Agronomic Packages for Improved Yield and Quality in the Australian Peanut Industry

Monitoring aflatoxin and developing improved peanut drying practices, cadmium management and web based irrigation decision support systems.

Spatially based data delivery and recording sys-Aust Sugar Cane industry

Establish an internet platform where spatially referenced data can be viewed, entered and stored.

Internet based spatial data delivery and reporting system for cotton industry

Development of an internet based spatial data delivery and reporting system for the Australian Cotton Industry.

Smart technologies for peanut industry

Commercialisation and adoption of remote sensing and GIS technologies for improved production forecasting, productivity, quality and paddock- to- plate tracking within the Australian Peanut Industry.

Enhancing supplies of high quality barley to meet pork industry demands

Producing barley varieties that have incrased grain yield and consistent or higher energy for pigs, as well as resistance to the major diseases of barley.

Cross-industry preparedness for Cotton leaf curl disease

Cotton leaf curl disease (CLCuD) is a major biosecurity threat to the Australian cotton industry. This proposal seeks cross-industry investment from the cotton (CRDC) and horticulture (HAL) industries to address the threat of exotic whitefly-transmitted viruses. Testing of silverleaf whitefly, the vector of CLCuD, could provide an alternative, cheaper strategy for early warning disease surveillance compared to surveys for disease symptoms. Control of whitefly-transmitted viruses in Australia and overseas will be reviewed to produce an integrated management package for their control in Australia. This will also involve a workshop with key stakeholders and selected overseas participants, to develop a working party to help formulate this package.

Benchmarking water management in the Australian cotton industry

Benchmarking irrigation performance has always been a challenge. As part of the Rural Water Use Efficiency (RWUE3) project the team in, collaboration with the Cotton Catchments Communities CRC, National Certificate of Educational Achievement and the Knowledge Management Phase 2 project, aimed to standardise the irrigation indices in use within the cotton industry. This was achieved through: - the delivery of training workshops - access to benchmarking tools - promotion of benchmarking as a best practice to be adopted on farm.

Job-related diversity and team performance: An empirical analysis of the US music industry

A significant amount of research has been carried out to investigate the existing bonds between team characteristics and team outcomes in contexts of social creativity. Specifically, how work group diversity affects its performance is of great relevance but unfortunately, there is no clear understanding of the diversity-performance relationship. Therefore, to improve our understanding of this phenomenon, it would be worthwhile to investigate further empirical settings. For this reason, we decided to study the music industry that, to our knowledge, has never been chosen as empirical setting for the application of the theoretical constructs linked to the topic of team diversity and performance. Our research aims at analyze the US music industry to study the relationship between job-related characteristics of team diversity and team performances.

The Potential for a New Value Adding Industry for Noni Tropical Fruit Producers

Morinda citrifolia (noni) grows widely throughout the Pacific and is native to Australia. It is a source of traditional medicine amongst Coastal Aboriginal Communities in Cape York, the Pacific Islands and South East Asia, and in recent years has experienced significant economic growth worldwide through a variety of health and cosmetic claims. The largest markets for noni are North America, Europe, Japan, Mexico, Asia and Australia with the worldwide market for these products estimated at US$400 million.

Economic modelling of grazing systems in the Fitzroy and Burdekin catchments

The Great Barrier Reef (GBR) is the largest reef system in the world; it covers an area of approximately 2,225,000 km² in the northern Queensland continental shelf. There are approximately 750 reefs that exist within 40 km of the Queensland coast. Recent research has identified that poor water quality is having negative impacts on the GBR (Haynes et al. 2007). The Fitzroy Basin covers 143,000 km² and is the largest catchment draining into the GBR as well as being one of the largest catchments in Australia (Karfs et al. 2009). The Burdekin Catchment is the second largest catchment entering into the GBR and covers 133,432 km².The prime determinant for the changes in water quality entering into the GBR have been attributed to grazing, with beef production the largest single land use industry comprising 90% of the land area (Karfs et al. 2009). Extensive beef production contributes over $1 billion dollars to the national economy annually and employs over 9000 people, many in rural communities (Gordon 2007). ‘Economic modelling of grazing systems in the Fitzroy and Burdekin catchments’ was a joint project with the Fitzroy Basin Association and the Queensland Department of Employment Economic Development and Innovation. The project was formed under the federally funded Caring For Our Country and the Reef Rescue programs. The project objectives were as follows; * Quantifying the costs of over-utilising available pasture and the resulting sediment leaving a representative farm for four of the major land systems in the Burdekin or Fitzroy catchments and identifying economically optimal pasture utilisation rates * Estimating the cost of reducing pasture utilisation rates below the determined optimal * Using this information, guide the selection of appropriate tools to achieve reduced utilisation rates e.g. extension process versus incentive payments or a combination of both * Model the biophysical and economic impacts of altering grazing systems to restore land condition e.g. from C condition to B condition for four land systems in the Burdekin or Fitzroy catchments.

