17 resultados para software requirements specification

em eResearch Archive - Queensland Department of Agriculture


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Climate matching software (CLIMEX) was used to prioritise areas to explore for biological control agents in the native range of cat's claw creeper Macfadyena unguis-cati (Bignoniaceae), and to prioritise areas to release the agents in the introduced ranges of the plant. The native distribution of cat's claw creeper was used to predict the potential range of climatically suitable habitats for cat's claw creeper in its introduced ranges. A Composite Match Index (CMI) of cat's claw creeper was determined with the 'Match Climates' function in order to match the ranges in Australia and South Africa where the plant is introduced with its native range in South and Central America. This information was used to determine which areas might yield climatically-adapted agents. Locations in northern Argentina had CMI values which best matched sites with cat's claw creeper infestations in Australia and South Africa. None of the sites from where three currently prioritised biological control agents for cat's claw creeper were collected had CMI values higher than 0.8. The analysis showed that central and eastern Argentina, south Brazil, Uruguay and parts of Bolivia and Paraguay should be prioritised for exploration for new biological control agents for cat's claw creeper to be used in Australia and South Africa.

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Background: With the advances in DNA sequencer-based technologies, it has become possible to automate several steps of the genotyping process leading to increased throughput. To efficiently handle the large amounts of genotypic data generated and help with quality control, there is a strong need for a software system that can help with the tracking of samples and capture and management of data at different steps of the process. Such systems, while serving to manage the workflow precisely, also encourage good laboratory practice by standardizing protocols, recording and annotating data from every step of the workflow Results: A laboratory information management system (LIMS) has been designed and implemented at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) that meets the requirements of a moderately high throughput molecular genotyping facility. The application is designed as modules and is simple to learn and use. The application leads the user through each step of the process from starting an experiment to the storing of output data from the genotype detection step with auto-binning of alleles; thus ensuring that every DNA sample is handled in an identical manner and all the necessary data are captured. The application keeps track of DNA samples and generated data. Data entry into the system is through the use of forms for file uploads. The LIMS provides functions to trace back to the electrophoresis gel files or sample source for any genotypic data and for repeating experiments. The LIMS is being presently used for the capture of high throughput SSR (simple-sequence repeat) genotyping data from the legume (chickpea, groundnut and pigeonpea) and cereal (sorghum and millets) crops of importance in the semi-arid tropics. Conclusions: A laboratory information management system is available that has been found useful in the management of microsatellite genotype data in a moderately high throughput genotyping laboratory. The application with source code is freely available for academic users and can be downloaded from http://www.icrisat.org/bt-software-d-lims.htm

