969 resultados para corn rootworm


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Mycotoxicosis due to ingestion of zearalenone was detected on 2 pig farms on the Atherton Tableland in northern Queensland. In one herd of 200 pigs, this resulted from feeding maize which had been stored with a high moisture content. In the other herd of 1400 pigs, it resulted from feeding sorghum grain which was rain affected before harvest. Concentrations of zearalenone in the feeds ranged up to 8 mg/kg. Most prepubertal gilts in the herds displayed enlarged teats and signs of oestrus such as having red, swollen vulvas. In several cases both rectal and vaginal prolapses occurred. On one of the farms, 25 pigs died as a direct result of prolapses. Autopsy of a 3-monthold gilt revealed apparently enlarged ovaries and uterine horns. Sows and boars seemed to be unaffected. Four gilts failed to conceive following mating during the period of zearalenone ingestion, but apart from this and the deaths from prolapses, production of the herds appeared ti be unaffected.

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We have characterised six Australian Cucumber mosaic virus (CMV) strains belonging to different subgroups, determined by the sequence of their complete RNA 3 and by their host range and the symptoms they cause on species in the Solanaceae, Cucurbitaceae and on sweet corn. These data allowed classification of strains into the known three CMV subgroups and identification of plant species able to differentiate the Australian strains by symptoms and host range. Western Australian strains 237 and Twa and Queensland strains 207 and 242 are closely related members of CMV subgroup IA, which cause similar severe symptoms on Nicotiana species. Strains 207 and 237 (subgroup IA) were the only strains tested which systemically infected sweet corn. Strain 243 caused the most severe symptoms of all strains on Nicotiana species, tomato and capsicum and appears to be the first confirmed subgroup IB strain reported in Australia. Based on pair-wise distance analysis and phylogeny of RNA 3, as well as mild disease symptoms on Nicotiana species, CMV 241 was assigned to subgroup II, as the previously described Q-CMV and LY-CMV.

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Large larval populations of the scarabaeid beetle Heteronyx piceus Blanchard that occur under peanuts, but not maize, in the South Burnett region of Australia are the result of a high rate and prolonged period of egg production by females feeding on peanut foliage. Heteronyx piceus is a relatively sedentary species and movement of females between adjacent fields is low. Populations of H. piceus varied markedly with landscape position. High larval populations are more likely (1 in 4 chance) to be encountered on the ‘scrub’ soils in the upper parts of the landscape than in the ‘forest’ soils in the lower half (1 in 20 chance), indicating that soil type/landscape position is a key risk factor in assessing the need for management intervention. The studies indicate that, because of the species' sedentary nature, the most meaningful population entity for management of H. piceus is the individual field, rather than the whole-farm or the region. The implications of this population ecology for management of the pest are discussed in relation to control strategies.

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Australian researchers have been developing robust yield estimation models, based mainly on the crop growth response to water availability during the crop season. However, knowledge of spatial distribution of yields within and across the production regions can be improved by the use of remote sensing techniques. Images of Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices, available since 1999, have the potential to contribute to crop yield estimation. The objective of this study was to analyse the relationship between winter crop yields and the spectral information available in MODIS vegetation index images at the shire level. The study was carried out in the Jondaryan and Pittsworth shires, Queensland , Australia . Five years (2000 to 2004) of 250m resolution, 16-day composite of MODIS Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) images were used during the winter crop season (April to November). Seasonal variability of the profiles of the vegetation index images for each crop season using different regions of interest (cropping mask) were displayed and analysed. Correlation analysis between wheat and barley yield data and MODIS image values were also conducted. The results showed high seasonal variability in the NDVI and EVI profiles, and the EVI values were consistently lower than those of the NDVI. The highest image values were observed in 2003 (in contrast to 2004), and were associated with rainfall amount and distribution. The seasonal variability of the profiles was similar in both shires, with minimum values in June and maximum values at the end of August. NDVI and EVI images showed sensitivity to seasonal variability of the vegetation and exhibited good association (e.g. r = 0.84, r = 0.77) with winter crop yields.

