68 resultados para Multivariate unit root tests

em eResearch Archive - Queensland Department of Agriculture


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A concentration as low as 1 μM lead (Pb) is highly toxic to plants, but previous studies have typically related plant growth to the total amount of Pb added to a solution. In the present experiment, the relative fresh mass of cowpea (Vigna unguiculata) was reduced by 10% at a Pb2+ activity of 0.2 μM for the shoots and at a Pb2+ activity of 0.06 μM for the roots. The primary site of Pb2+ toxicity was the root, causing severe reductions in root growth, loss of apical dominance (shown by an increase in branching per unit root length), the formation of localized swellings behind the root tips (due to the initiation of lateral roots), and the bending of some root tips. In the root, Pb was found to accumulate primarily within the cell walls and intercellular spaces.

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Brassicaceae plants have the potential as part of an integrated approach to replace fumigant nematicides, providing the biofumigation response following their incorporation is not offset by reproduction of plant-parasitic nematodes on their roots. Forty-three Brassicaceae cultivars were screened in a pot trial for their ability to reduce reproduction of three root-knot nematode isolates from north Queensland, Australia: M. arenaria (NQ1), M. javanica (NQ2) and M. arenaria race 2 (NQ5/7). No cultivar was found to consistently reduce nematode reproduction relative to forage sorghum, the current industry standard, although a commercial fodder radish (Raphanus sativus) and a white mustard (Sinapis alba) line were consistently as resistant to the formation of galls as forage sorghum. A second pot trial screened five commercially available Brassicaceae cultivars, selected for their biofumigation potential, for resistance to two nematode species, M. javanica (NQ2) and M. arenaria (NQ5/7). The fodder radish cv. Weedcheck, was found to be as resistant as forage sorghum to nematode reproduction. A multivariate cluster analysis using the resistance measurements, gall index, nematode number per g of root and multiplication for two nematode species (NQ2 and NQ5/7) confirmed the similarity in resistance between the radish cultivar and forage sorghum. A field trial confirmed the resistance of the fodder radish cv. Weedcheck, with a similar reduction in the number of Meloidogyne spp. juveniles recovered from the roots 8 weeks after planting. The use of fodder radish cultivars as biofumigation crops to manage root-knot nematodes in tropical vegetable production systems deserves further investigation.

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The use of near infrared (NIR) hyperspectral imaging and hyperspectral image analysis for distinguishing between hard, intermediate and soft maize kernels from inbred lines was evaluated. NIR hyperspectral images of two sets (12 and 24 kernels) of whole maize kernels were acquired using a Spectral Dimensions MatrixNIR camera with a spectral range of 960-1662 nm and a sisuChema SWIR (short wave infrared) hyperspectral pushbroom imaging system with a spectral range of 1000-2498 nm. Exploratory principal component analysis (PCA) was used on absorbance images to remove background, bad pixels and shading. On the cleaned images. PCA could be used effectively to find histological classes including glassy (hard) and floury (soft) endosperm. PCA illustrated a distinct difference between glassy and floury endosperm along principal component (PC) three on the MatrixNIR and PC two on the sisuChema with two distinguishable clusters. Subsequently partial least squares discriminant analysis (PLS-DA) was applied to build a classification model. The PLS-DA model from the MatrixNIR image (12 kernels) resulted in root mean square error of prediction (RMSEP) value of 0.18. This was repeated on the MatrixNIR image of the 24 kernels which resulted in RMSEP of 0.18. The sisuChema image yielded RMSEP value of 0.29. The reproducible results obtained with the different data sets indicate that the method proposed in this paper has a real potential for future classification uses.

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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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This manual identifies simple, practical tests to measure soil health and outlines the use of an on-farm testing kit to perform these tests. This testing is designed so that banana producers or agricultural consultants can asses or monitor the health of the soil inexpensively and without the need for a laboratory.

