7 resultados para Zones of Peace

em eResearch Archive - Queensland Department of Agriculture


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Isolates of Sclerotinia sclerotiorum were collected from infected lentil plants from 2 agro-ecological zones of Syria and used to study their comparative growth on culture media and pathogenicity on different lentil genotypes. The growth studies were carried out on Potato Dextrose Agar (PDA) growth media under laboratory conditions. Mycelial radial growth and sclerotial production were the parameters used to compare the isolates. Pathogenicity studies were carried out with selected isolates on 10 lentil genotypes, infected as detached shoots and as whole potted-plants in the plastic house. The isolates showed considerable variation in cultural characteristics through mycelial growth, mycelial pigmentation and sclerotial production in the media plates. There were significant differences in the growth and sclerotial production of most of the isolates, but no apparent correlation between mycelial growth and sclerotial production among the isolates. Genotype by isolate interactions was significant for the isolates tested for pathogenicity. These interactions, however, appeared to be caused by differences in virulence of the isolates and did not suggest the occurrence of distinct pathogenic races of the pathogen isolates.

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Wheat is one of the major food crops in the world. It is Australia's largest crop and most important agricultural commodity. In Australia the crop is grown under rainfed conditions with inherently important regional environmental differences; wheat growing areas are characterized by winter dominant rainfall in southern and western Australia and summer rainfall in northern Australia. Maximizing yield potential across these diverse regions is dependent upon managing, either genetically or agronomically, those factors in the environment that limit yield. The potential of synthetic backcross lines (SBLs) to increase yield in the diverse agroecological zones of Australia was investigated. Significant yield advantages were found for many of the SBLs across diverse environments. Depending on the environment, the yield of the SBLs ranged from 8% to 30% higher than the best local check in Australia. Apart from adaptation to semiarid water stressed conditions, some SBLs were also found to be significantly higher yielding under more optimal (irrigated) conditions. The four testing environments were classified into two groups, with the northern and southern environments being in separate groups. An elite group of SBLs was identified that exhibited broad adaptation across all diverse Australian environments included in this study. Other SBLs showed specific adaptation to either northern or southern Australia. This study showed that SBLs are likely to provide breeders with the opportunity to significantly improve wheat yield beyond what was previously possible in a number of diverse production environments.

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Background: The territorial fishing zones of Australia and Indonesia are contiguous to the north of Australia in the Timor and Arafura Seas and in the Indian Ocean to the north of Christmas Island. The area surrounding the shared boundary consists of a variety of bio-diverse marine habitats including shallow continental shelf waters, oceanic trenches and numerous offshore islands. Both countries exploit a variety of fisheries species, including whaler (Carcharhinus spp.) and hammerhead sharks (Sphyrna spp.). Despite their differences in social and financial arrangements, the two countries are motivated to develop complementary co-management practices to achieve resource sustainability. An essential starting point is knowledge of the degree of population subdivision, and hence fisheries stock status, in exploited species. Results: Populations of four commercially harvested shark species (Carcharhinus obscurus, Carcharhinus sorrah, Prionace glauca, Sphyrna lewini) were sampled from northern Australia and central Indonesia. Neutral genetic markers (mitochondrial DNA control region sequence and allelic variation at co-dominant microsatellite loci) revealed genetic subdivision between Australian and Indonesian populations of C. sorrah. Further research is needed to address the possibility of genetic subdivision among C. obscurus populations. There was no evidence of genetic subdivision for P. glauca and S. lewini populations, but the sampling represented a relatively small part of their distributional range. For these species, more detailed analyses of population genetic structure is recommended in the future. Conclusion: Cooperative management between Australia and Indonesia is the best option at present for P. glauca and S. lewini, while C. sorrah and C. obscurus should be managed independently. On-going research on these and other exploited shark and ray species is strongly recommended. Biological and ecological similarity between species may not be a predictor of population genetic structure, so species-specific studies are recommended to provide new data to assist with sustainable fisheries management.

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Objective To describe the influence of the dingo (Canis lupus dingo) on the past, present and future distributions of sheep in Australia. Design The role of the dingo in the rise and fall of sheep numbers is reviewed, revised data are provided on the present distribution and density of sheep and dingoes, and historical patterns of sheep distribution are used to explore the future of rangeland sheep grazing. Results Dingoes are a critical causal factor in the distribution of sheep at the national, regional and local levels. Dingo predation contributed substantially to the historical contraction of the sheep industry to its present-day distribution, which is almost exclusively confined to areas within fenced dingo exclusion zones. Dingo populations and/or their influence are now present and increasing in all sheep production zones of Australia, inclusive of areas that were once dingo free'. Conclusions Rangeland production of wool and sheep meat is predicted to disappear within 30-40 years if the present rate of contraction of the industry continues unabated. Understanding the influence of dingoes on sheep production may help refine disease response strategies and help predict the future distribution of sheep and their diseases.

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Mikania micrantha (Asteraceae) commonly known as mikania, is a major invasive alien plant (IAP) in the tropical humid agricultural and forest zones of the Asia-Pacific region. This fast-growing Neotropical vine is able to smother plants in agricultural ecosystems, agroforestry and natural habitats, reducing productivity and biodiversity. Fungal pathogens were first investigated for the classical biological control of this weed in 1996. This resulted in the selection and screening of the highly host-specific and damaging rust pathogen, Puccinia spegazzinii (Pucciniales). It was first released in India and China in 2005/6, although it is not believed to have established. Since then, it has been released successfully in Taiwan, Papua New Guinea (PNG), Fiji and most recently Vanuatu. The rust has established and is spreading rapidly after applying lessons learned from the first releases on the best rust pathotype and release strategy. In PNG, direct monitoring of vegetation change has demonstrated that the rust is having a significant impact on M. micrantha, with no unpredicted non-target impacts. Despite this, the authorities in many countries where mikania is a problem remain cautious about releasing the rust. In Western Samoa, introduction of the rust was not pursued because of a conflict of interest, and the perception that mikania suppresses even worse weeds. For some, ‘pathophobia’ is still a major obstacle. In Indonesia, where insects for weed CBC have been introduced, pathogens will currently not be considered. In other countries such as Bhutan and Myanmar, there are no baseline data on the presence and impact of IAPs and, with no history of CBC, no institutional framework for implementing this approach. Malaysia has a well-developed framework, but capacity needs to be built in the country. Overall, it remains critical to have champions at decision making levels. Hence, even with an effective ‘off-the-shelf’ agent available, implementation of mikania CBC still requires significant inputs tailored to the countries’ specific needs.

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Rabbit haemorrhagic disease is a major tool for the management of introduced, wild rabbits in Australia. However, new evidence suggests that rabbits may be developing resistance to the disease. Rabbits sourced from wild populations in central and southeastern Australia, and domestic rabbits for comparison, were experimentally challenged with a low 60 ID50 oral dose of commercially available Czech CAPM 351 virus - the original strain released in Australia. Levels of resistance to infection were generally higher than for unselected domestic rabbits and also differed (0-73% infection rates) between wild populations. Resistance was lower in populations from cooler, wetter regions and also low in arid regions with the highest resistance seen within zones of moderate rainfall. These findings suggest the external influences of non-pathogenic calicivirus in cooler, wetter areas and poor recruitment in arid populations may influence the development rate of resistance in Australia.

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Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising methodology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.