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The development of innovative methods of stock assessment is a priority for State and Commonwealth fisheries agencies. It is driven by the need to facilitate sustainable exploitation of naturally occurring fisheries resources for the current and future economic, social and environmental well being of Australia. This project was initiated in this context and took advantage of considerable recent achievements in genomics that are shaping our comprehension of the DNA of humans and animals. The basic idea behind this project was that genetic estimates of effective population size, which can be made from empirical measurements of genetic drift, were equivalent to estimates of the successful number of spawners that is an important parameter in process of fisheries stock assessment. The broad objectives of this study were to 1. Critically evaluate a variety of mathematical methods of calculating effective spawner numbers (Ne) by a. conducting comprehensive computer simulations, and by b. analysis of empirical data collected from the Moreton Bay population of tiger prawns (P. esculentus). 2. Lay the groundwork for the application of the technology in the northern prawn fishery (NPF). 3. Produce software for the calculation of Ne, and to make it widely available. The project pulled together a range of mathematical models for estimating current effective population size from diverse sources. Some of them had been recently implemented with the latest statistical methods (eg. Bayesian framework Berthier, Beaumont et al. 2002), while others had lower profiles (eg. Pudovkin, Zaykin et al. 1996; Rousset and Raymond 1995). Computer code and later software with a user-friendly interface (NeEstimator) was produced to implement the methods. This was used as a basis for simulation experiments to evaluate the performance of the methods with an individual-based model of a prawn population. Following the guidelines suggested by computer simulations, the tiger prawn population in Moreton Bay (south-east Queensland) was sampled for genetic analysis with eight microsatellite loci in three successive spring spawning seasons in 2001, 2002 and 2003. As predicted by the simulations, the estimates had non-infinite upper confidence limits, which is a major achievement for the application of the method to a naturally-occurring, short generation, highly fecund invertebrate species. The genetic estimate of the number of successful spawners was around 1000 individuals in two consecutive years. This contrasts with about 500,000 prawns participating in spawning. It is not possible to distinguish successful from non-successful spawners so we suggest a high level of protection for the entire spawning population. We interpret the difference in numbers between successful and non-successful spawners as a large variation in the number of offspring per family that survive – a large number of families have no surviving offspring, while a few have a large number. We explored various ways in which Ne can be useful in fisheries management. It can be a surrogate for spawning population size, assuming the ratio between Ne and spawning population size has been previously calculated for that species. Alternatively, it can be a surrogate for recruitment, again assuming that the ratio between Ne and recruitment has been previously determined. The number of species that can be analysed in this way, however, is likely to be small because of species-specific life history requirements that need to be satisfied for accuracy. The most universal approach would be to integrate Ne with spawning stock-recruitment models, so that these models are more accurate when applied to fisheries populations. A pathway to achieve this was established in this project, which we predict will significantly improve fisheries sustainability in the future. Regardless of the success of integrating Ne into spawning stock-recruitment models, Ne could be used as a fisheries monitoring tool. Declines in spawning stock size or increases in natural or harvest mortality would be reflected by a decline in Ne. This would be good for data-poor fisheries and provides fishery independent information, however, we suggest a species-by-species approach. Some species may be too numerous or experiencing too much migration for the method to work. During the project two important theoretical studies of the simultaneous estimation of effective population size and migration were published (Vitalis and Couvet 2001b; Wang and Whitlock 2003). These methods, combined with collection of preliminary genetic data from the tiger prawn population in southern Gulf of Carpentaria population and a computer simulation study that evaluated the effect of differing reproductive strategies on genetic estimates, suggest that this technology could make an important contribution to the stock assessment process in the northern prawn fishery (NPF). Advances in the genomics world are rapid and already a cheaper, more reliable substitute for microsatellite loci in this technology is available. Digital data from single nucleotide polymorphisms (SNPs) are likely to super cede ‘analogue’ microsatellite data, making it cheaper and easier to apply the method to species with large population sizes.

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Space allowance is a major factor influencing animal welfare. For livestock, at least, it plays a critical role in profitability, yet there is little information on the amount of space that animals require. The amount of space an animal occupies as a consequence of its shape and size can be estimated using allometry; linear dimensions (L) can be expressed as L = kW1/3 and surface area (S) as S = kW2/3, where k = a constant and W = the weight of the animal. Such equations have been used to determine the amount of space needed by standing (area [m2] = 0.019W0.66) and lying (area [m2] = 0.027W0.67) animals. Limited studies on the lying down and standing up behaviors of pigs and cattle suggest that the amount of space required can be estimated by area (m2) = 0.047W0.66. Linear space required per animal for behaviors such as feeding or drinking from a trough can be estimated from 0.064W0.33, but in groups this requirement will be affected by social interactions among group members and the amount of competition for the resource. Determining the amount of space for groups of animals is complex, as the amount of useable space can vary with group size and by how group members share space in time. Some studies have been conducted on the way in which groups of domestic fowl use space, but overall, we know very little about the ways in which livestock time-share space, synchronicity in the performance of behaviors, and the effects of spatial restrictions on behavior and welfare.

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Paropsis atomaria is a recently emerged pest of eucalypt plantations in subtropical Australia. Its broad host range of at least 20 eucalypt species and wide geographical distribution provides it the potential to become a serious forestry pest both within Australia and, if accidentally introduced, overseas. Although populations of P. atomaria are genetically similar throughout its range, population dynamics differ between regions. Here, we determine temperature-dependent developmental requirements using beetles sourced from temperate and subtropical zones by calculating lower temperature thresholds, temperature-induced mortality, and day-degree requirements. We combine these data with field mortality estimates of immature life stages to produce a cohort-based model, ParopSys, using DYMEX™ that accurately predicts the timing, duration, and relative abundance of life stages in the field and number of generations in a spring–autumn (September–May) field season. Voltinism was identified as a seasonally plastic trait dependent upon environmental conditions, with two generations observed and predicted in the Australian Capital Territory, and up to four in Queensland. Lower temperature thresholds for development ranged between 4 and 9 °C, and overall development rates did not differ according to beetle origin. Total immature development time (egg–adult) was approximately 769.2 ± S.E. 127.8 DD above a lower temperature threshold of 6.4 ± S.E. 2.6 °C. ParopSys provides a basic tool enabling forest managers to use the number of generations and seasonal fluctuations in abundance of damaging life stages to estimate the pest risk of P. atomaria prior to plantation establishment, and predict the occurrence and duration of damaging life stages in the field. Additionally, by using local climatic data the pest potential of P. atomaria can be estimated to predict the risk of it establishing if accidentally introduced overseas. Improvements to ParopSys’ capability and complexity can be made as more biological data become available.

