Abstract

Canola is a relatively new crop in the Mediterranean environment of Western Australia and growers need information on crop management to maximise profitability. However, local information from field experiments is limited to a few seasons and its interpretation is hampered by seasonal rainfall variability. Under these circumstances, a simulation model can be a useful tool. The APSIM-Canola model was tested using data from Western Australian field experiments. These experiments included different locations, cultivars, and sowing dates. Flowering date was predicted by the model with a root mean squared deviation (RMSD) of 4.7 days. The reduction in the period from sowing to flowering with delay in sowing date was accurately reproduced by the model. Observed yields ranged from 0.1 to 3.2 t/ha and simulated yields from 0.4 to 3.0 t/ha. Yields were predicted with a RMSD of 0.3–0.4 t/ha. The yield reduction with delayed sowing date in the high, medium, and low rainfall region (3.2, 6.1, and 8.6% per week, respectively) was accurately simulated by the model (1.1, 6.7, and 10.3% per week, respectively). It is concluded that the APSIM-Canola model, together with long-term weather data, can be reliably used to quantify yield expectation for different cultivars, sowing dates, and locations in the grainbelt of Western Australia.

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