public read Assoc. Prof. Mike Bell Queensland Alliance for Agriculture and Food Innovation (QAAFI) Associate Professor

University of Queensland Saint Lucia Queensland 4072 Australia

+61 7 4160 0730 m.bell4@uq.edu.au Fertiliser application is the largest single variable expense for grain growers when producing a crop, with Nitrogen inputs by far the largest nutrient input in the northern grains region. Despite this, growers are consistently running negative N budgets from a nutrient balance perspective, largely in response to uncertain yield targets due to variable seasonal conditions and limited opportunity to manage N by in-season inputs in situations where rainfall is unpredictable. These negative N budgets further erode soil reserves and will result in higher fertilizer N demand in future, although growers are also being faced with increased need to supply other nutrients (P, K and S) in the fertilizer program. There is therefore a clear need to accurately predict N demands, and to maximise the efficient use of soil and fertilizer N reserves to produce grain, freeing up cash to meet other nutrient demands while also minimizing environmental impacts. Soil testing information is one of the key factors needed to identify nutrient limits to productivity and subsequently devise a fertilizer program. However, without calibrated soil test – yield relationships that are robust enough to quantify likely yield response to added fertilizer, farm managers and advisors are not able to make fertilizer decisions that will optimize productivity, nutrient use efficiency or profitability. This uncertainty can result in under-application and further erosion of nutrient reserves, as well as declining productivity and water use efficiency, or alternately over-application with reduced N use efficiency and profitability. The latter situation greatly increases the environmental risks of off-site impacts due to relative mobility of N, with nitrogen leaching and gaseous loss of nitrous oxide (a potent greenhouse gas) common loss pathways. The latter is of particular concern in clay soils that characterise the northern cropping region, due to the combination of poor internal drainage and extended fallowing to allow build-up of soil water and mineral N reserves prior to crop establishment. It is also unclear how desired increases in soil carbon in response to climate change will influence nitrogen fertiliser demands in these cropping systems, as well as the potential for nitrous oxide emissions. The interaction between soil carbon and nitrogen fertiliser requirements will be pivotal in any assessment of the effectiveness of soil carbon sequestration to abate greenhouse gas emissions from grain production. The national database "Making Better Fertiliser Decisions for Crops" has identified some significant gaps in soil test-crop response relationships for major crops in the northern region, with the only crop with a reasonable quantity of data defining fertilizer N response being wheat. The coverage for sorghum and canola are the next most prominent, but these relationships are currently of limited value due to inconsistencies with soil testing procedures and limitations with accompanying measurements like soil C (to explain variation in-season N mineralization). The purpose of this project is to address the gaps for summer sorghum, and expand the database for canola in the southern parts of the region. It will have trials spread from northeast and northwest NSW to southern and central Qld, with locations based on rotating clusters of trials through different soils and districts. These regional trials will complement work conducted at core sites in Qld, where detailed studies of soil N dynamics, environmental losses (gaseous and leaching) and crop N use efficiency will be conducted. N response curves Kingaroy N use efficiency Auto Chambers Urea Entec DMPP Nitrification Inhibitors QLD Sorghum 0502 0799 anzsrc-for Kingaroy, Bjelke Petersen Research Station, Kingaroy, Queensland 151.828671 151.980499671 -26.58183 -26.58183 2013 2014 Dr. David Rowlings Queensland University of Technology, Institute for Future Environments Research Fellow

2 George Street Brisbane Queensland 4001 Australia

+61 7 3138 9508 d.rowlings@qut.edu.au Dr. Clemens Scheer Queensland University of Technology, Institute for Future Environments Senior Lecturer Biogeosciences

2 George Street Brisbane Queensland 4001 Australia

+61 7 3138 7636 clemens.scheer@qut.edu.au

The soil–atmosphere exchange of N2O was measured with a mobile fully automated measuring system. Sampling chambers (50cm x 50cm x 15cm) were fixed on stainless steel frames. The lids of the chambers were opened and closed automatically with pneumatic devices. During the closing period air samples from each chamber were taken alternately and injected towards the analytical devices. Soil-atmosphere exchange measurements were made at 3 subplots for each treatment within the split-plot design. Changes in N2O concentration after chamber closure were measured with a gas chromatograph (Texas Instruments SRI 8610C, Torrance/USA) equipped with a 63Ni electron capture detector (ECD) for N2O analysis.