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Models are abstractions of reality that have predetermined limits (often not consciously thought through) on what problem domains the models can be used to explore. These limits are determined by the range of observed data used to construct and validate the model. However, it is important to remember that operating the model beyond these limits, one of the reasons for building the model in the first place, potentially brings unwanted behaviour and thus reduces the usefulness of the model. Our experience with the Agricultural Production Systems Simulator (APSIM), a farming systems model, has led us to adapt techniques from the disciplines of modelling and software development to create a model development process. This process is simple, easy to follow, and brings a much higher level of stability to the development effort, which then delivers a much more useful model. A major part of the process relies on having a range of detailed model tests (unit, simulation, sensibility, validation) that exercise a model at various levels (sub-model, model and simulation). To underline the usefulness of testing, we examine several case studies where simulated output can be compared with simple relationships. For example, output is compared with crop water use efficiency relationships gleaned from the literature to check that the model reproduces the expected function. Similarly, another case study attempts to reproduce generalised hydrological relationships found in the literature. This paper then describes a simple model development process (using version control, automated testing and differencing tools), that will enhance the reliability and usefulness of a model.

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The project renewed the Breedcow and Dynama software making it compatible with modern computer operating systems and platforms. Enhancements were also made to the linkages between the individual programs and their operation. The suite of programs is a critical component of the skill set required to make soundly based plans and production choices in the north Australian beef industry.

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Sawing studies of mixed species and age plantation hardwoods representing potential early resource flows available to plantation sawlog processing industry. Provide information needed to underpin a business case to invest in small log sawing infrastucture.

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Management of fruit quality and pest infestations of mango and mangosteen for Market access requirements.

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Reef Project 20: Nitrogen fertiliser requirements of representative soils of the Burdekin (BRIA and Delta), and peaty soils of the Wet Tropics to inform the ReefWise farming Nutrient Calculator.

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This publication lists the more important wood properties of commercial timbers used for construction in Queensland. It also provides requirements and conditions of use for these timbers to provide appropriate design service life in various construction applications. The correct specification of timber considers a range of timber properties including, but not limited to, stress grade; durability class; moisture content and insect resistance. For the specification of timber sizes and spans, relevant Australian Standards and design manuals should be consulted—e.g. Australian Standard AS 1684 series Residential timber—framed construction parts 2 and 3 (Standards Australia 2006a;b.) Book 1 explains the terms used; with reference to nomenclature; origin and timber properties presented under specific column headings in the schedules (Book 2). It also explains target design life; applications and decay hazard zones; presented in the Book 2 Schedules. Book 2 consists of reference tables; presented as schedules A; B and C: • Schedule A contains commercial mixtures of unidentified timbers and of some Australian and imported softwoods. Index numbers 1–10 • Schedule B contains Australian-grown timber species; including both natural forests and plantations. Index numbers 11–493 • Schedule C contains timbers imported into Australia from overseas. Index numbers 494–606 Each schedule has two parts presenting data in tables. • Part 1: Nomenclature, origin and properties of imported timber species • Part 2: Approved uses for commercial mixtures of imported timber species The recommendations made in this publication assume that good building practice will be carried out.

