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Catalogue: GRDC Final Reports
ABSTRACT A preliminary, mouse abundance model was constructed using artificial neural networks and data on trap success rates spanning a ten-year period in neighbouring catchments in Central Queensland... To predict trap success (percentage of traps that catch mice) in June, the model uses trap success rates in December and February, as well as rainfall in January/February and March/April... The preliminary results shown suggest that artificial neural networks have potential to be used to predict the likelihood of high mouse abundance in winter in Central Queensland...
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Catalogue: GRDC Final Reports
The uptake of PA was limited by difficulties that individual farmers and industry were encountering in deciding which layers of spatial data to gather and how to integrate the information into farm management... Crop yield maps are the best method for quantifying crop yield variability across paddocks and farms and across seasons... The project has produced the first true site-specific gross margin maps in Australia by combining grain quantity, moisture, and protein measured on harvester and applying the appropriate delivery premium/discounts scales...
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