F, Martre P, Boote KJ, Thorburn PJ, Aggarwal PK, Angulo C, Basso B, Bertuzzi P, Biernath C, Brisson N, Challinor AJ, Doltra J, Gayler S, Goldberg R, Grant RF, Heng L, Hooker J, Hunt LA, Ingwersen J, Izaurralde RC, Kersebaum KC, Naresh Kumar S, Müller C, Nendel C, O’Leary G, Olesen JE, Osborne TM, Palosuo T, Priesack E, Ripoche D, Rötter RP, Semenov MA, Shcherbak I, Steduto P, Stöckle CO, Stratonovitch P, Streck T, Supit I, Tao F, Travasso M, Waha K, Wallach D, White JW, Wolf J (2016) Multi-wheat-model ensemble responses to interannual climate variability. Environmental Modelling & Software. https://doi.org/10.1016/j.envsoft.2016.03.008
  20. Cammarano D, Rötter RP, Asseng S, Ewert F, Wallach D, Martre P, Hatfield JL, Jones JW, Rosenzweig C, Ruane AC, Boote KJ, Thorburn PJ, KersebaumKC, Aggarwal PK, Angulo C, BassoB, Bertuzzi P, Biernath C, Brisson N, Challinor AJ, Doltra J, Gayler S, Goldberg R, Heng L, Hooker JE, Hunt LA, Ingwersen J, Izaurralde RC, Müller C, Naresh Kumar S, Nende C, O’Leary G, Olesen JE, Osborne TM, Palosuo T, Priesack E, Ripochel D, Semenov MA, Shcherbak I, Steduto P, Stöckle CO, Stratonovitch P, Streck T, Supit I, Tao F, Travasso M, Waha K, White JW, Wolf J (2016) Uncertainty of wheat water use: simulated patterns and sensitivity to temperature and CO2. Field Crops Research. https://doi.org/10.1016/j.fcr.2016.08.015
  21. Makowski D, Asseng S, Ewert FA, Bassu S, Durand JL, Li T, Martre P, Adam M, Aggarwal PK, Angulo C, Baron C, Basso B, Bertuzzi P, Biernath C, Boogaard HL, Boote KJ, Bouman BAM, Bregaglio SUM, Brisson N, Buis S, Cammarano D, Challinor AJ, Confalonieri R, Conijn JG, Corbeels M, Deryng D, De Sanctis G, Doltra J, Fumoto T, Gaydon DS, Gayler S, Goldberg RA, Grant RF, Grassini P, Hatfield JL, Hasegawa T, Heng LK, Hoek SB, Hooker JE, Hunt LA, Ingwersen J, Izaurralde RC, Jongschaap REE, Jones JW, Kemanian AR, Kersebaum KC, Kim SH, Lizaso JI, Marcaida M, Müller C, Nakagawa H, Naresh Kumar S, Nendel C, O’Leary GJ, Olesen JE, Oriol P, Osborne TM, Palosuo T, Pravia MV, Priesack E, Ripoche D, Rosenzweig CE, Ruane AC, Ruget F, Sau F, Semenov MA, Shcherbak I, Singh B, Singh U, Soo HK, Steduto P, Stockle CO, Stratonovitch P, Streck T, Supit I, Tang L, Tao F, Teixeira EI, Thorburn PJ, Timlin DJ, Travasso MI, Rötter RP, Waha K, Wallach D, White JW, Wilkens PW, Williams JR, Wolf J, Yin X, Yoshida H, Zhang Z, Zhu Y (2015) A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration. Agricultural and Forest Meteorology. https://doi.org/10.1016/j.agrformet .2015.09.013
  22. O’Leary G, Christy B, Nuttall J, Huth N, Cammarano D, Stöckle C, Basso B, Shcherbak I, Fitzgerald G, Lou Q, Farre-Codina I, Palta J, Asseng S (2015) Response of wheat growth, grain yield and water use to elevated CO2 under a Free Air CO2 Enrichment (FACE) experiment and modelling in a semi-arid environment. Global Change Biology. https://doi.org/10.1111/gcb.12830
