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The timing of flowering in canola (Brassica napus) is an important determinant of adaptation to its environment. Cultivars of canola varying in maturity are grown over a wide range of photoperiod and temperature conditions in Australia. A quantitative understanding of the genotypic and environmental control of time to flowering can be used to improve breeding programs and crop management strategies. Controlled environment and field studies were used to determine the responses of 21 cultivars of canola and breeding lines of Indian mustard to vernalisation, temperature, and photoperiod. The number of days to flowering in all genotypes was reduced in response to vernalisation and long days, due to a reduced duration between sowing and buds visible. The vernalisation response was saturated with c. 25 days at 3°C. Base and optimum temperatures for development were confirmed at 0 and 20°C, respectively. The photoperiod response occurred between 10.8 and 16.3 h, and plants responded to photoperiod from emergence. A simulation model incorporating these effects was developed, which predicted days to flowering with a mean deviation of c. 5 days. Later flowering genotypes had model parameters that indicated greater responses to vernalisation and photoperiod than early-flowering genotypes.

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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