A sampling technique for two-spotted mite in papaya

Two-spotted mite, Tetranychus urticae Koch, was until recently regarded as a minor and infrequent pest of papaya in Queensland through the dry late winter/early summer months. The situation has changed over the past 4-5 years, so that now some growers consider spider mites significant pests all year round. This altered pest status corresponded with a substantial increase in the use of fungicides to control black spot (Asperisporium caricae). A project was initiated in 1998 to examine the potential reasons for escalating mite problems in commercially-grown papaya, which included regular sampling over a 2 year period for mites, mite damage and beneficial arthropods on a number of farms on the wet tropical coast and drier Atherton Tableland. Differences in soil type, papaya variety, chemical use and some agronomic practices were included in this assessment. Monthly visits were made to each site where 20 randomly-selected plants from each of 2 papaya lines (yellow and red types) were surveyed. Three leaves were selected from each plant, one from each of the bottom, middle and top strata of leaves. The numbers of mobile predators were recorded, along with visual estimates of the percentage and age of mite damage on each leaf. Leaves were then sprayed with hairspray to fix the mites and immature predators to the leaf surface. Four leaf disks, 25 mm in diameter, were then punched from each leaf into a 50 ml storage container with a purpose-built disk-cutting tool. Disks from each leaf position were separated by tissue paper, within the container. On return to the laboratory, each leaf disk was scrutinised under a binocular microscope to determine the numbers of two-spotted mites and eggs, predatory mites and eggs, and the immature stages of predatory insects (mainly Stethorus, Halmus and lacewings). A total of 2160 leaf disks have been examined each month. All data have been entered into an Access database to facilitate comparisons between sites.

Observations on the influence of repeated sampling procedures on temperament changes of weaner cattle

Experimental cattle are often restrained for repeated blood collection and faecal sampling and may baulk at entering the crush, possibly from learning that crush entry is followed by an unpleasant experience. We asked whether repeated sampling affects temperament. One measure of temperament is flight speed, which is the time, measured electronically, for an animal to cover a set distance on release from a weighing crate (Burrow et al. 1988). 22nd Biennial Conference.

Sampling and management of Bemisia tabaci (Genn.) biotype B in Australian cotton

Data on seasonal population abundance of Bemisia tabaci biotype B (silverleaf whitefly (SLW)) in Australian cotton fields collected over four consecutive growing seasons (2002/2003-2005/2006) were used to develop and validate a multiple-threshold-based management and sampling plan. Non-linear growth trajectories estimated from the field sampling data were used as benchmarks to classify adult SLW field populations into six density-based management zones with associated control recommendations in the context of peak flowering and open boll crop growth stages. Control options based on application of insect growth regulators (IGRs) are recommended for high-density populations (>2 adults/leaf) whereas conventional (non-IGR) products are recommended for the control of low to moderate population densities. A computerised re-sampling program was used to develop and test a binomial sampling plan. Binomial models with thresholds of T=1, 2 and 3 adults/leaf were tested using the field abundance data. A binomial plan based on a tally threshold of T=2 adults/leaf and a minimum sample of 20 leaves at nodes 3, 4 or 5 below the terminal is recommended as the most parsimonious and practical sampling protocol for Australian cotton fields. A decision support guide with management zone boundaries expressed as binomial counts and control options appropriate for various SLW density situations is presented. Appropriate use of chemical insecticides and tactics for successful field control of whiteflies are discussed.

Comparison of sampling sites and detection methods for Haemophilus parasuis

Objective To improve the isolation rate and identification procedures for Haemophilus parasuis from pig tissues. Design Thirteen sampling sites and up to three methods were used to confirm the presence of H. parasuis in pigs after experimental challenge. Procedure Colostrum-deprived, naturally farrowed pigs were challenged intratracheally with H parasuis serovar 12 or 4. Samples taken during necropsy were either inoculated onto culture plates, processed directly for PCR or enriched prior to being processed for PCR. The recovery of H parasuis from different sampling sites and using different sampling methods was compared for each serovar. Results H parasuis was recovered from several sample sites for all serovar 12 challenged pigs, while the trachea was the only positive site for all pigs following serovar 4 challenge. The method of solid medium culture of swabs, and confirmation of the identity of cultured bacteria by PCR, resulted in 38% and 14% more positive results on a site basis for serovars 12 and 4, retrospectively, than direct PCR on the swabs. This difference was significant in the serovar 12 challenge. Conclusion Conventional culture proved to be more effective in detecting H parasuis than direct PCR or PCR on enrichment broths. For subacute (serovar 4) infections, the most successful sites for culture or direct PCR were pleural fluid, peritoneal fibrin and fluid, lung and pericardial fluid. For acute (serovar 12) infections, the best sites were lung, heart blood, affected joints and brain. The methodologies and key sampling sites identified in this study will enable improved isolation of H parasuis and aid the diagnosis of Glässer's disease.

Temporal variation in arthropod sampling effectiveness: The case for using the beat sheet method in cotton

Predatory insects and spiders are key elements of integrated pest management (IPM) programmes in agricultural crops such as cotton. Management decisions in IPM programmes should to be based on a reliable and efficient method for counting both predators and pests. Knowledge of the temporal constraints that influence sampling is required because arthropod abundance estimates are likely to vary over a growing season and within a day. Few studies have adequately quantified this effect using the beat sheet, a potentially important sampling method. We compared the commonly used methods of suction and visual sampling to the beat sheet, with reference to an absolute cage clamp method for determining the abundance of various arthropod taxa over 5 weeks. There were significantly more entomophagous arthropods recorded using the beat sheet and cage clamp methods than by using suction or visual sampling, and these differences were more pronounced as the plants grew. In a second trial, relative estimates of entomophagous and phytophagous arthropod abundance were made using beat sheet samples collected over a day. Beat sheet estimates of the abundance of only eight of the 43 taxa examined were found to vary significantly over a day. Beat sheet sampling is recommended in further studies of arthropod abundance in cotton, but researchers and pest management advisors should bear in mind the time of season and time of day effects.