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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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Physiological and genetic studies of leaf growth often focus on short-term responses, leaving a gap to whole-plant models that predict biomass accumulation, transpiration and yield at crop scale. To bridge this gap, we developed a model that combines an existing model of leaf 6 expansion in response to short-term environmental variations with a model coordinating the development of all leaves of a plant. The latter was based on: (1) rates of leaf initiation, appearance and end of elongation measured in field experiments; and (2) the hypothesis of an independence of the growth between leaves. The resulting whole-plant leaf model was integrated into the generic crop model APSIM which provided dynamic feedback of environmental conditions to the leaf model and allowed simulation of crop growth at canopy level. The model was tested in 12 field situations with contrasting temperature, evaporative demand and soil water status. In observed and simulated data, high evaporative demand reduced leaf area at the whole-plant level, and short water deficits affected only leaves developing during the stress, either visible or still hidden in the whorl. The model adequately simulated whole-plant profiles of leaf area with a single set of parameters that applied to the same hybrid in all experiments. It was also suitable to predict biomass accumulation and yield of a similar hybrid grown in different conditions. This model extends to field conditions existing knowledge of the environmental controls of leaf elongation, and can be used to simulate how their genetic controls flow through to yield.

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Laboratory experiments were conducted to determine the efficacy of spinosad (a biopesticide), chlorpyrifos-methyl (an organophosphorus compound (OP)) and s-methoprene (a juvenile hormone analogue) applied alone and in binary combinations against five stored-grain beetles in wheat. There were three strains of Rhyzopertha dominica, and one strain each of Sitophilus oryzae, Tribolium castaneum, Oryzaephilus surinamensis and Cryptolestes ferrugineus. These strains were chosen to represent a range of possible resistant genotypes, exhibiting resistance to organophosphates, pyrethroids or methoprene. Treatments were applied at rates that are registered or likely to be registered in Australia. Adults were exposed to freshly treated wheat for 2 weeks, and the effects of treatments on mortality and reproduction were determined. No single protectant or protectant combination controlled all insect strains, based on the criterion of >99% reduction in the number of live F1 adults relative to the control. The most effective combinations were spinosad at 1 mg kg-1+chlorpyrifos-methyl at 10 mg kg-1 which controlled all strains except for OP-resistant O. surinamensis, and chlorpyrifos-methyl at 10 mg kg-1+s-methoprene at 0.6 mg kg-1 which controlled all strains except for methoprene-resistant R. dominica. The results of this study demonstrate the difficulty in Australia, and potentially other countries which use protectants, of finding protectant treatments to control a broad range of pest species in the face of resistance development.

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Weighing lysimeters are the standard method for directly measuring evapotranspiration (ET). This paper discusses the construction, installation, and performance of two (1.52 m × 1.52 m × 2.13-m deep) repacked weighing lysimeters for measuring ET of corn and soybean in West Central Nebraska. The cost of constructing and installing each lysimeter was approximately US $12,500, which could vary depending on the availability and cost of equipment and labor. The resolution of the lysimeters was 0.0001 mV V-1, which was limited by the data processing and storage resolution of the datalogger. This resolution was equivalent to 0.064 and 0.078 mm of ET for the north and south lysimeters, respectively. Since the percent measurement error decreases with the magnitude of the ET measured, this resolution is adequate for measuring ET for daily and longer periods, but not for shorter time steps. This resolution would result in measurement errors of less than 5% for measuring ET values of ≥3 mm, but the percent error rapidly increases for lower ET values. The resolution of the lysimeters could potentially be improved by choosing a datalogger that could process and store data with a higher resolution than the one used in this study.

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Compared to grain sorghums, sweet sorghums typically have lower grain yield and thick, tall stalks which accumulate high levels of sugar (sucrose, fructose and glucose). Unlike commercial grain sorghum (S. bicolor ssp. bicolor) cultivars, which are usually F1 hybrids, commercial sweet sorghums were selected as wild accessions or have undergone limited plant breeding. Although all sweet sorghums are classified within S. bicolor ssp. bicolor, their genetic relationship with grain sorghums is yet to be investigated. Ninety-five genotypes, including 31 sweet sorghums and 64 grain sorghums, representing all five races within the subspecies bicolor, were screened with 277 polymorphic amplified fragment length polymorphism (AFLP) markers. Cluster analysis separated older sweet sorghum accessions (collected in mid 1800s) from those developed and released during the early to mid 1900s. These groups were emphasised in a principle component analysis of the results such that sweet sorghum lines were largely distinguished from the others, particularly by a group of markers located on sorghum chromosomes SBI-08 and SBI-10. Other studies have shown that QTL and ESTs for sugar-related traits, as well as for height and anthesis, map to SBI-10. Although the clusters obtained did not group clearly on the basis of racial classification, the sweet sorghum lines often cluster with grain sorghums of similar racial origin thus suggesting that sweet sorghum is of polyphyletic origin within S. bicolor ssp. bicolor.