Gas chromatograph (Texas Instruments SRI 8610C, Torrance/USA) equipped with a 63Ni electron capture detector (ECD) for N2O analysis. 2013-2014 Greenhouse gases: 1. N2O: Automated Greenhouse Gas (GHG) Measurement System – 12 automated chambers 2. CH4: Automated Greenhouse Gas (GHG) Measurement System– 12 automated chambers 3. CO2: Automated Greenhouse Gas (GHG) Measurement System– 12 automated chambers Soil water content: 1. Volumetric water content: a. 3 x FDR (frequency domain reflectometry), @ 10, 20, 30, 50, 80 cm (EnviroSCAN Sentek, Stepney, SA, Australia) b. 4 x TDR(time domain reflectometry) @ 10 cm depth (MP406 Soil Moisture Sensor) 2. Gravimetric water content (fortnightly soil sampling) Mineral N in the soil (fortnightly soil sampling) Rain fall & irrigation amount Soil temperature: PT 100 sensors (IMKO Germany) 2013-2014_KY_Sorghum_N2O.csv 2013-2014_KY_Sorghum_N2O.csv 2198 1 #x0A column , ecogrid://knb/datalibrarian.270.1 Date Date DD-MM-YYYY 0 N2O emission - Urea 0 N [g ha-1] N2O emission - Urea 0 N [g ha-1] g N2O-N/ha/day real N2O emission - Urea 80 N [g ha-1] N2O emission - Urea 80 N [g ha-1] g N2O-N/ha/day real N2O emission - Urea 120 N [g ha-1] N2O emission - Urea 120 N [g ha-1] g N2O-N/ha/day real N2O emission - Entec 120 N [g ha-1] N2O emission - Entec 120 N [g ha-1] g N2O-N/ha/day real 48 2013-2014_MK_Sorghum_N2Ocum.csv 2013-2014_MK_Sorghum_N2Ocum.csv 1996 1 #x0A column , ecogrid://knb/datalibrarian.271.1 Date Date DD-MM-YYYY 0 cumulative N2O emissions - Urea 0 N [g ha-1] cumulative N2O emissions - Urea 0 N [g ha-1] g N2O-N/ha/day real cumulative N2O emissions - Urea 80 N [g ha-1] cumulative N2O emissions - Urea 80 N [g ha-1] g N2O-N/ha/day real cumulative N2O emissions - Urea 120 N [g ha-1] cumulative N2O emissions - Urea 120 N [g ha-1] g N2O-N/ha/day real cumulative N2O emissions - Entec 120 N [g ha-1] cumulative N2O emissions - Entec 120 N [g ha-1] g N2O-N/ha/day real 48 2013-2014_KY_Sorghum_environment.csv 2013-2014_KY_Sorghum_environment.csv 85974 1 #x0A column , ecogrid://knb/datalibrarian.272.1 Date_hour Date_hour DD-MM-YYYY 0 Soil_temp [¯C] Soil_temp [¯C] celsius real Rain - Irrigation [mm] Rain - Irrigation [mm] liter real Soil Moisture TDR 1 TDR 1 cubicCentimetersPerCubicCentimeters real Soil Moisture TDR 2 TDR 2 cubicCentimetersPerCubicCentimeters real Soil Moisture TDR 3 TDR 3 cubicCentimetersPerCubicCentimeters real Soil Moisture TDR 4 TDR 4 cubicCentimetersPerCubicCentimeters real FDR @ Level 1 10 cm FDR @ Level 1 10 cm cubicCentimetersPerCubicCentimeters real 1590 Summary_2014_15_Kingaroy_all .xlsx Summary_2014_15_Kingaroy_all.xlsx application/vnd.ms-excel ecogrid://knb/datalibrarian.273.1 Multiple Values Multiple Values Multiple Values Summary_2013_14_Kingaroy_all Summary_2013_14_Kingaroy_all.xlsx application/vnd.ms-excel ecogrid://knb/datalibrarian.275.1 Multiple Values Multiple Values Multiple Values g N2O-N/ha/day cubicCentimetersPerCubicCentimeters