Nutrient-use efficiency is a key issue for grazing systems in Australia. Spatial variability in soil pH and nutrients at the sub-paddock scale may affect the efficiency of utilisation of, and provide an opportunity for, site-specific management (SSM) of fertiliser and soil ameliorants. However, there has been little research exploring the potential for SSM in grazing systems. This study examines the spatial variability of soil test pH, phosphorus (P), potassium (K) and sulfur(S) in two typical pasture fields (a native and an improved) on the Northern Tablelands of New South Wales and evaluates the potential for SSM based on a comparison with critical values. In both fields, the overall paddock mean from a grid survey containing >80 samples for pH, P, K and S (0-10 cm) exceeded the critical values, suggesting that the addition of fertiliser or lime was not required. However, considerable sub-paddock-scale variability was observed, with CV ranging from 35% to 66% for the key nutrients (P, K and S). The Sprengel-Liebig Law of the Minimum was applied to evaluate the proportion of each field constrained by one or more soil characteristics. Up to 55% of the improved paddock and 78% of the native pasture was potentially responsive to amendments. The results of this study suggest that SSM of fertilisers and ameliorants could provide substantial improvements in productivity and possibly reductions in fertiliser use. The development and application of appropriate systems and tools to effectively quantify this spatial variability remain a challenge, coupled with management strategies that optimise the placement of amendments and account for the variability in other production limiting factors.

Precision agriculture (PA) technologies and applications have largely been targeted at the cropping and horticultural industries. Little research has been undertaken exploring the potential for PA in grazing systems. This paper reports on the results of five studies examining PA technologies and techniques in grazing systems including: spatial variability in soil nutrients and fertiliser response across the grazing landscape; spatial landscape utilisation in relationship to individual animal productivity and health; spatial variability in pasture pests; and the development of a sensor network for monitoring spatial soil moisture, soil temperature and ambient temperature across a grazing landscape. The large variability exhibited in our trials suggests there is an enormous opportunity for precision agriculture in grazing systems. Sensing and responding to this variability will require careful application of modern PA technology and a substantial investment in research to better understand spatial variability in our grazing landscapes.