Our goal is to conduct research and research-oriented training to further the understanding of the functioning of major tropical plant production systems in a changing environment. Environmental changes comprise the big challenges agricultural systems are increasingly facing in the future in the different regions in the tropics and sub-tropics: water scarcity, soil nutrient depletion, soil loss, more severe adverse weather events, enhanced ozone concentrations and climate change. Last, but not least, in collaboration with other disciplines we conduct quantitative research on the various dimensions of food security at different scales.
Key publications:technological innovations
Hoffmann, M.P., et al. (2016). Assessing the Potential for Zone-Specific Management of Cereals in Low-Rainfall South-Eastern Australia: Combining On-Farm Results and Simulation Analysis Journal of Agronomy and Crop Science 203, 14–28. DOI:10.1111/jac.12159 Kassie, B.T., Van Ittersum, M.K., Hengsdijk, H., Asseng, S., Wolf, J. & Rötter, R.P. (2014). Climate-induced yield variability and yield gaps of maize (Zea mays L.) in the Central Rift Valley of Ethiopia Field Crops Research 160, 41-53. DOI:10.1016/j.fcr.2014.02.010
Asseng, S., et al. (2015). Rising temperatures reduce global wheat production Nature Climate Change 5, 143-147. DOI:10.1038/nclimate2470 Hoffmann, M.P., et al. (2018). Exploring adaptations of groundnut cropping to prevailing climate variability and extremes in Limpopo Province, South Africa Field Crops Research 219, 1-13. DOI: 10.1016/j.fcr.2018.01.019 Rötter, R.P., et al. (2018). Linking modelling and experimentation to better capture crop impacts of agroclimatic extremes - A review Field Crops Research 221, 142–156. DOI: 10.1016/j.fcr.2018.02.023 Kahiluoto, H., et al. (2014). Cultivating resilience by empirically revealing response diversity Global Environmental Change 25, 186-193. DOI:10.1016/j.gloenvcha.2014.02.002 Rötter, R.P., et al. (2015). Use of crop simulation modelling to aid ideotype design of future cereal cultivars Journal of Experimental Botany 66, 3463-3476. DOI:10.1093/jxb/erv098
de Wit, A., et al. (2015). WOFOST developer's response to article by Stella et al. Environmental Modelling & Software 59, 44-58. DOI:10.1016/j.envsoft.2015.07.005 Hoffmann, M.P., et al. (2014). Simulating potential growth and yield in oil palm with PALMSIM: Model description, evaluation and application Agricultural Systems 131, 1-10. DOI:10.1016/j.agsy.2014.07.006 Rötter, R.P., et al. (2011). Crop–climate models need an overhaul Nature Climate Change 1, 175-177. DOI:10.1038/nclimate1152 Rötter, R.P., et al. (2014). Robust uncertainty Nature Climate Change 4, 251-252. DOI:10.1038/nclimate2181 Wallach, D., et al. (2016). Estimating model prediction error: Should you treat predictions as fixed or random? Environmental Modelling & Software 84, 529-539. DOI:10.1016/j.envsoft.2016.07.010
Ewert, F., et al. (2015). Crop modelling for integrated assessment of risk to food production from climate change Environmental Modelling & Software 72, 287-303. DOI:10.1016/j.envsoft.2014.12.003 Liu, X., et al. (2016). Dynamic economic modelling of crop rotations with farm management practices under future pest pressure Agricultural Systems 144, 65-76. DOI:10.1016/j.agsy.2015.12.003
Read more about TROPAGS in our slideshow