  23. Asseng S, Ewert F, Martre P, Rötter RP, Lobell DB, Cammarano D, Kimball BA, Ottman MJ, Wall GW, White JW, Reynolds MP, Alderman PD, Prasad PVV, Aggarwal PK, Anothai J, Basso B, Biernath C, Challinor AJ, De Sanctis G, Doltra J, Fereres E, Garcia-Vila M, Gayler S, Hoogenboom G, Hunt LA, Izaurralde RC, Jabloun M, Jones CD, Kersebaum KC, Koehler A-K, Müller C, Naresh Kumar S, Nendel C, O’Leary G, Olesen JE, Palosuo T, Priesack E, Eyshi Rezaei E, Ruane AC, Semenov MA, Shcherbak I, Stöckle C, Stratonovitch P, Streck T, Supit I, Tao F, Thorburn PJ, Waha K, Wang E, Wallach D, Wolf J, Zhao Z, Zhu Y (2015) Rising temperatures reduce global wheat production. Nature Climate Change. https://doi.org/10.1038/nclimate2470
  24. Challinor A, Martre P, Asseng S, Thornton P, Ewert F (2014) Making the most of climate impacts ensembles. Nature Climate Change. https://doi.org/10.1038/nclimate2117
  25. Martre P, Wallach D, Asseng S, Ewert F, Jones JW, Rötter RP, Boote KJ, Ruane AC, Thorburn PJ, Cammarano D, Hatfield JL, Rosenzweig C, Aggarwal PK, Angulo C, Basso B, Bertuzzi P, Biernath C, Brisson N, Challinor AJ, Doltra J, Gayler S, Goldberg R, Grant RF, Heng L, Hooker J, Hunt LA, Ingwersen J, Izaurralde RC, Kersebaum KC, Müller C, Naresh Kumar S, Nendel C, O’leary G, Olesen JE, Osborne TM, Palosuo T, Priesack E, Ripoche D, Semenov MA, Shcherbak I, Steduto P, Stöckle CO, Stratonovitch P, Streck T, Supit I, Tao F, Travasso M, Waha K, White JW, Wolf J (2014) Multimodel ensembles of wheat growth: many models are better than one. Global Change Biology. https://doi.org/10.1111/gcb.12768  
  26. Asseng S, Ewert F, Rosenzweig C, Jones JW, Hatfield JL, Ruane AC, Boote KJ, Thorburn PJ, Rotter RP, Cammarano D, Brisson N, Basso B, Martre P, Aggarwal PK, Angulo C, Bertuzzi P, Biernath C, Challinor AJ, Doltra J, Gayler S, Goldberg R, Grant R, Heng L, Hooker J, Hunt LA, Ingwersen J, Izaurralde RC, Kersebaum KC, Mueller C, Naresh Kumar S, Nendel C, O’Leary G, Olesen JE, Osborne TM, Palosuo T, Priesack E, Ripoche D, Semenov MA, Shcherbak I, Steduto P, Stoeckle C, Stratonovitch P, Streck T, Supit I, Tao F, Travasso M, Waha K, Wallach D, White JW, Williams JR, Wolf J (2013) Uncertainty in simulating wheat yields under climate change. Nature Climate Change. https://www.nature.com/articles/nclimate1916

Data papers

  1. Martre P, Dueri S, Brown H, Asseng S, Ewert F, Webber H, George M, Craigie R, Guarin J, Pequeno D, Stella T, Ahmed M, Alderman P, Basso B, Berger A, Bracho Mujica G, Cammarano D, Chen Y, Dumont B, Rezaei E, Fereres E, Ferrise R, Gaiser T, Gao Y, Garcia-Vila M, Gayler S, Hochman Z, Hoogenboom G, Kersebaum K, Nendel C, Olesen J, Padovan G, Palosuo T, Priesack E, Pullens J, Rodríguez A, Rötter R, Ruiz Ramos M, Semenov M, Senapati N, Siebert S, Srivastava A, Stöckle C, Supit I, Tao F, Thorburn P, Wang E, Weber T, Xiao L, Zhao C, Zhao J, Zhao Z, Zhu Y (2024) Winter Wheat Experiments to Optimize Sowing Dates and Densities in a High-Yielding Environment in New Zealand: Field Experiments and AgMIP-Wheat Multi-Model Simulations. Open Data Journal for Agricultural Research. https://doi.org/10.18174/odjar.v10i0.18442
