Enhanced diagnostic platforms for Post Entry Quarantine (PEQ)

Enhanced diagnostic platforms for Post Entry Quarantine (PEQ) and market access (Phase 1).

Alternative fruit fly control for market access and to enhance IPM in eggplant

Eggplant was identified as another fruit fly host commodity where recent changes to interstate market access requirements are causing problems for industry. The proposed research aims to develop a systems approach to meet interstate market access requirements.

Improved Post Entry Quarantine Diagnostics

Develop a new diagnostic platform for Post Entry Plant Quarantine to support the detection of Emergency Plant Pests in the Australian Grains and Nursery Industries.

CRC40142 Defining the plant pathogen risk posed by international travellers

This project will define the plant pathogen incursion risk posed by people returning from overseas and interstate travel. This will be achieved through the development of technically sound sample/survey methodologies. The project will initially focus on cereal rusts. An assessment of the current level of human mediated rust entries into Australia will be determined through the sampling of travellers who have been known to have visited grain production regions overseas.

Post Entry Plant Quarantine

The seeds of the majority of commercial crops must be grown for one generation in post-entry plant quarantine on arrival in Australia. Live plants and cuttings must also undergo quarantine screening on arrival, and spend a minimum of three months in quarantine.

Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.

Hierarchical Bayesian modelling of plant pest invasions with human-mediated dispersal

Hierarchical Bayesian models can assimilate surveillance and ecological information to estimate both invasion extent and model parameters for invading plant pests spread by people. A reliability analysis framework that can accommodate multiple dispersal modes is developed to estimate human-mediated dispersal parameters for an invasive species. Uncertainty in the observation process is modelled by accounting for local natural spread and population growth within spatial units. Broad scale incursion dynamics are based on a mechanistic gravity model with a Weibull distribution modification to incorporate a local pest build-up phase. The model uses Markov chain Monte Carlo simulations to infer the probability of colonisation times for discrete spatial units and to estimate connectivity parameters between these units. The hierarchical Bayesian model with observational and ecological components is applied to a surveillance dataset for a spiralling whitefly (Aleurodicus dispersus) invasion in Queensland, Australia. The model structure provides a useful application that draws on surveillance data and ecological knowledge that can be used to manage the risk of pest movement.

Dipping and jetting with tea tree (Melaleuca alternifolia) oil formulations control lice (Bovicola ovis) on sheep

The in vivo pediculicidal effectiveness of 1% and 2% formulations of tea tree (Melaleuca alternifolia) oil (TTO) against sheep chewing lice (Bovicola ovis) was tested in two pen studies. Immersion dipping of sheep shorn two weeks before treatment in both 1% and 2% formulations reduced lice to non detectable levels. No lice were found on any of the treated sheep despite careful inspection of at least 40 fleece partings per animal at 2, 6, 12 and 20 weeks after treatment. In the untreated sheep louse numbers increased from a mean (+/- SE) of 2.4 (+/- 0.7) per 10 cm fleece part at 2 weeks to 12.3 (+/- 4.2) per part at 20 weeks. Treatment of sheep with 6 months wool by jetting (high pressure spraying into the fleece) reduced louse numbers by 94% in comparison to controls at two weeks after treatment with both 1% and 2% TTO formulations. At 6 and 12 weeks after treatment reductions were 94% and 91% respectively with the 1% formulation and 78% and 84% respectively with the 2% formulation. TTO treatment also appeared to reduce wool damage in infested sheep. Laboratory studies indicated that tea tree oil 'stripped' from solution with a progressive reduction in concentration as well as volume as more wool was dipped, indicating that reinforcement of active ingredient would be required to maintain effectiveness when large numbers of sheep are treated. The results of these studies suggest significant potential for the development of ovine lousicides incorporating TTO. (C) 2012 Elsevier B.V. All rights reserved.

Drywood termites in Queensland.

Discusses: Biology and damage, native drywood termite, West Indian drywood termite, building inspection, prevention, treating active infestation.

Improving the prediction of odour impacts from meat chicken farms with detailed ventilation and odour data

Odour from meat chicken (broiler) farms is an environmental issue affecting the sustainable development of the chicken meat industry but is a normal part of broiler production. Odour plumes exhausted from broiler sheds interact with the environment, where dispersion and dilution of the odours varies constantly, especially diurnally. The potential for odour impacts is greatest when odour emission rates are high and/or when atmospheric dispersion and dilution of odour plumes is limited (i.e. during stable conditions). We continuously monitored ventilation rate, on-site weather conditions, atmospheric stability, and estimated odour concentration with an artificial olfaction system. Detailed inspection of odour emission rates at critical times, i.e. dawn, dusk and night time, revealed that maximum daily and batch odour emission rates are not necessarily the cause of odour impacts. Periods of lower odour emission rates on each day are more likely to correspond with odour impacts. Odour emission rates need to be measured at the times when odour impacts are most likely to occur, which is likely to be at night. Additionally, high resolution ventilation rate data should be sought after to improve odour emission models, especially at critical times of the day. Consultants, regulators and researchers need to give more thought to odour emission rates from meat chicken farms to improved prediction and management of odour impacts.