Enhancing economic input to the CQSS2 Project report. Commissioned by the Fitzroy Basin Association.

The Fitzroy Basin is the second largest catchment area in Australia covering 143,00 km² and is the largest catchment for the Great Barrier Reef lagoon (Karfs et al., 2009). The Great Barrier Reef is the largest reef system in the world; it covers an area of approximately 225,000 km² in the northern Queensland continental shelf. There are approximately 750 reefs that exist within 40 km of the Queensland Coast (Haynes et al., 2007). The prime determinant for the changes in water quality have been attributed to grazing, with beef production the largest single land use industry comprising 90% of the land area (Karfs et al., 2009). In response to the depletion of water quality in the reef, in 2003 a Reef Water Quality plan was developed by the Australian and Queensland governments. The plan targets as a priority sediment contributions from grazing cattle in high risk catchments (The State of Queensland and Commonwealth of Australia, 2003). The economic incentive strategy designed includes analysing the costs and benefits of best management practice that will lead to improved water quality (The State of Queensland and Commonwealth of Australia, 2003).

Economic evaluation of precision controlled traffic farming in the Australian sugar industry: a case study of an early adopter

Controlled traffic has been identified as the most practical method of reducing compaction-related soil structural degradation in the Australian sugarcane industry. GPS auto-steer systems are required to maximize this potential. Unfortunately there is a perception that little economic gain will result from investing in this technology. Regardless, a number of growers have made the investment and are reaping substantial economic and lifestyle rewards. In this paper we assess the cost effectiveness of installing GPS guidance and using it to implement Precision Controlled Traffic Farming (PCTF) based on the experience of an early adopter. The Farm Economic Analysis Tool (FEAT) model was used with data provided by the grower to demonstrate the benefits of implementing PCTF. The results clearly show that a farming system based on PCTF and the minimum tillage improved farm gross margin by 11.8% and reduced fuel usage by 58%, compared to producers' traditional practice. PCTF and minimum tillage provide sugar producers with a tool to manage the price cost squeeze at a time of low sugar prices. These data provide producers with the evidence that investment in PCTF is economically prudent.

The Queensland forest industry

An overview of the commercial growing, management and processing of forest products in Queensland.

Relocation of Intensive Agriculture to Northern Queensland The Cotton Industry

Development of new agricultural industries in northern Australia is often perceived as a solution to changes in water availability that have occurred within southern Australia as a result of changes to government policy in response to and exacerbated by climate change. This report examines the likely private, social and community costs and benefits associated with the establishment of a cotton industry in the Burdekin. The research undertaken covers three spatial scales by modelling the response of cotton and to climate change at the crop and farm scale and linking this to regional scale modelling of the economy. Modelling crop growth as either a standalone crop or as part of a farm enterprise provides the clearest picture of how yields and water use will be affected under climate change. The alternative to this is to undertake very costly trials in environmental chambers. For this reason it is critical that funding for model development especially for crops being crop in novel environments be seen as a high priority for climate change and adaptation studies. Crop level simulations not only provide information on how the crop responds to climate change, they also illustrate that that these responses are the result of complex interactions and cannot necessarily be derived from the climate information alone. These simulations showed that climate change would lead to decreased cotton yields in 2030 and 2050 without the affect of CO2 fertilisation. Without CO2 fertilisation, yields would be decreased by 3.2% and 17.8%. Including CO2 fertilisation increased yields initially by 5.9%, but these were reduced by 3.6% in 2050. This still represents a major offset and at least ameliorates the impact of climate change on yield. To cope with the decreased in-crop rainfall (4.5% by 2030 and 15.8% in 2050) and an initial increase in evapotranspiration of 2% in 2030 and