Journalartikel

Autorenliste: Parker, P; Ingwersen, J; Hogy, P; Priesack, E; Aurbacher, J

Jahr der Veröffentlichung: 2016

Seiten: 207-222

Zeitschrift: The Journal of Agricultural Science

Bandnummer: 154

Heftnummer: 2

ISSN: 0021-8596

DOI Link: https://doi.org/10.1017/S0021859615000490

Verlag: Cambridge University Press

Abstract: 
Agriculture is a largely technical endeavour involving complicated managerial decision-making that affects crop performance. Farm-level modelling integrates crop models with agent behaviour to account for farmer decision-making and complete the representation of agricultural systems. To replicate an important part of agriculture in Central Europe a crop model was calibrated for a unique region's predominant crops: winter wheat, winter and spring barley, silage maize and winter rapeseed. Their cultivation was then simulated over multiple decades at daily resolution to test validity and stability, while adding the dimension of agent behaviour in relation to environmental and economic conditions. After validation against regional statistics, simulated future weather scenarios were used to forecast crop management and performance under anticipated global change. Farm management and crop genetics were treated as adaptive variables in the milieu of shifting climatic conditions to allow projections of agriculture in the study region into the coming decades.

Harvard-Zitierstil: Parker, P., Ingwersen, J., Hogy, P., Priesack, E. and Aurbacher, J. (2016) Simulating regional climate-adaptive field cropping with fuzzy logic management rules and genetic advance, The Journal of Agricultural Science, 154(2), pp. 207-222. https://doi.org/10.1017/S0021859615000490

APA-Zitierstil: Parker, P., Ingwersen, J., Hogy, P., Priesack, E., & Aurbacher, J. (2016). Simulating regional climate-adaptive field cropping with fuzzy logic management rules and genetic advance. The Journal of Agricultural Science. 154(2), 207-222. https://doi.org/10.1017/S0021859615000490