8 resultados para Shape factor
em eResearch Archive - Queensland Department of Agriculture
Resumo:
Dry-season weight loss in grazing cattle in northern Australia has been attenuated using a number of strategies (Hunter and Vercoe, 1987, Sillence et al. 1993, Gazzola and Hunter, 1999). Furthermore, the potential to improve efficiency of feed utilisation (and thus, dry-season performance) in ruminants through conventional modulation of the insulin-like growth factor (IGF) axis (Oddy and Owens, 1997, Hill et al., 1999) and through immunomodulation of the IGF axis (Hill et al., 1998a,b) has been demonstrated. The present study investigated the use of a vaccine directed against IGFBP-1 in Brahman steers which underwent a period of nutritional restriction followed by a return to wet-season grazing.
Resumo:
Globalisation is set to have a major impact on world horticultural production and distribution of fruit and vegetables throughout the world. In contrast to developing countries such as China, production and consumption of fresh fruit and vegetables in most developed countries is relatively static. For developed countries, we are starting to see consolidation in the number of farms producing fruit and vegetables with falling or static prices and real farm incomes. Global supply chains are now dominated by a few large multi-national retailers supplied by preferred trans-national distribution companies. The major competitive advantages that are emerging are consistency of supply of high quality product over an extended season and the control of genetic resources and their marketing. To capture these new competitive advantages, new strategic analyses and planning processes must be implemented. In the past, strategic analyses and planning has been undertaken on an ad hoc basis without accurate global intelligence. In the future, working ‘on the supply chain’ will become equally, if not more important, than working ‘in the supply chain’. A revised approach to strategic planning, which encompasses and adjusts for the changes caused by globalisation, is urgently needed. A new 6-step strategic analyses process is described.
Resumo:
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.
Resumo:
Modeling of cultivar x trial effects for multienvironment trials (METs) within a mixed model framework is now common practice in many plant breeding programs. The factor analytic (FA) model is a parsimonious form used to approximate the fully unstructured form of the genetic variance-covariance matrix in the model for MET data. In this study, we demonstrate that the FA model is generally the model of best fit across a range of data sets taken from early generation trials in a breeding program. In addition, we demonstrate the superiority of the FA model in achieving the most common aim of METs, namely the selection of superior genotypes. Selection is achieved using best linear unbiased predictions (BLUPs) of cultivar effects at each environment, considered either individually or as a weighted average across environments. In practice, empirical BLUPs (E-BLUPs) of cultivar effects must be used instead of BLUPs since variance parameters in the model must be estimated rather than assumed known. While the optimal properties of minimum mean squared error of prediction (MSEP) and maximum correlation between true and predicted effects possessed by BLUPs do not hold for E-BLUPs, a simulation study shows that E-BLUPs perform well in terms of MSEP.
Resumo:
Quality and safety evaluation of agricultural products has become an increasingly important consideration in market/commercial viability and systems for such evaluations are now demanded by customers, including distributors and retailers. Unfortunately, most horticultural products struggle with delivering adequate and consistent quality to the consumer. Removing inconsistencies and providing what the consumer expects is a key factor for retaining and expanding both domestic and international markets. Most commercial quality classification systems for fruit and vegetables are based on external features of the product, for example: shape, colour, size, weight and blemishes. However, the external appearance of most fruit is generally not an accurate guide to the internal or eating quality of the fruit. Internal quality of fruit is currently subjectively judged on attributes such as volatiles, firmness, and appearance. Destructive subjective measures such as internal flesh colour, or objective measures such as extraction of juice to measure sweetness (oBrix) or assessment of dry matter (DM) content are also used, although obviously not for every fruit – just a sample to represent the whole consignment. For avocado fruit, external colour is not a maturity characteristic, and its smell is too weak and appears later in its maturity stage (Gaete-Garreton et al., 2005). Since maturity is a major component of avocado quality and palatability, it is important to harvest mature fruit, so as to ensure that fruit will ripen properly and have acceptable eating quality. Currently, commercial avocado maturity estimation is based on destructive assessment of the %DM, and sometimes percent oil, both of which are highly correlated with maturity (Clark et al., 2003; Mizrach & Flitsanov, 1999). Avocados Australia Limited (AAL (2008)) recommend a minimum maturity standard for its growers of 23 %DM (greater than 10% oil content) for the ‘Hass’ cultivar, although consumer studies indicate a preference for at least 25 %DM (Harker et al., 2007).
