Dr Rick Llewellyn1, Ms Jackie Ouzman1, Dr Masood Azeem1, Dr Therese McBeath1, Fiona Dempster2
1CSIRO, Adelaide, Australia, 2University of Western Australia, Perth, Australia
Biography:
Dr. Rick llewellyn is a CSIRO senior principal research scientist based in Adelaide. His research bridges farming systems research & economics. He has a bachelor of agricultural science from the university of Adelaide and a PhD in agricultural economics from UWA. His research has included weed and herbicide resistance management strategies and innovation adoption. He and CSIRO colleague Lindsay bell are now leading the new GRDC national risk management initiative; riskwi$e.
Abstract:
Increasing attention is being given to the role of data and quantitative information in agricultural decision-making. Together with technology that allows greater precision of agronomic treatments, the opportunity for data-driven agronomic approaches continues to grow. However, it hasn’t necessarily followed that demand for soil and plant/weed testing data has grown at the same rate. The potential for testing data to reduce uncertainty and lead to more cost-effective management decisions was evaluated using results from two studies involving field sampling, testing and grain grower data. One involved soil nutrient testing (on 100 SA and Victorian farms) and the other herbicide resistant weed testing (on 51 Western Australian farms). Paddock-specific sampling, elicitation of existing grower perceptions of paddock status, the perceived uncertainty associated with the test information, the intended management practice options in the absence of additional test information, and field results were used to identify the scope for the new information to profitably affect management practice. The results demonstrate that combinations of commonly sound prior assumptions or readily observed status (in the absence of testing), often high levels of residual uncertainty post-testing (including spatial uncertainty), and often under-estimated total sampling costs and logistical constraints on increasingly large farms should not be overlooked when considering the benefit:cost of testing from the decision-maker perspective. A framework for considering the value of information in different types of testing and tool scenarios is presented. Strong value propositions for testing information are identified, but the decision context and role for this information is rapidly changing.