Cross-protection study of the nine serovars of Haemophilus paragallinarum in the Kume haemagglutinin scheme

The cross-protection and haemagglutination-inhibition antibodies present in chickens vaccinated with one of the nine currently recognized Kume haemagglutinin serovars of Haemophilus paragallinarum were investigated. The results confirmed the widely accepted dogma that serogroups A, B, and C represent three distinct immunovars. Within Kume serogroup A, there was generally good cross-protection among all four serovars. However, within Kume serogroup C, there was evidence of a reduced level of cross protection between some of the four serovars. The haemagglutination-inhibition antibody levels generally showed the same trend as with the cross-protection results. This study suggests that some apparent field failures of infectious coryza vaccines may be due to a lack of cross-protection between the vaccine strains and the field strains. Our results will help guide the selection of strains for inclusion in infectious coryza vaccines.

Estimation in a multiplicative mixed model involving a genetic relationship matrix.

Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs) in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA) form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.

The climate change risk management matrix for the grazing industry of northern Australia

The complexity, variability and vastness of the northern Australian rangelands make it difficult to assess the risks associated with climate change. In this paper we present a methodology to help industry and primary producers assess risks associated with climate change and to assess the effectiveness of adaptation options in managing those risks. Our assessment involved three steps. Initially, the impacts and adaptation responses were documented in matrices by ‘experts’ (rangeland and climate scientists). Then, a modified risk management framework was used to develop risk management matrices that identified important impacts, areas of greatest vulnerability (combination of potential impact and adaptive capacity) and priority areas for action at the industry level. The process was easy to implement and useful for arranging and analysing large amounts of information (both complex and interacting). Lastly, regional extension officers (after minimal ‘climate literacy’ training) could build on existing knowledge provided here and implement the risk management process in workshops with rangeland land managers. Their participation is likely to identify relevant and robust adaptive responses that are most likely to be included in regional and property management decisions. The process developed here for the grazing industry could be modified and used in other industries and sectors. By 2030, some areas of northern Australia will experience more droughts and lower summer rainfall. This poses a serious threat to the rangelands. Although the impacts and adaptive responses will vary between ecological and geographic systems, climate change is expected to have noticeable detrimental effects: reduced pasture growth and surface water availability; increased competition from woody vegetation; decreased production per head (beef and wool) and gross margin; and adverse impacts on biodiversity. Further research and development is needed to identify the most vulnerable regions, and to inform policy in time to facilitate transitional change and enable land managers to implement those changes.

Development of a multi-locus sequence typing scheme for avian isolates of Pasteurella multocida.

A total of 63 isolates of Pasteurella multocida from Australian poultry, all associated with fowl cholera outbreaks, and three international reference strains, representing the three subspecies within P. multocida were used to develop a multi-locus sequence typing scheme. Primers were designed for conserved regions of seven house-keeping enzymes - adk, est, gdh, mdh, pgi, pmi and zwf - and internal fragments of 570-784 bp were sequenced for all isolates and strains. The number of alleles at the different loci ranged from 11 to 20 and a total of 29 allelic profiles or sequence types were recognised amongst the 66 strains. There was a strong concordance between the MLST data and the existing multi-locus enzyme electrophoresis and ribotyping data. When used to study a sub-set of isolates with a known detailed epidemiological history, the MLST data matched the results given by restriction endonuclease analysis, pulsed-field gel electrophoresis, ribotyping and REP-PCR. The MLST scheme provides a high level of resolution and is an excellent tool for studying the population structure and epidemiology of P. multocida.

Sorghum Midge Tested Scheme

Scheme provides independant testing and official industry midge resistance rating of pre-commercial sorghum varieities. Continuation of current project.

Sorghum Midge Testing Scheme

Scheme provides independant testing and official industry midge resistance rating of pre-commercial sorghum varieities.

Influence of site, storage and steaming on Eucalyptus nitens log-end splitting

Key message Log-end splitting is one of the single most important defects in veneer logs. We show that log-end splitting in the temperate plantation species Eucalyptus nitens varies across sites and within-tree log position and increases with time in storage. Context Log-end splitting is one of the single most important defects in veneer logs because it can substantially reduce the recovery of veneer sheets. Eucalyptus nitens can develop log-end splits, but factors affecting log-end splitting in this species are not well understood. Aims The present study aims to describe the effect of log storage and steaming on the development of log-end splitting in logs from different plantations and log positions within the tree. Methods The study was conducted on upper and lower logs from each of 41 trees from three 20–22-year-old Tasmanian E. nitens plantations. Log-end splitting was assessed immediately after felling, after transport and storage in a log-yard, and just before peeling. A pre-peeling steam treatment was applied to half the logs. Results Site had a significant effect on splitting, and upper logs split more than lower logs with storage. Splitting increased with tree diameter breast height (DBH), but this relationship varied with site. The most rapidly growing site had more splitting even after accounting for DBH. No significant effect of steaming was detected. Conclusion Log-end splitting varied across sites and within-tree log position and increased with time in storage.