Whole-farm simulation models are useful tools for evaluating the effect of management practices and climate variability on the agro-environmental and economic performance of farms. A few process-based farm-scale models have been developed, but none has been evaluated in northern regions with boreal and hemiboreal climates characterized by a short growing season and a long period with snow cover. The study objectives were to calibrate the grass sub-model of the Integrated Farm System Model (IFSM) and evaluate its predictions of yield and nutritive value of timothy and alfalfa, grown alone or in a mixture, using experimental field data from across Canada, andto assess IFSM’s predictions of yield of major annual crops grown on dairy farms in eastern Canada using regional yield data from two contrasting regions. Several timothy and alfalfa datasets combining sites, years, harvests, and N fertilization rates were used to calibrate and evaluate the model. For timothy and alfalfa, the model’s accuracy was globally satisfactory in predicting dry matter yield and neutral detergent fiber concentration with a normalized root mean square error (NRMSE)<30%. For N uptake, the scatter was a bit larger, especially for timothy (NRMSE= 49%), mainly because of a small range in the measured data. The model’s accuracy for predicting the yield of annual crops was generally good, with an NRMSE<30%. Adding timothy and alfalfa to the grass sub-model of IFSM and verifying the model’s performance for annual crops confirmed that IFSM can be used in northern regions of North America. In addition, the model was able to simulate the yield and nutritive value of a timothy–alfalfa mixture, which is the most common perennial mixture used in Canada.
|Translated title of the contribution||Simulating forage crop production in a northern climate with the Integrated Farm System Model|
|Number of pages||13|
|Journal||Canadian Journal of Plant Science|
|State||Published - Jul 25 2015|
All Science Journal Classification (ASJC) codes
- Agronomy and Crop Science
- Plant Science