Resumo:
BACKGROUND Control of pests in stored grain and the evolution of resistance to pesticides are serious problems worldwide. A stochastic individual-based two-locus model was used to investigate the impact of two important issues, the consistency of pesticide dosage through the storage facility and the immigration rate of the adult pest, on overall population control and avoidance of evolution of resistance to the fumigant phosphine in an important pest of stored grain, the lesser grain borer. RESULTS A very consistent dosage maintained good control for all immigration rates, while an inconsistent dosage failed to maintain control in all cases. At intermediate dosage consistency, immigration rate became a critical factor in whether control was maintained or resistance emerged. CONCLUSION Achieving a consistent fumigant dosage is a key factor in avoiding evolution of resistance to phosphine and maintaining control of populations of stored-grain pests; when the dosage achieved is very inconsistent, there is likely to be a problem regardless of immigration rate. © 2012 Society of Chemical Industry
Resumo:
Hendra virus causes sporadic but typically fatal infection in horses and humans in eastern Australia. Fruit-bats of the genus Pteropus (commonly known as flying-foxes) are the natural host of the virus, and the putative source of infection in horses; infected horses are the source of human infection. Effective treatment is lacking in both horses and humans, and notwithstanding the recent availability of a vaccine for horses, exposure risk mitigation remains an important infection control strategy. This study sought to inform risk mitigation by identifying spatial and environmental risk factors for equine infection using multiple analytical approaches to investigate the relationship between plausible variables and reported Hendra virus infection in horses. Spatial autocorrelation (Global Moran’s I) showed significant clustering of equine cases at a distance of 40 km, a distance consistent with the foraging ‘footprint’ of a flying-fox roost, suggesting the latter as a biologically plausible basis for the clustering. Getis-Ord Gi* analysis identified multiple equine infection hot spots along the eastern Australia coast from far north Queensland to central New South Wales, with the largest extending for nearly 300 km from southern Queensland to northern New South Wales. Geographically weighted regression (GWR) showed the density of P. alecto and P. conspicillatus to have the strongest positive correlation with equine case locations, suggesting these species are more likely a source of infection of Hendra virus for horses than P. poliocephalus or P. scapulatus. The density of horses, climate variables and vegetation variables were not found to be a significant risk factors, but the residuals from the GWR suggest that additional unidentified risk factors exist at the property level. Further investigations and comparisons between case and control properties are needed to identify these local risk factors.
Resumo:
Four species of large mackerels (Scomberomorus spp.) co-occur in the waters off northern Australia and are important to fisheries in the region. State fisheries agencies monitor these species for fisheries assessment; however, data inaccuracies may exist due to difficulties with identification of these closely related species, particularly when specimens are incomplete from fish processing. This study examined the efficacy of using otolith morphometrics to differentiate and predict among the four mackerel species off northeastern Australia. Seven otolith measurements and five shape indices were recorded from 555 mackerel specimens. Multivariate modelling including linear discriminant analysis (LDA) and support vector machines, successfully differentiated among the four species based on otolith morphometrics. Cross validation determined a predictive accuracy of at least 96% for both models. An optimum predictive model for the four mackerel species was an LDA model that included fork length, feret length, feret width, perimeter, area, roundness, form factor and rectangularity as explanatory variables. This analysis may improve the accuracy of fisheries monitoring, the estimates based on this monitoring (i.e. mortality rate) and the overall management of mackerel species in Australia.