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Loss of nitrogen in deep drainage from agriculture is an important issue for environmental and economic reasons, but limited field data is available for tropical crops. In this study, nitrogen (N) loads leaving the root zone of two major humid tropical crops in Australia, sugarcane and bananas, were measured. The two field sites, 57 km apart, had a similar soil type (a well drained Dermosol) and rainfall (∼2700 mm year -1) but contrasting crops and management. A sugarcane crop in a commercial field received 136-148 kg N ha -1 year -1 applied in one application each year and was monitored for 3 years (first to third ratoon crops). N treatments of 0-600 kg ha -1 year -1 were applied to a plant and following ratoon crop of bananas. N was applied as urea throughout the growing season in irrigation water through mini-sprinklers. Low-suction lysimeters were installed at a depth of 1 m under both crops to monitor loads of N in deep drainage. Drainage at 1 m depth in the sugarcane crops was 22-37% of rainfall. Under bananas, drainage in the row was 65% of rainfall plus irrigation for the plant crop, and 37% for the ratoon. Nitrogen leaching loads were low under sugarcane (<1-9 kg ha -1 year -1) possibly reflecting the N fertiliser applications being reasonably matched to crop requirements and at least 26 days between fertiliser application and deep drainage. Under bananas, there were large loads of N in deep drainage when N application rates were in excess of plant demand, even when applied fortnightly. The deep drainage loss of N attributable to N fertiliser, calculated by subtracting the loss from unfertilised plots, was 246 and 641 kg ha -1 over 2 crop cycles, which was equivalent to 37 and 63% of the fertiliser application for treatments receiving 710 and 1065 kg ha -1, respectively. Those rates of fertiliser application resulted in soil acidification to a depth of 0.6 m by as much as 0.6 of a unit at 0.1-0.2 m depth. The higher leaching losses from bananas indicated that they should be a priority for improved N management. Crown Copyright © 2012.

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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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The inheritance of resistance to root-lesion nematode was investigated in five synthetic hexaploid wheat lines and two bread wheat lines using a half-diallel design of F1 and F2 crosses. The combining ability of resistance genes in the synthetic hexaploid wheat lines was compared with the performance of the bread wheat line 'GS50a', the source of resistance to Pratylenchus thornei used in Australian wheat breeding programmes. Replicated glasshouse trials identified P. thornei resistance as polygenic and additive in gene action. General combining ability (GCA) of the parents was more important than specific combining ability (SCA) effects in the inheritance of P. thornei resistance in both F1 and F2 populations. The synthetic hexaploid wheat line 'CPI133872' was identified as the best general combiner, however, all five synthetic hexaploid wheat lines possessed better GCA than 'GS50a'. The synthetic hexaploid wheat lines contain novel sources of P. thornei resistance that will provide alternative and more effective sources of resistance to be utilized in wheat breeding programmes

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Rhizoctonia solani AG-2-2 was isolated from wilting and dying plants of sulla (Hedysarum coronarium), which is currently being assessed in eastern and southern Australia for its potential as a pasture and forage legume. Infected plants in the field had extensive rotting of the taproot, lateral roots and crown. Koch's postulates were fulfilled using three inoculation methods. The disease may pose a considerable threat to the potential use of H. coronarium in the dryland, grazing farming systems of Australia, with resistance offering the most viable option for minimising its impact.

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The robustness of multivariate calibration models, based on near infrared spectroscopy, for the assessment of total soluble solids (TSS) and dry matter (DM) of intact mandarin fruit (Citrus reticulata cv. Imperial) was assessed. TSS calibration model performance was validated in terms of prediction of populations of fruit not in the original population (different harvest days from a single tree, different harvest localities, different harvest seasons). Of these, calibration performance was most affected by validation across seasons (signal to noise statistic on root mean squared error of prediction of 3.8, compared with 20 and 13 for locality and harvest day, respectively). Procedures for sample selection from the validation population for addition to the calibration population (‘model updating’) were considered for both TSS and DM models. Random selection from the validation group worked as well as more sophisticated selection procedures, with approximately 20 samples required. Models that were developed using samples at a range of temperatures were robust in validation for TSS and DM.

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Strawberry runner production areas in Queensland are assessed for the presence of Pratylenchus vulnus (lesion nematode) and Meloidogyne hapla (root-knot nematode) as part of the approval process for sites used in runner production under the approved runner scheme. M. hapla is known to infest strawberry. The ability of three other Meloidogyne species occurring in Queensland to infest this host was investigated. The species M. arenaria, M. incognita and M. javanica, in addition to M. hapla, were able to reproduce on strawberry roots of the cultivar 'Joy', which sustained higher nematode reproduction rates than 'Jewel' and 'Sweet Charlie'. The ability of species other than M. hapla to infest strawberry needs to be recognised in site selection for runner production, and in screening cultivars for resistance to nematodes.

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In recent years, there have been significant developments in climate science relevant to agriculture and natural resource management. Assessing impacts of climate variability and use of seasonal climate forecasts have become increasingly important elements in the management "toolkit" for many Australian farmers. Consideration of climate change further increases the need for improved management strategies. While climate risk extension activities have kept pace with advances in climate science, a national review of the Vocational Education and Training system in Australia in relation to "weather and climate" showed that these topics were "poorly represented" at the management level in the Australian Qualifications Framework, and needed increased emphasis. Consequently, a new Unit of Competency concerning management of climatic risk was developed and accredited to address this deficiency. The objective of the unit was to build knowledge and skills for better management of climate variability via the elements of surveying climatic and enterprise data; analysing climatic risks and opportunities; and developing climatic risk management strategies. This paper describes establishment of a new unit for vocational education that is designed to harness recent developments in applied climate science for better management of Australia's highly variable climate. The main benefits of the new unit of competency, "Developing climatic risk management strategies,"were seen as improving decisions in climate and agriculture, and reducing climate risk exposure to enhance sustainable agriculture. The educational unit is now within the scope of agricultural colleges, universities, and registered training organisations as an accredited unit.

