Defining optimal sowing and flowering periods for canola in Australia

Abstract

Increasingly variable rainfall and temperatures and larger farm size in Australia have prompted earlier sowing of canola (Brassica napus L.). Improved agronomy and the release of cultivars suited to a wider range of environments have facilitated the expansion of canola production into new environments. To maximise grain yield at earlier sowing dates and in new environments, growers need to know the most suitable development pattern for their environment and sowing date to reduce production losses associated with frost, heat and drought at flowering. A simulation analysis was conducted at 77 locations across the Australian cropping zone to determine the optimal period for flowering to start in order to maximise long-term yield. The simulation accounted for effects of frost, heat and water stress on yield as well as duration of biomass accumulation. The optimal start of flowering period (OSF) was a function of the environment rather than the cultivar, and the relative importance of frost, heat and water stress varied with location. We found that the OSF was earlier (mid to late July), in most Mediterranean environments of Western Australia, South Australia and Victoria and later (August to September) in the southern temperate environments of Tasmania, Victoria and New South Wales (NSW). In medium and low rainfall areas of NSW, temperature extremes and rainfall interacted so that the OSF occurred in mid-July to mid-August. In low rainfall environments the duration of the optimal period was shorter (19–35 days) in most cases than in high rainfall environments (30–52 days). Knowledge of the OSF for a location, will allow breeders to develop cultivars with appropriate phenological characteristics for target environments. For growers, an understanding of the OSF, combined with an appropriate phenology classification of commercial cultivars, will allow selection of cultivar and sowing date combinations which decrease the risk of stress and maximise productivity.