Tools to manage climate risk in cropping (Australia).

Because of the variable and changing environment, advisors and farmers are seeking systems that provide risk management support at a number of time scales. The Agricultural Production Systems Research Unit, Toowoomba, Australia has developed a suite of tools to assist advisors and farmers to better manage risk in cropping. These tools range from simple rainfall analysis tools (Rainman, HowWet, HowOften) through crop simulation tools (WhopperCropper and YieldProphet) to the most complex, APSFarm, a whole-farm analysis tool. Most are derivatives of the APSIM crop model. These tools encompass a range of complexity and potential benefit to both the farming community and for government policy. This paper describes, the development and usage of two specific products; WhopperCropper and APSFarm. WhopperCropper facilitates simulation-aided discussion of growers' exposure to risk when comparing alternative crop input options. The user can readily generate 'what-if' scenarios that separate the major influences whilst holding other factors constant. Interactions of the major inputs can also be tested. A manager can examine the effects of input levels (and Southern Oscillation Index phase) to broadly determine input levels that match their attitude to risk. APSFarm has been used to demonstrate that management changes can have different effects in short and long time periods. It can be used to test local advisors and farmers' knowledge and experience of their desired rotation system. This study has shown that crop type has a larger influence than more conservative minimum soil water triggers in the long term. However, in short term dry periods, minimum soil water triggers and maximum area of the various crops can give significant financial gains.

New developments in UAV remote sensing for pest management and the implications for cotton

Efficient crop monitoring and pest damage assessments are key to protecting the Australian agricultural industry and ensuring its leading position internationally. An important element in pest detection is gathering reliable crop data frequently and integrating analysis tools for decision making. Unmanned aerial systems are emerging as a cost-effective solution to a number of precision agriculture challenges. An important advantage of this technology is it provides a non-invasive aerial sensor platform to accurately monitor broad acre crops. In this presentation, we will give an overview on how unmanned aerial systems and machine learning can be combined to address crop protection challenges. A recent 2015 study on insect damage in sorghum will illustrate the effectiveness of this methodology. A UAV platform equipped with a high-resolution camera was deployed to autonomously perform a flight pattern over the target area. We describe the image processing pipeline implemented to create a georeferenced orthoimage and visualize the spatial distribution of the damage. An image analysis tool has been developed to minimize human input requirements. The computer program is based on a machine learning algorithm that automatically creates a meaningful partition of the image into clusters. Results show the algorithm delivers decision boundaries that accurately classify the field into crop health levels. The methodology presented in this paper represents a venue for further research towards automated crop protection assessments in the cotton industry, with applications in detecting, quantifying and monitoring the presence of mealybugs, mites and aphid pests.

Transcriptome analysis of Neotyphodium and Epichloë grass endophytes

Large-scale gene discovery has been performed for the grass fungal endophytes Neotyphodium coenophialum, Neotyphodium lolii, and Epichloë festucae. The resulting sequences have been annotated by comparison with public DNA and protein sequence databases and using intermediate gene ontology annotation tools. Endophyte sequences have also been analysed for the presence of simple sequence repeat and single nucleotide polymorphism molecular genetic markers. Sequences and annotation are maintained within a MySQL database that may be queried using a custom web interface. Two cDNA-based microarrays have been generated from this genome resource. They permit the interrogation of 3806 Neotyphodium genes (NchipTM microarray), and 4195 Neotyphodium and 920 Epichloë genes (EndoChipTM microarray), respectively. These microarrays provide tools for high-throughput transcriptome analysis, including genome-specific gene expression studies, profiling of novel endophyte genes, and investigation of the host grass–symbiont interaction. Comparative transcriptome analysis in Neotyphodium and Epichloë was performed

Tree growth relationships and silvicultural tools to assist stand management in private native spotted gum dominant forests in Queensland and northern New South Wales.

