Browsing by Author "Skocaj, D"

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Australian sugarcane nutrition manual
(Sugar Research Australia Limited, 2018) Calcino, D; Schroeder, B; Panitz, J; Hurney, A; Skocaj, D; Wood, A; Salter, B
On-farm nutrient management has a key role in farm and industry sustainability, and in ensuring minimal off-site impacts occur.
Climate forecasting to improve nitrogen management in the Wet Tropics
(Sugar Research Australia Limited, 2016) Rodman, G; Skocaj, D
SRA researcher Danielle Skocaj's PhD thesis investigated the impact of climatic conditions on Tully sugarcane yields and nitrogen fertiliser requirements. She found that climate forecasting can be used to predict N fertiliser requirements for ratoon crops.
Climate forecasting to improve nitrogen management in the Wet Tropics
(Sugar Research Australia Limited, 2016) Rodman, G; Skocaj, D
SRA research Danielle Skocaj's PhD thesis investigated the impact of climatic conditions on Tully sugarcane yields and nitrogen fertiliser requirements. She found that climate forecasting can be used to predict N fertiliser requirements for ratoon crops.
Creating discussions, generating curiosity and promoting soil health
(Sugar Research Australia Limited, 2020) Skocaj, D
Creating discussions, generating curiosity and promoting soil health
Fertiliser calibrations have never been easier
(Sugar Research Australia Limited, 2018) Rodman, G; Skocaj, D
Calibrating your fertiliser applicator can be a chore. SRA has developed a new tool called CogCalibratorTM, which does some of the hard work for you.
Fertiliser calibrations have never been easier
(Sugar Research Australia Limited, 2018) Rodman, G; Skocaj, D
Fertiliser calibrations have never been easier
How much nitrogen will that crop need? Incorporating climate forecasting to improve nitrogen management in the Wet Tropics : Final project 2015/075
(Sugar Research Australia Limited, 2018) Everingham, Y; Biggs, J; Schroeder, B; Skocaj, D; Thorburn, P; Sexton, J
Determining the optimum amount of nitrogen that is required by the crop to maximise production, profitability and environmental outcomes is a challenging problem. The modelling approach taken in this project has balanced each of these complex elements to produce, and demonstrate, a novel and grower-friendly solution for the Tully canegrowing region. Optim-N Gets a Thumbs Up “How much nitrogen does my crop need?” depends on many interacting factors such as soil type, harvest management, position in the landscape and climate variability! This project took a unique and innovative approach to solving this problem and neatly embedded this process in a prototype tool called “Optim-N”. Instead of applying the same rate of nitrogen every year, Optim-N formulates nitrogen guidelines based on climate forecasts, for eight important soils in two climate zones in the Tully region, and three harvest dates. The processes behind Optim-N were tested against all available data, both from experiments and, where these were not available, expert opinion. When fully developed and operational, this tool will save farmers money by tailoring season- and site-specific recommendations for individual cane paddocks; improve water quality leaving farms and entering waterways to the Great Barrier Reef, and skill-up extension officers, allowing them to provide more targeted advice for farmers that factors in seasonal climate forecasts from the world’s best climate models. Two major activities are needed to take Optim-N from a prototype, to a widely used tool: Optim-N would need to be trialled with farmers in an action learning context so they could understand how it helps their decision making. This experience would also drive refinements of the Optim-N tool. It would also provide more empirical data for testing the science behind the tool, reducing the reliance on expert opinion and simultaneously increase trust and end-user confidence in the tool, which would accelerate adoption. The Optim-N prototype also needs input from professional software experts to take it to commercial levels of robustness and usability. When presented at a variety of forums, the Optim-N prototype receives a big “thumbs-up”.