29 resultados para Frequency diverse array

em eResearch Archive - Queensland Department of Agriculture


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Global trends in human population and agriculture dictate that future calls made on the resources (physical, human, financial) and systems involved in producing food will be increasingly more demanding and complex. Both plant breeding and improved agronomy lift the potential yield of crops, a key component in progressing farm yield, so society can reasonably expect both agronomy as a science and agronomists as practitioners to contribute to the successful delivery of necessary change. By reflecting on current trends in agricultural production (diversification, intensification, integration, industrialisation, automation) and deconstructing a futuristic scenario of attempting agricultural production on Mars, it seems the skills agronomists will require involve not only the mandatory elements of their discipline but also additional skills that enable engagement with, even leadership of, teams who integrate (in sum or part) engineering, (agri-)business, economics and operational management, and build the social capital required to create and maintain a diverse array of enhanced and new ethical production systems and achieve increasing efficiencies within them.

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Mastreviruses (family Geminiviridae) that infect monocotyledonous plants occur throughout the temperate and tropical regions of Asia, Africa, Europe and Australia. Despite the identification of a very diverse array of mastrevirus species whose members infect African monocots, few such species have been discovered in other parts of the world. For example, the sequence of only a single monocot-infecting mastrevirus, Chloris striate mosaic virus (CSMV), has been reported so far from Australia, even though earlier biological and serological studies suggested that other distinct mastreviruses were present. Here, we have obtained the complete nucleotide sequence of a virus from the grass Digitaria didactyla originating from Australia. Analysis of the sequence shows the virus to be a typical mastrevirus, with four open reading frames, two in each orientation, separated by two non-coding intergenic regions. Although it showed the highest levels of sequence identity to CSMV (68.7%), their sequences are sufficiently diverse for the virus to be considered a member of a new species in the genus Mastrevirus, based on the present species demarcation criteria. We propose that the name first used during the 1980s be used for this species, Digitaria didactyla striate mosaic virus (DDSMV).

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Obesity is associated with many chronic disease states, such as diabetes mellitus, coronary disease and certain cancers, including those of the breast and colon. There is a growing body of evidence that links phytochemicals with the inhibition of adipogenesis and protection against obesity. Mangoes (Mangifera indica L.) are tropical fruits that are rich in a diverse array of bioactive phytochemicals. In this study, methanol extracts of peel and flesh from three archetypal mango cultivars; Irwin, Nam Doc Mai and Kensington Pride, were assessed for their effects on a 3T3-L1 pre-adipocyte cell line model of adipogenesis. High content imaging was used to assess: lipid droplets per cell, lipid droplet area per cell, lipid droplet integrated intensity, nuclei count and nuclear area per cell. Mango flesh extracts from the three cultivars did not inhibit adipogenesis; peel extracts from both Irwin and Nam Doc Mai, however, did so with the Nam Doc Mai extract most potent at inhibiting adipogenesis. Peel extract from Kensington Pride promoted adipogenesis. The inhibition of adipogenesis by Irwin (100 mu g mL(-1)) and Nam Doc Mai peel extracts (50 and 100 mu g mL(-1)) was associated with an increase in the average nuclear area per cell; similar effects were seen with resveratrol, suggesting that these extracts may act through pathways similar to resveratrol. These results suggest that differences in the phytochemical composition between mango cultivars may influence their effectiveness in inhibiting adipogenesis, and points to mango fruit peel as a potential source of nutraceuticals.

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BACKGROUND: In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). RESULTS: The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks. CONCLUSION: Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia, in addition to various species of Acacia, it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks.

