De Li Liu1, Felicity Harris1, Bin Wang1, Eric Koetz1, Peter Martin2, Aaron Preston1, Graeme Sandral1, Michael Cashsen1, Tim Sides1
1 NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW 2650, Australia
2 Howqua Consulting, 48 Fulham Road, Alphington, Victoria, Australia
Extreme temperature damage to Australian grain crops remains the major production constraint with estimated losses of $1,100M per year. Thus, it is crucial to reduce such losses to improve food security for Australian and international consumers. NSW DPI developed a computer based decision support called SOWMAN to help farmers select the most appropriate varieties at sowing for minimum risk of frost and heat damage. SOWMAN is based on a phenology model that integrates varietal response to vernalisation, temperature and photoperiod and their interactions. The phenological parameters of up to 163 varieties were fitted using multiple regression analysis, based on over 13,000 sowing-flowering observations. The parameterised variety models are established as site-specific models (SSMs) and generic models (GMs). GMs can be used when site specific field observations for a variety are unavailable. SOWMAN is currently applicable to southern NSW and can be applied to other regions when observed sowing-flowering data are available for model validation.