description
- To improve margins for wheat production and reduce nitrogen losses to the environment, Salle Farms seeks ways to improve N use efficiency from the current level of 60%. Soils are highly heterogenous, which often causes yields on some areas to be water- not N-limited. Current methods of variable rate N application (VRNA) are based on estimates of spatial variation in the N status of the crop, but cannot predict the yield response to N. We aim to test a new method that utilises cropping system models to determine economically and environmentally optimum N management strategies, which account for crop-soil interactions within each spatially-defined management zone. **Objective 1 Delineate management zones (MZ) within target fields** Using geostatistical clustering techniques on existing spatial yield and soil electrical conductivity data sets, identify homogeneous MZs across on Salle Farms. A subset of 10-12 fields will be selected for model parameterisation and evaluation. **Objective 2 Collect soil data to parameterise crop model** Sample intact cores to 1 m depth at strategic positions within MZs to determine soil physical characteristics required for the pedotransfer functions for plant available soil water and other physical and chemical properties to parametrise cropping system models for each MZ (Obj 3). **Objective 3 Calculate spatially specific N rates for each MZ** An ensemble of wheat crop simulation models (e.g. DSSAT, APSIM, Sirius) will be parameterised using soil data for each MZ, and run using ~20 years of historic weather for the site. Crop response will be simulated for a range of N input levels to generate season-specific N response curves to derive the economically optimum N rates for each MZ. Models will be validated using Salle's on-farm data from previous N-response trials and in-season measurements. N application rates will also be calculated for each MZ using commercial canopy-based precision N tools, based on measures of canopy greenness using proximal sensing or satellite imagery (e.g. Yara). **Objective 4 Farm-scale tests of VRNA methods** Three methods of N fertilisation will be compared in defined blocks within each MZ, applied at rates calculated according to : 1) economically optimum N rates produced by model simulations; 2) N rates determined by commercial canopy-based precision N tools; 3) flat-rate N. Using combine yields, margins and fertiliser NUE for each method will be calculated and compared across MZ. Measurements across 20-30 management zones will provide sufficient replication for a comprehensive method assessment.