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Cuticular hydrocarbon components in beetles of six Australian melolonthines whose larvae damage sugarcane, Antitrogus parvulus (Britton), A. consanguineus (Blackburn), Lepidiota negatoria (Blackburn), L. picticollis (Lea), L. noxia (Britton) and Dermolepida alborhirtum (Arrow), are identified and compared. These species demonstrate species-specific cuticular hydrocarbon profiles with a number of unprecedented structures. Major components have been identified as polymethylated hydrocarbons, 3-methyl substituted n-alkanes, 9,10-allenes and the corresponding C9 alkenes. The similarity of these compounds shows some correlation with the phylogeny of the beetles, but two polymethylated C22 hydrocarbons are unique to A. parvulus. One C25 allene is shown to have a potential role in mate recognition in A. consanguineus.

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Prediction of the initiation, appearance and emergence of leaves is critically important to the success of simulation models of crop canopy development and some aspects of crop ontogeny. Data on leaf number and crop ontogeny were collected on five cultivars of maize differing widely in maturity and genetic background grown under natural and extended photoperiods, and planted on seven sowing dates from October 1993 to March 1994 at Gatton, South-east Queensland. The same temperature coefficients were established for crop ontogeny before silking, and the rates of leaf initiation, leaf tip appearance and full leaf expansion, the base, optimum and maximum temperatures for each being 8, 34 and 40 degrees C. After silking, the base temperature for ontogeny was 0 degrees C, but the optimum and maximum temperatures remained unchanged. The rates of leaf initiation, appearance of leaf tips and full leaf expansion varied in a relatively narrow range across sowing times and photoperiod treatments, with average values of 0.040 leaves (degrees Cd)-1, 0.021 leaves (degrees Cd)-1, and 0.019 leaves (degrees Cd)-1, respectively. The relationships developed in this study provided satisfactory predictions of leaf number and crop ontogeny (tassel initiation to silking, emergence to silking and silking to physiological maturity) when assessed using independent data from Gatton (South eastern Queensland), Katherine and Douglas Daly (Northern Territory), Walkamin (North Queensland) and Kununurra (Western Australia).

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Approximately 30% of plant nuclear genes appear to encode proteins targeted to the plastids or endoplasmic reticulum (ER). The signals that direct proteins into these compartments are diverse in sequence, but, on the basis of a limited number of tests in heterologous systems, they appear to be functionally conserved across species. To further test the generality of this conclusion, we tested the ability of two plastid transit peptides and an ER signal peptide to target green fluorescent protein (GFP) in 12 crops, including three monocots (barley, sugarcane, wheat) and nine dicots (Arabidopsis, broccoli, cabbage, carrot, cauliflower, lettuce, radish, tobacco, turnip). In all species, transient assays following microprojectile bombardment or vacuum infiltration using Agrobacterium showed that the plastid transit peptides from tomato DCL (defective chloroplast and leaves) and tobacco RbcS [ribulose bisphosphate carboxylase (Rubisco) small subunit] genes were effective in targeting GFP to the leaf plastids. GFP engineered as a fusion to the N-terminal ER signal peptide from Arabidopsis basic chitinase and a C-terminal HDEL signal for protein retention in the ER was accumulated in the ER of all species. The results in tobacco were confirmed in stably transformed cells. These signal sequences should be useful to direct proteins to the plastid stroma or ER lumen in diverse plant species of biotechnological interest for the accumulation of particular recombinant proteins or for the modification of particular metabolic streams.

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The original pasture ecosystems of southern inland Queensland ranged from treeless grasslands on cracking clays through grassy woodlands of varying density on a great range of soil types to those competing at the dynamic edges of forests and scrubs. Fire, both wild and aboriginal-managed, was a major factor, along with rainfall extremes, in shaping the pastures and tree:grass balance. Seedling recruitment was driven by rainfall extremes, availability of germinable seed and growing space, with seed availability and space being linked to the timing and intensity of recent fires and rain. The impact of insects, diseases, severe wind and hailstorms on recruitment should not be underestimated. The more fertile soils had denser grass growth, greater fire frequency and thinner tree cover than infertile soils, except where trees were so dense that grass growth was almost eliminated. The pastures were dominated by perennial tussock grasses of mid-height but included a wide array of minor herbaceous species whose abundance was linked to soil type and recent seasonal conditions. Many were strongly perennial with Asteraceae, Fabaceae, Malvaceae, Cyperaceae and Goodeniaceae most common in an environment, which can experience effective rainfall at any time of year. The former grassland communities that are now productive farming lands are not easily returned to their original composition. However, conservation of remnant examples of original pasture types is very achievable provided tree density is controlled, prescribed burning and grazing are used and rigorous control of invasive, exotic species is undertaken. This should be done with a clear understanding that significant short-and medium-term fluctuations in botanical composition are normal.

