Abstract
This is the second of a six paper series on farmer AgTech adoption in the WA grains industry that use open source information technology devices to solve for production problems that increase productivity. The first five papers are case studies outlining the business drivers of the adoption of differing types of AgTech adoption. A key proposition under investigation is that the particular circumstances of a farm implies that each farm will have a different path of open source information technology adoption that will give it the best risk adjusted rate of return. They consider the variables of farm scale (three are at or above minimum efficient scale – MES – for cropping), enterprise mix (three are mixed farm operations), rainfall zone and management structure/depth and group vs. single farmer adoption. The sixth paper is a summary document of key themes, – including the interaction of adoption with on and off farm connectivity and data integration – and public policy implications. It will discuss private and public structural and strategic options to deal with connectivity and complexity issues that are necessary for WA agriculture to access the productivity gains possible from adopting the full suite of available technologies. This case is similar to the first case in that: both are of a similar size (~10,000 ha); both farm on the edge of the low and medium rainfall zones; both are at least minimum efficient scale in grain production (or ‘one tractor size’ or ‘unitisation scale’; that is a minimum of 4,000 ha); both have sufficient financial resources to deal with the cost of initial investment; and both have management structures to permit the business development needed to deal with the inherent complexity associated with adopting a new technology. However, the Newmans’ farm is a discontinuous mixed operation of grains and sheep spread over several properties. The farm places its premium on monitoring data largely pertinent to livestock production because this generates the best rate of (risk adjusted) return for it. Typical of most WA broadacre farms, connectivity to the Newman’s farm is poor. Much of the farm does not have mobile coverage or frequently drops out and the NBN satellite service is slow, intermittent and expensive. Consequently, the Newmans have invested to create an internal farm connectivity backbone onto which open source technology devices are attached to solve production problems. They have also invested in farm to mobile tower connectivity; further investment to automatically connect to the existing satellite NBN connection in case of mobile tower failure is in progress. The rate of return from these investments is high, reflecting significant productivity gains. Modelling by Perret et al (2017) for the Cotton CRC indicates that very large productivity and Gross Value of Production gains can be made by the full adoption of decision/precision agriculture. A key issue running through these papers is how are farms able to begin the journey of adopting such technologies? CSRIO’s ADOPT framework is used to outline the observed patterns of farmer adoption of new technologies. The Newmans’ adopted AgTech technologies are easily trialed, easily reversed, comparatively low cost, and because of the farm’s management structures and financial resources, they are able to be absorbed into existing production without greatly increasing complexity. The pertinent question is whether the expense and complexity of establishing this type of system implies a significant barrier to entry for farmers without the required financial resources and management structures. This theme will be further explored in subsequent case studies.
Published Version
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