Spotted gum dominant forests occur from Cooktown in northern Queensland (Qld) to Orbost in Victoria (Boland et al. 2006) and these forests are commercially very important with spotted gum the most commonly harvested hardwood timber in Qld and one of the most important in New South Wales (NSW). Spotted gum has a wide range of end uses from solid wood products through to power transmission poles and generally has excellent sawing and timber qualities (Hopewell 2004). The private native forest resource in southern Qld and northern NSW is a critical component of the hardwood timber industry (Anon 2005, Timber Qld 2006) and currently half or more of the native forest timber resource harvested in northern NSW and Qld is sourced from private land. However, in many cases productivity on private lands is well below what could be achieved with appropriate silvicultural management. This project provides silvicultural management tools to assist extension staff, land owners and managers in the south east Qld and north eastern NSW regions. The intent was that this would lead to improvement of the productivity of the private estate through implementation of appropriate management. The other intention of this project was to implement a number of silvicultural experiments and demonstration sites to provide data on growth rates of managed and unmanaged forests so that landholders can make informed decisions on the future management of their forests. To assist forest managers and improve the ability to predict forest productivity in the private resource, the project has developed: • A set of spotted gum specific silvicultural guidelines for timber production on private land that cover both silvicultural treatment and harvesting. The guidelines were developed for extension officers and property owners. • A simple decision support tool, referred to as the spotted gum productivity assessment tool (SPAT), that allows an estimation of: 1. Tree growth productivity on specific sites. Estimation is based on the analysis of site and growth data collected from a large number of yield and experimental plots on Crown land across a wide range of spotted gum forest types. Growth algorithms were developed using tree growth and site data and the algorithms were used to formulate basic economic predictors. 2. Pasture development under a range of tree stockings and the expected livestock carrying capacity at nominated tree stockings for a particular area. 3. Above-ground tree biomass and carbon stored in trees. •A series of experiments in spotted gum forests on private lands across the study area to quantify growth and to provide measures of the effect of silvicultural thinning and different agro-forestry regimes. The adoption and use of these tools by farm forestry extension officers and private land holders in both field operations and in training exercises will, over time, improve the commercial management of spotted gum forests for both timber and grazing. Future measurement of the experimental sites at ages five, 10 and 15 years will provide longer term data on the effects of various stocking rates and thinning regimes and facilitate modification and improvement of these silvicultural prescriptions.

Scoping genetic tools, their limitations and applications for wild fisheries management

FRDC has commissioned a review of the role that existing and future genetic technologies may play in addressing critical challenges facing the exploitation of wild fisheries. Wild fisheries management has been assisted by genetic research for over 50 years and in Australia, this research has been largely funded by FRDC. Both fisheries management and the methods of genetic analysis have changed significantly during this time. Given these dynamics, as well as perceptions that communication between fisheries managers and geneticists has been poor in some cases, there is a strong need to reassess the ways in which genetic research can contribute to fisheries and for all stakeholders to critically examine each other's needs and capabilities.

Veneer Recovery Analysis of Plantation Eucalypt Species Using Spindleless Lathe Technology

The Australian hardwood plantation industry is challenged to identify profitable markets for the sale of its wood fibre. The majority of the hardwood plantations already established in Australia have been managed for the production of pulpwood; however, interest exists to identify more profitable and value-added markets. As a consequence of a predominately pulpwood-focused management regime, this plantation resource contains a range of qualities and performance. Identifying alternative processing strategies and products that suit young plantation-grown hardwoods have proved challenging, with low product recoveries and/or unmarketable products as the outcome of many studies. Simple spindleless lathe technology was used to process 918 billets from six commercially important Australian hardwood species. The study has demonstrated that the production of rotary peeled veneer is an effective method for converting plantation hardwood trees. Recovery rates significantly higher than those reported for more traditional processing techniques (e.g., sawmilling) were achieved. Veneer visually graded to industry standards exhibited favourable recoveries suitable for the manufacture of structural products.

Rapid continuous chemical analysis of meat chicken shed emissions by SIFT–MS

Assessing and addressing odour impacts from poultry production is extremely difficult and subjective because the odorants involved and their dynamics over time and space are poorly understood. This knowledge gap is due, in part, to the lack of suitable analytical tools for measuring and monitoring odorants in the field. The emergence of Selected Ion Flow Tube – Mass Spectrometry (SIFT–MS) and similar instruments is changing that. These tools can rapidly quantify targeted odorants in ambient air in real time, even at very low concentrations. Such data is essential for developing better odour abatement strategies, assessment methods and odour dispersion models. This project trialled a SIFT–MS to determine its suitability for assessing the odorants in meat chicken shed emissions over time and space. This report details evaluations in New Zealand and Australia to determine the potential of SIFT–MS as a tool for the chicken meat industry, including odour measurement (as a proxy for dynamic olfactometry). The report is specifically targeted at those funding and conducting poultry odour research. It will be of interest to those involved with environmental odour monitoring and assessment in general. The high upfront cost of SIFT–MS will lead to potential users wanting compelling evidence that SIFT–MS will meet their needs before they invest in one.