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Metal oxide semiconductor (MOS) sensors are a class of chemical sensor that have potential for being a practical core sensor module for an electronic nose system in various environmental monitoring applications. However, the responses of these sensors may be affected by changes in humidity and this must be taken into consideration when developing calibration models. This paper characterises the humidity dependence of a sensor array which consists of 12 MOS sensors. The results were used to develop calibration models using partial least squares. Effects of humidity on the response of the sensor array and predictive ability of partial least squares are discussed. It is shown that partial least squares can provide proper calibration models to compensate for effects caused by changes in humidity.

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Metal oxide semiconductor (MOS) sensors are a class of chemical sensors that have potential for being a practical core sensor module for an electronic nose system in various environmental monitoring applications. However, the responses of these sensors may be affected by changes in humidity and this must be taken into consideration when developing calibration models. This paper characterises the humidity dependence of a sensor array which consists of 12 MOS sensors. The results were used to develop calibration models using partial least squares (PLS). Effects of humidity on the response of the sensor array and predictive ability of partial least squares are discussed. It is shown that partial least squares can provide proper calibration models to compensate for effects caused by changes in humidity. Special Issue: Selected Paper from the 12th International Symposium on Olfaction and Electronic Noses - ISOEN 2007, International Symposium on Olfaction and Electronic Noses.

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The appropriate frequency and precision for surveys of wildlife populations represent a trade-off between survey cost and the risk of making suboptimal management decisions because of poor survey data. The commercial harvest of kangaroos is primarily regulated through annual quotas set as proportions of absolute estimates of population size. Stochastic models were used to explore the effects of varying precision, survey frequency and harvest rate on the risk of quasiextinction for an arid-zone and a more mesic-zone kangaroo population. Quasiextinction probability increases in a sigmoidal fashion as survey frequency is reduced. The risk is greater in more arid regions and is highly sensitive to harvest rate. An appropriate management regime involves regular surveys in the major harvest areas where harvest rate can be set close to the maximum sustained yield. Outside these areas, survey frequency can be reduced in relatively mesic areas and reduced in arid regions when combined with lowered harvest rates. Relative to other factors, quasiextinction risk is only affected by survey precision (standard error/mean × 100) when it is >50%, partly reflecting the safety of the strategy of harvesting a proportion of a population estimate.

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The sequential nature of gel-based marker systems entails low throughput and high costs per assay. Commonly used marker systems such as SSR and SNP are also dependent on sequence information. These limitations result in high cost per data point and significantly limit the capacity of breeding programs to obtain sufficient return on investment to justify the routine use of marker-assisted breeding for many traits and particularly quantitative traits. Diversity Arrays Technology (DArT™) is a cost effective hybridisation-based marker technology that offers a high multiplexing level while being independent of sequence information. This technology offers sorghum breeding programs an alternative approach to whole-genome profiling. We report on the development, application, mapping and utility of DArT™ markers for sorghum germplasm. Results: A genotyping array was developed representing approximately 12,000 genomic clones using PstI+BanII complexity with a subset of clones obtained through the suppression subtractive hybridisation (SSH) method. The genotyping array was used to analyse a diverse set of sorghum genotypes and screening a Recombinant Inbred Lines (RIL) mapping population. Over 500 markers detected variation among 90 accessions used in a diversity analysis. Cluster analysis discriminated well between all 90 genotypes. To confirm that the sorghum DArT markers behave in a Mendelian manner, we constructed a genetic linkage map for a cross between R931945-2-2 and IS 8525 integrating DArT and other marker types. In total, 596 markers could be placed on the integrated linkage map, which spanned 1431.6 cM. The genetic linkage map had an average marker density of 1/2.39 cM, with an average DArT marker density of 1/3.9 cM. Conclusion: We have successfully developed DArT markers for Sorghum bicolor and have demonstrated that DArT provides high quality markers that can be used for diversity analyses and to construct medium-density genetic linkage maps. The high number of DArT markers generated in a single assay not only provides a precise estimate of genetic relationships among genotypes, but also their even distribution over the genome offers real advantages for a range of molecular breeding and genomics applications.

