APPLYING SIMULATION TO IMPROVE RICE VARIETIES IN REDUCING THE ON-FARM YIELD GAP IN CAMBODIAN LOWLAND RICE ECOSYSTEMS

Achieving export growth in rice production from variable rainfed lowland rice ecosystems is at risk if depending on conventional breeding or genetic development alone. Sustained, long-term production requires building adaption capacity of smallholder farmers to better manage the challenges of seasonal climate variability and future climate change. Better understanding of the risks and constraints that farmers face in managing their current cropping system helps develop strategies for improving rice production in Cambodia. System models are now considered valuable assessment tools for evaluating cropping systems performance worldwide but require validation at the local level. This paper presents an evaluation of the APSIM-Oryza model for 15 Cambodian rice varieties under recommended practice. Data from a field experiment in 2011, conducted in a non-limiting water and nutrient environment, are used to calibrate varietal-specific coefficients and model input parameters. An independent dataset is then used to validate the model performance for a real-world' situation using on-farm data for six rice varieties planted in 54 farmer fields on 32 farms in two villages of Southeastern Cambodia. From this analysis, the APSIM-Oryza model is shown to be an acceptable tool for exploring the mismatch between current on-farm yields and potential production through yield gap analysis and the exploration of cropping system options for smallholder farmers to increase production, adapt to seasonal climate variability and be prepared for potential climate changes.