  2. Martre P, Ewert F, Webber H, Waha K, Thorburn PJ, Ruane AC, PrAggarwal PC, Ahmed M, Balkovič J, Basso B, Biernath C, Bindi M, Cammarano D, Cao W, Challinor AJ, De Sanctis G, Dumont B, Espadafor M, Rezaei EE, Fereres E, Ferrise R, Garcia-Vila M, Gayler S, Gao Y, Horan H, Hoogenboom G, Izaurralde RC, Jabloun M, Jones CD, Kassie BT, Kersebaum KC, Klein C, Koehler AK, Maiorano A, Minoli S, Montesino San Martin M, Müller C, Naresh Kumar S, Nendel C, O’Leary GJ, Olesen JE, Palosuo T, Porter JR, Priesack E, Ripoche D, Rötter RP, Semenov MA, Stöckle C, Stratonovitch P, Streck T, Supit I, Tao F, Van der Velde M, Wang E, Wolf J, Xiao L, Zhang Z, Zhao Z, Zhu Y, Asseng S (2023) AgMIP-Wheat multi-model simulations on climate change impact and adaptation for global wheat. Open Data Journal for Agricultural Research. https://doi.org/10.18174/odjar.v9i0.18092
  3. Guarin JR, Martre P, Ewert F, Webber H, Dueri S, Calderini D, Reynolds M, Molero G, Miralles D, Garcia G, Slafer G, Giunta F, Pequeno DNL, Stella T, Ahmed M, Alderman PD, Basso B, Berger AG, Bindi M, Bracho-Mujica G, Cammarano D, Chen Y, Dumont B, Rezaei EE, Fereres E, Ferrise R, Gaiser T, Gao Y, Garcia-Vila M, Gayler S, Hochman Z, HoogenboomG, Hunt LA, Kersebaum KC, Nendel C, Olesen JE, Palosuo T, Priesack E, Pullens JWM, Rodríguez A, Rötter RP, Ruiz Ramos M, Semenov MA, Senapati N, Siebert S, Srivastava AK, Stöckle C, Supit I, Tao F, Thorburn P, Wang E, T Weber TKD, Xiao L, Zhang Z, Zhao C, Zhao J, Zhao Z, Zhu Y, Asseng S (2022) Data from the AgMIP-Wheat high-yielding traits experiment for modeling potential production of wheat: field experiments and multi-model simulations. Harvard Dataverse. https://doi.org/10.7910/DVN/VKWKUP
  4. Asseng A, Ewert FA, Martre P, Rosenzweig C, Jones JW, Hatfield JL, Ruane A, Boote K, Thorburn P, Rötter R, Cammarano D, Basso B, Aggarwal, Angulo C, Bertuzzi P, Biernath C, Challinor A, Doltra J, Gayler S, Goldberg R, Grant R, Heng L, Hooker J, Hunt T, Ingwersen J, Izaurralde C, Kersebaum C, Müller C, Naresh Kumar S, Nendel C, O’Leary G, Olesen J, Osborne T, Palosuo T, Priesack E, Ripoche D, Semenov M, Shcherbak I, Steduto P, Stöckle C, Stratonovitch P, Streck T, Supit I, Tao F, Travasso M, Waha K, Wallach D, White J, Williams J, Wolf J (2015) Benchmark data set for wheat growth models: field experiments and AgMIP multi-model simulations. Open Data Journal for Agricultural Research. https://doi.org/10.18174/odjar.v1i1.14746

Member organizations of AgMIP-Wheat