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One of the pathways for transfer of cadmium (Cd) through the food chain is addition of urban wastewater solids (biosolids) to soil, and many countries have restrictions on biosolid use to minimize crop Cd contamination. The basis of these restrictions often lies in laboratory or glasshouse experimentation of soil-plant transfer of Cd, but these studies are confounded by artefacts from growing crops in controlled laboratory conditions. This study examined soil to plant (wheat grain) transfer of Cd under a wide range of field environments under typical agronomic conditions, and compared the solubility and bioavailability of Cd in biosolids to soluble Cd salts. Solubility of biosolid Cd (measured by examining Cd partitioning between soil and soil solution) was found to be equal to or greater than that of soluble Cd salts, possibly due to competing ions added with the biosolids. Conversely, bioavailability of Cd to wheat and transfer to grain was less than that of soluble Cd salts, possibly due to addition of Zn with the biosolids, causing reduced plant uptake or grain loading, or due to complexation of soluble Cd2+ by dissolved organic matter.

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The ability to predict phenology and canopy development is critical in crop models used for simulating likely consequences of alternative crop management and cultivar choice strategies. Here we quantify and contrast the temperature and photoperiod responses for phenology and canopy development of a diverse range of elite Indian and Australian sorghum genotypes (hybrid and landrace). Detailed field experiments were undertaken in Australia and India using a range of genotypes, sowing dates, and photoperiod extension treatments. Measurements of timing of developmental stages and leaf appearance were taken. The generality of photo-thermal approaches to modelling phenological and canopy development was tested. Environmental and genotypic effects on rate of progression from emergence to floral initiation (E-FI) were explained well using a multiplicative model, which combined the intrinsic development rate (Ropt), with responses to temperature and photoperiod. Differences in Ropt and extent of the photoperiod response explained most genotypic effects. Average leaf initiation rate (LIR), leaf appearance rate and duration of the phase from anthesis to physiological maturity differed among genotypes. The association of total leaf number (TLN) with photoperiod found for all genotypes could not be fully explained by effects on development and LIRs. While a putative effect of photoperiod on LIR would explain the observations, other possible confounding factors, such as air-soil temperature differential and the nature of model structure were considered and discussed. This study found a generally robust predictive capacity of photo-thermal development models across diverse ranges of both genotypes and environments. Hence, they remain the most appropriate models for simulation analysis of genotype-by-management scenarios in environments varying broadly in temperature and photoperiod.

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Identification of major contributors to odour annoyance in areas with multiple emission sources is necessary to address and resolve odour disputes. In an effort to develop an appropriate tool for this task, odour samples were collected on-site at a piggery and an abattoir (the major odour sources in the area) and at surrounding off-site areas, then analysed using a commercial non-specific chemical sensor array to develop an odour fingerprint database. The developed odour fingerprint database was analysed using two pattern recognition algorithms including a partial least squares-discriminant analysis (PLS-DA) and a Kohonen self-organising map (KSOM). The KSOM model could identify odour samples sourced from the piggery shed 15, piggery pond 8, piggery pond 9, abattoir, motel and others with mean percentage values of 77.5, 65.0, 90.2, 75.7, 44.8 and 64.6%, respectively.