Impact of resistance on the efficacy of binary combinations of spinosad, chlorpyrifos-methyl and s-methoprene against five stored-grain beetles

Laboratory experiments were conducted to determine the efficacy of spinosad (a biopesticide), chlorpyrifos-methyl (an organophosphorus compound (OP)) and s-methoprene (a juvenile hormone analogue) applied alone and in binary combinations against five stored-grain beetles in wheat. There were three strains of Rhyzopertha dominica, and one strain each of Sitophilus oryzae, Tribolium castaneum, Oryzaephilus surinamensis and Cryptolestes ferrugineus. These strains were chosen to represent a range of possible resistant genotypes, exhibiting resistance to organophosphates, pyrethroids or methoprene. Treatments were applied at rates that are registered or likely to be registered in Australia. Adults were exposed to freshly treated wheat for 2 weeks, and the effects of treatments on mortality and reproduction were determined. No single protectant or protectant combination controlled all insect strains, based on the criterion of >99% reduction in the number of live F1 adults relative to the control. The most effective combinations were spinosad at 1 mg kg-1+chlorpyrifos-methyl at 10 mg kg-1 which controlled all strains except for OP-resistant O. surinamensis, and chlorpyrifos-methyl at 10 mg kg-1+s-methoprene at 0.6 mg kg-1 which controlled all strains except for methoprene-resistant R. dominica. The results of this study demonstrate the difficulty in Australia, and potentially other countries which use protectants, of finding protectant treatments to control a broad range of pest species in the face of resistance development.

Characterisation of chicken Campylobacter jejuni isolates using resolution optimised single nucleotide polymorphisms and binary gene markers

The principal objective of this study was to determine if Campylobacter jejuni genotyping methods based upon resolution optimised sets of single nucleotide polymorphisms (SNPs) and binary genetic markers were capable of identifying epidemiologically linked clusters of chicken-derived isolates. Eighty-eight C. jejuni isolates of known flaA RFLP type were included in the study. They encompassed three groups of ten isolates that were obtained at the same time and place and possessed the same flaA type. These were regarded as being epidemiologically linked. Twenty-six unlinked C. jejuni flaA type I isolates were included to test the ability of SNP and binary typing to resolve isolates that were not resolved by flaA RFLP. The remaining isolates were of different flaA types. All isolates were typed by real-time PCR interrogation of the resolution optimised sets of SNPs and binary markers. According to each typing method, the three epidemiologically linked clusters were three different clones that were well resolved from the other isolates. The 26 unlinked C. jejuni flaA type I isolates were resolved into 14 SNP-binary types, indicating that flaA typing can be unreliable for revealing epidemiological linkage. Comparison of the data with data from a fully typed set of isolates associated with human infection revealed that abundant lineages in the chicken isolates that were also found in the human isolates belonged to clonal complex (CC) -21 and CC-353, with the usually rare C-353 member ST-524 being especially abundant in the chicken collection. The chicken isolates selected to be diverse according to flaA were also diverse according to SNP and binary typing. It was observed that CC-48 was absent in the chicken isolates, despite being very common in Australian human infection isolates, indicating that this may be a major cause of human disease that is not chicken associated.

Modelling predicts positive and negative interactions between three Australian tropical tree species in monoculture and binary mixture

Computer modelling promises to be an important tool for analysing and predicting interactions between trees within mixed species forest plantations. This study explored the use of an individual-based mechanistic model as a predictive tool for designing mixed species plantations of Australian tropical trees. The `spatially explicit individually based-forest simulator' (SeXI-FS) modelling system was used to describe the spatial interaction of individual tree crowns within a binary mixed-species experiment. The three-dimensional model was developed and verified with field data from three forest tree species grown in tropical Australia. The model predicted the interactions within monocultures and binary mixtures of Flindersia brayleyana, Eucalyptus pellita and Elaeocarpus grandis, accounting for an average of 42% of the growth variation exhibited by species in different treatments. The model requires only structural dimensions and shade tolerance as species parameters. By modelling interactions in existing tree mixtures, the model predicted both increases and reductions in the growth of mixtures (up to +/-50% of stem volume at 7 years) compared to monocultures. This modelling approach may be useful for designing mixed tree plantations.

Developing a dynamic regional brand - focus on flavour.

This project has delivered technical sensory language that accurately and precisely describes the flavour and texture of key seafood species to the seafood industry of the Eyre Peninsula. Industry members and producers have been trained on the sensory properties of their products and are equipped with knowledge of how to apply sensory language to their products for their customers. The seafood industry of the Eyre Peninsula has embraced the “Eyre Peninsula Seafood Flavour wheel” and is already using it in the promotion of their products. In addition local, national and international seafood producers and end-users have indicated a strong interest in the results and outputs of this project and the potential application of the seafood flavour wheel in their respective businesses.

Separating grazing and rainfall effects at regional scale using remote sensing imagery: A dynamic reference-cover method

Remote detection of management-related trend in the presence of inter-annual climatic variability in the rangelands is difficult. Minimally disturbed reference areas provide a useful guide, but suitable benchmarks are usually difficult to identify. We describe a method that uses a unique conceptual framework to identify reference areas from multitemporal sequences of ground cover derived from Landsat TM and ETM+ imagery. The method does not require ground-based reference sites nor GIS layers about management. We calculate a minimum ground cover image across all years to identify locations of most persistent ground cover in years of lowest rainfall. We then use a moving window approach to calculate the difference between the window's central pixel and its surrounding reference pixels. This difference estimates ground-cover change between successive below-average rainfall years, which provides a seasonally interpreted measure of management effects. We examine the approach's sensitivity to window size and to cover-index percentiles used to define persistence. The method successfully detected management-related change in ground cover in Queensland tropical savanna woodlands in two case studies: (1) a grazing trial where heavy stocking resulted in substantial decline in ground cover in small paddocks, and (2) commercial paddocks where wet-season spelling (destocking) resulted in increased ground cover. At a larger scale, there was broad agreement between our analysis of ground-cover change and ground-based land condition change for commercial beef properties with different a priori ratings of initial condition, but there was also some disagreement where changing condition reflected pasture composition rather than ground cover. We conclude that the method is suitably robust to analyse grazing effects on ground cover across the 1.3 x 10(6) km(2) of Queensland's rangelands. Crown Copyright (c) 2012 Published by Elsevier Inc. All rights reserved.