Enhancing nitrogen use efficiency for Victoria and the world: a combined knowledge and innovation systems perspective

Priit Kaal1, Richard Vines2

1 DEDJTR, 1 Spring Street, Melbourne, Vic, 3000, priit.kaal@ecodev.vic.gov.au

2 DEDJTR, 1 Spring Street, Melbourne, Vic, 3000, richard.vines@ecodev.vic.gov.au


Since September 2012, knowledge management specialist staff within Agriculture Victoria, (Department of Economic Development, Jobs Transport and Resources and its predecessor institutions) have been developing a number of different digital applications to foster more effective online collaborations across the public, research, private service provider, community and education sectors. Adoption of these work practices and systems, including governance systems has the potential to improve the means by which those involved in the design, deployment and monitoring of research, development and extension programs and projects can reach and engage audiences, facilitate co-design of solutions with target audiences and improve access to information and expertise.

In this paper, we explore these possibilities and articulate the benefits for adopting these innovations in line with the overarching theme of this conference: that is through the aspiration of developing solutions to enhance nitrogen use efficiency for the world. The context will be the Victorian dairy sector and in particular a project called: Manure Technologies To Drive Resource Efficiencies.  This project is situated within a policy context that intensification of all agricultural industries including the Victorian dairy industry is desirable and inevitable. This global trend towards agricultural intensification is increasing place-based conflicts involved with securing a social license to underpin a ‘right to farm’. The Victorian Government State Government in Australia is grappling with the complexity of the trade-offs between these two policy objectives.

The central claim of the paper is this. Embedding principles of good practice knowledge management into the way programs and projects are designed and managed will do much to ameliorate the tensions inherent between the policy objectives of enabling agricultural intensification and securing a social license underpinning any ‘right to farm’. The complexity associated with the trade-offs between these dual objectives involve many technical challenges. To enhance nitrogen use efficiency in the dairy sector, solutions are required across many domains –for example in facilitating the re-use of nutrients, addressing soil nutrient accumulation, reducing gaseous emissions and odour and eliminating nutrient contamination of water and air, particularly those where there are larger herds and intensive operations involved.

It will be concluded that effective knowledge management needs to address two overarching challenges (Snowden 2003). The first is to create the conditions within which innovation can emerge via effective sense-making, collaboration and innovation systems thinking that apply in both face to face and online environments. Practical examples from other sectors will be discussed to highlight how technology can be harnessed to create the conditions within which representatives of “communities of practice” (CoPs) can co-learn and co-evolve with representatives of “communities of interest” (CoIs)  in order that solutions to problems involve principles of co-design. It will be emphasised that such approaches have significant potential in the realm of manure technologies and enhancing nitrogen use efficiency. The second is to enhance the quality of decision support systems. In the case of agriculture such support systems need to be flexible and extensible enough to apply at different levels in integrated ways (i.e. across farms, catchments, industry development, community based and public policy levels). The problem at the moment is that current decision support systems do not take into account the need to integrate and value the many different types of evidence to support decision making across these different levels.