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The results of research into the water relations and irrigation requirements of lychee are collated and reviewed. The stages of plant development are summarised, with an emphasis on factors influencing the flowering process. This is followed by reviews of plant water relations, water requirements, water productivity and, finally, irrigation systems. The lychee tree is native to the rainforests of southern China and northern Vietnam, and the main centres of production remain close to this area. In contrast, much of the research on the water relations of this crop has been conducted in South Africa, Australia and Israel where the tree is relatively new. Vegetative growth occurs in a series of flushes. Terminal inflorescences are borne on current shoot growth under cool (<15 °C), dry conditions. Trees generally do not produce fruit in the tropics at altitudes below 300 m. Poor and erratic flowering results in low and irregular fruit yields. Drought can enhance flowering in locations with dry winters. Roots can extract water from depths greater than 2 m. Diurnal trends in stomatal conductance closely match those of leaf water status. Both variables mirror changes in the saturation deficit of the air. Very little research on crop water requirements has been reported. Crop responses to irrigation are complex. In areas with low rainfall after harvest, a moderate water deficit before floral initiation can increase flowering and yield. In contrast, fruit set and yield can be reduced by a severe water deficit after flowering, and the risk of fruit splitting increased. Water productivity has not been quantified. Supplementary irrigation in South-east Asia is limited by topography and competition for water from the summer rice crop, but irrigation is practised in Israel, South Africa, Australia and some other places. Research is needed to determine the benefits of irrigation in different growing areas. Copyright © Cambridge University Press 2013.

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Understanding the life-history attributes of aquatic species is integral to the development of environmental-flow strategies in regulated river systems. This is particularly important when species are under continual and increasing pressure from water-resource development. In this study, the water temperature and flow requirements for spawning of the Fitzroy River golden perch (Macquaria ambigua oriens) were investigated over 4 years at 22 sites in the Fitzroy River catchment. Eggs, larvae and young-of-year (YOY) M. ambigua oriens were sampled on a variety of flow events to determine the environmental requirements for spawning. Eggs and larvae of M. ambigua oriens were detected during natural flow events generally with a minimum of 1.5 m river rise and duration of 7 days. Spawning was associated with the peak and/or recession of the first or second post-winter flow event where water temperatures exceeded 248 degrees C. Our data suggests that it is important to protect a range of flows, not just flood flows, as previously documented for this species. The interaction of spawning flows with existing and future water-resource development should be considered to ensure maintenance of the population viability of M. ambigua oriens.

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NeEstimator v2 is a completely revised and updated implementation of software that produces estimates of contemporary effective population size, using several different methods and a single input file. NeEstimator v2 includes three single-sample estimators (updated versions of the linkage disequilibrium and heterozygote-excess methods, and a new method based on molecular coancestry), as well as the two-sample (moment-based temporal) method. New features include the following: (i) an improved method for accounting for missing data; (ii) options for screening out rare alleles; (iii) confidence intervals for all methods; (iv) the ability to analyse data sets with large numbers of genetic markers (10000 or more); (v) options for batch processing large numbers of different data sets, which will facilitate cross-method comparisons using simulated data; and (vi) correction for temporal estimates when individuals sampled are not removed from the population (Plan I sampling). The user is given considerable control over input data and composition, and format of output files. The freely available software has a new JAVA interface and runs under MacOS, Linux and Windows.

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A recent report to the Australian Government identified concerns relating to Australia's capacity to respond to a medium to large outbreak of FMD. To assess the resources required, the AusSpread disease simulation model was used to develop a plausible outbreak scenario that included 62 infected premises in five different states at the time of detection, 28 days after the disease entered the first property in Victoria. Movements of infected animals and/or contaminated product/equipment led to smaller outbreaks in NSW, Queensland, South Australia and Tasmania. With unlimited staff resources, the outbreak was eradicated in 63 days with 54 infected premises and a 98% chance of eradication within 3 months. This unconstrained response was estimated to involve 2724 personnel. Unlimited personnel was considered unrealistic, and therefore, the course of the outbreak was modelled using three levels of staffing and the probability of achieving eradication within 3 or 6 months of introduction determined. Under the baseline staffing level, there was only a 16% probability that the outbreak would be eradicated within 3 months, and a 60% probability of eradication in 6 months. Deployment of an additional 60 personnel in the first 3 weeks of the response increased the likelihood of eradication in 3 months to 68%, and 100% in 6 months. Deployment of further personnel incrementally increased the likelihood of timely eradication and decreased the duration and size of the outbreak. Targeted use of vaccination in high-risk areas coupled with the baseline personnel resources increased the probability of eradication in 3 months to 74% and to 100% in 6 months. This required 25 vaccination teams commencing 12 days into the control program increasing to 50 vaccination teams 3 weeks later. Deploying an equal number of additional personnel to surveillance and infected premises operations was equally effective in reducing the outbreak size and duration.