Browsing by Author "Bramley, R"

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A collaborative approach to Precision Agriculture RDE for the Australian Sugar Industry : Final report CSE022
(Sugar Research Australia Limited, 2014) Bramley, R; Schroeder, B; Baillie, C
Strong sugar industry interest in Precision Agriculture (PA) has developed during the 2000s on the back of considerable progress with PA in other Australian agricultural sectors (grains and wine in particular), attempts in the Herbert (HCPSL and partners), and more recently in other districts, to develop a regional harvest management and yield mapping capability, and increased support for initiatives deemed of value in minimising possible impacts of sugarcane production on the Great Barrier Reef, including the provision of grants to growers for the purchase of GPS guidance systems and variable rate controllers for fertilizer spreaders. Against this background, the then Sugar Research and Development Corporation commissioned the reviews contained in SRDC Technical report 3/2007. A subsequent workshop held to mark the delivery of these reviews identified a number of PA-related R+D priorities which collectively could be characterised as being aimed at properly positioning the sugar industry for appropriate PA adoption, supported by access to the necessary technology, skills, methodological protocols and case studies. This project emerged from that process. Its intended focus, was to be based around core field sites in the Bundaberg, Burdekin and Herbert districts which were established with the intent of both PA research and demonstration.
Precision agriculture; an avenue for profitable innovation in the Australian sugar industry, or expensive technology we can do without? : SRDC Final report CSE018
(2007) Bramley, R; Webster, T; Thorburn, P
Precision Agriculture (PA) is an all-encompassing term given to a suite of technologies which promote improved management of agricultural production through recognition that the potential productivity of agricultural land can vary considerably, even over very short distances (a few m). The key technologies involved are yield monitors, remote and proximal sensing, the global positioning system (GPS) and geographical information systems. This project was conducted in response to the recognition by the Sugar Research and Development Corporation (SRDC) that the Australian sugar industry needs an informed basis from which to make decisions as to appropriate investment in PA. The project took the form of a review of published literature on PA and two industry workshops: the first conducted mid-project to provide the Industry Reference Group with an opportunity to review project progress and to make input to the recommendations emerging from it; the second conducted at the completion of the project to inform industry of the conclusions drawn and to promote industry input into SRDC’s priority setting with respect to future PA research. The review briefly discusses the philosophy underpinning PA, looks at PA research and application in a range of cropping systems, including sugarcane production, from around the world and considers the key drivers of short range spatial variability in these production systems. Constraints to the adoption of PA and its likely economic benefits are also considered in light of experiences from around the world. The opportunities that PA offers to the Australian sugar industry are identified, along with recommendations of further research, development and extension to facilitate its productive and profitable adoption. It is concluded that sugarcane production is ideally suited to the adoption of PA. However, a number of key tasks in Research, Development and Extension (RDE) are identified which will be required to enable its implementation in the Australian sugar industry.
Remote sensing-based precision agriculture tools for the sugar industry : SRDC Final report DPI021
(2013) Robson, A; Abbott, C; Bramley, R; Lamb, D
This project aimed to develop remote sensing applications that were both relevant and of commercial benefit to the Australian sugar industry and therefore adoptable. Such applications included the in season mapping of crop vigour so as to guide future management strategies, the identification of specific abiotic and biotic cropping constraints, and the conversion of GNDVI variability maps into yield at the block, farm and regional level. In order to achieve these applications the project team reviewed an array of remote sensing platforms, timing of imagery capture, software and analysis protocols; as well as distribution formats of derived imagery products, to a range of end users. The project developed strong collaborative linkages with all levels of the industry including mills, productivity services, agronomists, growers and researchers and increased its initial coverage from three individual farms in Bundaberg, Burdekin and the Herbert, coinciding with project CSE022, to include over 33,000 crops grown across 6 growing regions (Mulgrave, Herbert, Burdekin, Bundaberg, ISIS and Condong) during the 2011/2012 season.
Spatially explicit estimation of Achievable Yield Potential – An improved basis for fertilizer management: final report 2015/070
(Sugar Research Australia Limited, 2017) Bramley, R
Current practice in implementing the SIX EASY STEPS (6ES) is to use the ‘district yield potential’ (DYP) to guide development of nitrogen (N) fertilizer recommendations. However, because both land (soil, topography) and weather/climate may be strongly spatially variable at district scale, yield may also vary rendering use of DYP as sub-optimal. This project explored finer-scale alternatives to DYP as input to 6ES using spatial analysis of mill data and also data collected using yield monitors. The project was focussed in the Herbert River district. Analysis of mill records over 7 seasons shows that there is a marked spatial variability in yield in the Herbert River district, with the patterns of this variation stable across seasons and crop class. Accordingly, we conclude that DYP is not appropriate as an input to 6ES. Rather, a block yield potential derived from a map of the maximum yield of first ratoon achieved over these 7 seasons is suggested as a better alternative; this map, which is derived from interpolated maps of first ratoon yield for each year for which data are available, can be readily updated as more data become available. Growers with access to yield mapping could readily adopt a similar means of estimating yield potential at the within-farm or within-field scale. However, it is unlikely that sufficient data are yet available to support this given that data from several seasons are needed for yield zone delineation. Whether at the within-region or within-farm or field scales, further location-specific refinement of the application of 6ES is possible with access to data on soil carbon (C) content, whether derived from regional soil survey or local soil testing. Similar analyses to those reported here could be readily conducted in other sugarcane growing regions. Likewise, examination of spatial variation in the other factors underpinning 6ES may also be valuable as the industry seeks to optimise its N use efficiency.