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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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Aflatoxins are highly carcinogenic mycotoxins produced by two fungi, Aspergillus flavus and A. parasiticus, under specific moisture and temperature conditions before harvest and/or during storage of a wide range of crops including maize. Modelling of interactions between host plant and environment during the season can enable quantification of preharvest aflatoxin risk and its potential management. A model was developed to quantify climatic risks of aflatoxin contamination in maize using principles previously used for peanuts. The model outputs an aflatoxin risk index in response to seasonal temperature and soil moisture during the maize grain filling period using the APSIM's maize module. The model performed well in simulating climatic risk of aflatoxin contamination in maize as indicated by a significant R2 (P ≤ 0.01) between aflatoxin risk index and the measured aflatoxin B1 in crop samples, which was 0.69 for a range of rainfed Australian locations and 0.62 when irrigated locations were also included in the analysis. The model was further applied to determine probabilities of exceeding a given aflatoxin risk in four non-irrigated maize growing locations of Queensland using 106 years of historical climatic data. Locations with both dry and hot climates had a much higher probability of higher aflatoxin risk compared with locations having either dry or hot conditions alone. Scenario analysis suggested that under non-irrigated conditions the risk of aflatoxin contamination could be minimised by adjusting sowing time or selecting an appropriate hybrid to better match the grain filling period to coincide with lower temperature and water stress conditions.

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Recent incidents of mycotoxin contamination (particularly aflatoxins and fumonisins) have demonstrated a need for an industry-wide management system to ensure Australian maize meets the requirements of all domestic users and export markets. Results of recent surveys are presented, demonstrating overall good conformity with nationally accepted industry marketing standards but with occasional samples exceeding these levels. This paper describes mycotoxin-related hazards inherent in the Australian maize production system and a methodology combining good agricultural practices and the hazard analysis critical control point framework to manage risk.

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Mycotoxin contamination of Australian maize is neither common nor extensive, but has the capacity to seriously disrupt marketing. Low to moderate levels of aflatoxins and fumonisins can be widespread in some seasons, but zearalenone, nivalenol and deoxynivalenol are usually confined to small growing localities. Possible approaches to such situations were tested by an analysis of several case studies. It is concluded that communication and coordination across the industry, prediction and prevention of contamination, rapid detection and assessment of contamination, effective use of contaminated maize and breeding for resistance comprise a useful set of strategies for managing mycotoxins in maize.

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Two field experiments using maize (Pioneer 31H50) and three watering regimes [(i) irrigated for the whole crop cycle, until anthesis, (ii) not at all (experiment 1) and (iii) fully irrigated and rain grown for the whole crop cycle (experiment 2)] were conducted at Gatton, Australia, during the 2003-04 season. Data on crop ontogeny, leaf, sheath and internode lengths and leaf width, and senescence were collected at 1- to 3-day intervals. A glasshouse experiment during 2003 quantified the responses of leaf shape and leaf presentation to various levels of water stress. Data from experiment 1 were used to modify and parameterise an architectural model of maize (ADEL-Maize) to incorporate the impact of water stress on maize canopy characteristics. The modified model produced accurate fitted values for experiment 1 for final leaf area and plant height, but values during development for leaf area were lower than observed data. Crop duration was reasonably well fitted and differences between the fully irrigated and rain-grown crops were accurately predicted. Final representations of maize crop canopies were realistic. Possible explanations for low values of leaf area are provided. The model requires further development using data from the glasshouse study and before being validated using data from experiment 2 and other independent data. It will then be used to extend functionality in architectural models of maize. With further research and development, the model should be particularly useful in examining the response of maize production to water stress including improved prediction of total biomass and grain yield. This will facilitate improved simulation of plant growth and development processes allowing investigation of genotype by environment interactions under conditions of suboptimal water supply.