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Two species of root-lesion nematode (predominantly Pratylenchus thornei but also P. neglectus) are widespread pathogens of wheat and other crops in Australia's northern grain belt, a subtropical region with deep, fertile clay soils and a summer-dominant rainfall pattern. Losses in grain yield from P. thornei can be as high as 70% for intolerant wheat cultivars. This review focuses on research which has led to the development of effective integrated management programs for these nematodes. It highlights the importance of correct identification in managing Pratylenchus species, reviews the plant breeding work done in developing tolerant and resistant cultivars, outlines the methods used to screen for tolerance and resistance, and discusses how planned crop sequencing with tolerant and partially resistant wheat cultivars, together with crops such as sorghum, sunflower, millets and canaryseed, can be used to reduce nematode populations and limit crop damage. The declining levels of soil organic matter in cropped soils are also discussed with reference to their effect on soil health and biological suppression of root-lesion nematodes.

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Background: Plotless density estimators are those that are based on distance measures rather than counts per unit area (quadrats or plots) to estimate the density of some usually stationary event, e.g. burrow openings, damage to plant stems, etc. These estimators typically use distance measures between events and from random points to events to derive an estimate of density. The error and bias of these estimators for the various spatial patterns found in nature have been examined using simulated populations only. In this study we investigated eight plotless density estimators to determine which were robust across a wide range of data sets from fully mapped field sites. They covered a wide range of situations including animal damage to rice and corn, nest locations, active rodent burrows and distribution of plants. Monte Carlo simulations were applied to sample the data sets, and in all cases the error of the estimate (measured as relative root mean square error) was reduced with increasing sample size. The method of calculation and ease of use in the field were also used to judge the usefulness of the estimator. Estimators were evaluated in their original published forms, although the variable area transect (VAT) and ordered distance methods have been the subjects of optimization studies. Results: An estimator that was a compound of three basic distance estimators was found to be robust across all spatial patterns for sample sizes of 25 or greater. The same field methodology can be used either with the basic distance formula or the formula used with the Kendall-Moran estimator in which case a reduction in error may be gained for sample sizes less than 25, however, there is no improvement for larger sample sizes. The variable area transect (VAT) method performed moderately well, is easy to use in the field, and its calculations easy to undertake. Conclusion: Plotless density estimators can provide an estimate of density in situations where it would not be practical to layout a plot or quadrat and can in many cases reduce the workload in the field.

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Root system characteristics are of fundamental importance to soil exploration and below-ground resource acquisition. Root architectural traits determine the in situ space-filling properties of a root system or root architecture. The growth angle of root axes is a principal component of root system architecture that has been strongly associated with acquisition efficiency in many crop species. The aims of this study were to examine the extent of genotypic variability for the growth angle and number of seminal roots in 27 current Australian and 3 CIMMYT wheat (Triticum aestivum L.) genotypes, and to quantify using fractal analysis the root system architecture of a subset of wheat genotypes contrasting in drought tolerance and seminal root characteristics. The growth angle and number of seminal roots showed significant genotypic variation among the wheat genotypes with values ranging from 36 to 56 (degrees) and 3 to 5 (plant-1), respectively. Cluster analysis of wheat genotypes based on similarity in their seminal root characteristics resulted in four groups. The group composition reflected to some extent the genetic background and environmental adaptation of genotypes. Wheat cultivars grown widely in the Mediterranean environments of southern and western Australia generally had wider growth angle and lower number of seminal axes. In contrast, cultivars with superior performance on deep clay soils in the northern cropping region, such as SeriM82, Baxter, Babax, and Dharwar Dry exhibited a narrower angle of seminal axes. The wheat genotypes also showed significant variation in fractal dimension (D). The D values calculated for the individual segments of each root system suggested that, compared to the standard cultivar Hartog, the drought-tolerant genotypes adapted to the northern region tended to distribute relatively more roots in the soil volume directly underneath the plant. These findings suggest that wheat root system architecture is closely linked to the angle of seminal root axes at the seedling stage. The implications of genotypic variation in the seminal root characteristics and fractal dimension for specific adaptation to drought environment types are discussed with emphasis on the possible exploitation of root architectural traits in breeding for improved wheat cultivars for water-limited environments.