A comparison of mark-recapture distance-sampling methods applied to aerial surveys of eastern grey kangaroos

Aerial surveys of kangaroos (Macropus spp.) in Queensland are used to make economically important judgements on the levels of viable commercial harvest. Previous analysis methods for aerial kangaroo surveys have used both mark-recapture methodologies and conventional distance-sampling analyses. Conventional distance sampling has the disadvantage that detection is assumed to be perfect on the transect line, while mark-recapture methods are notoriously sensitive to problems with unmodelled heterogeneity in capture probabilities. We introduce three methodologies for combining together mark-recapture and distance-sampling data, aimed at exploiting the strengths of both methodologies and overcoming the weaknesses. Of these methods, two are based on the assumption of full independence between observers in the mark-recapture component, and this appears to introduce more bias in density estimation than it resolves through allowing uncertain trackline detection. Both of these methods give lower density estimates than conventional distance sampling, indicating a clear failure of the independence assumption. The third method, termed point independence, appears to perform very well, giving credible density estimates and good properties in terms of goodness-of-fit and percentage coefficient of variation. Estimated densities of eastern grey kangaroos range from 21 to 36 individuals km-2, with estimated coefficients of variation between 11% and 14% and estimated trackline detection probabilities primarily between 0.7 and 0.9.

Odour sampling 1: Physical chemistry considerations

The selection of an odour sampling device may influence the composition of the resulting odour sample. Limited comparison of emission rates derived from turbulent and essentially quiescent sampling devices confirms that the emission rates derived from these devices are quite different. There is therefore compelling evidence that current odour sampling practice should have greater regard for fundamental physical and chemical principles, the nature of the odour source and the conditions created by the sampling device. Such consideration may identify the most appropriate situations under which the use of these devices may or may not be correct.

Odour sampling. 2. Comparison of physical and aerodynamic characteristics of sampling devices: A review

Sampling devices differing greatly in shape, size and operating condition have been used to collect air samples to determine rates of emission of volatile substances, including odour. However, physical chemistry principles, in particular the partitioning of volatile substances between two phases as explained by Henrys Law and the relationship between wind velocity and emission rate, suggests that different devices cannot be expected to provide equivalent emission rate estimates. Thus several problems are associated with the use of static and dynamic emission chambers, but the more turbulent devices such as wind tunnels do not appear to be subject to these problems. In general, the ability to relate emission rate estimates obtained from wind tunnel measurements to those derived from device-independent techniques supports the use of wind tunnels to determine emission rates that can be used as input data for dispersion models.

Comparison of odour emission rates measured from various sources using two sampling devices

Two commonly used sampling devices (a wind tunnel and the US EPA dynamic emission chamber), were used to collect paired samples of odorous air from a number of agricultural odour sources. The odour samples were assessed using triangular, forced-choice dynamic olfactometry. The odour concentration data was combined with the flushing rate data to calculate odour emission rates for both devices on all sources. Odour concentrations were consistently higher in samples collected with a flux chamber (ratio ranging from 10:7 to 5:1, relative to wind tunnel samples), whereas odour emission rates were consistently larger when derived from wind tunnels (ratio ranging from 60:1 to 240:1, relative to flux chamber values). A complex relationship existed between emission rate estimates derived from each device, apparently influenced by the nature of the emitting surface. These results have great significance for users of odour dispersion models, for which an odour emission rate is a key input parameter.

Estimating crop area using seasonal time series of enhanced vegetation index from MODIS satellite imagery

Cereal grain is one of the main export commodities of Australian agriculture. Over the past decade, crop yield forecasts for wheat and sorghum have shown appreciable utility for industry planning at shire, state, and national scales. There is now an increasing drive from industry for more accurate and cost-effective crop production forecasts. In order to generate production estimates, accurate crop area estimates are needed by the end of the cropping season. Multivariate methods for analysing remotely sensed Enhanced Vegetation Index (EVI) from 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery within the cropping period (i.e. April-November) were investigated to estimate crop area for wheat, barley, chickpea, and total winter cropped area for a case study region in NE Australia. Each pixel classification method was trained on ground truth data collected from the study region. Three approaches to pixel classification were examined: (i) cluster analysis of trajectories of EVI values from consecutive multi-date imagery during the crop growth period; (ii) harmonic analysis of the time series (HANTS) of the EVI values; and (iii) principal component analysis (PCA) of the time series of EVI values. Images classified using these three approaches were compared with each other, and with a classification based on the single MODIS image taken at peak EVI. Imagery for the 2003 and 2004 seasons was used to assess the ability of the methods to determine wheat, barley, chickpea, and total cropped area estimates. The accuracy at pixel scale was determined by the percent correct classification metric by contrasting all pixel scale samples with independent pixel observations. At a shire level, aggregated total crop area estimates were compared with surveyed estimates. All multi-temporal methods showed significant overall capability to estimate total winter crop area. There was high accuracy at pixel scale (>98% correct classification) for identifying overall winter cropping. However, discrimination among crops was less accurate. Although the use of single-date EVI data produced high accuracy for estimates of wheat area at shire scale, the result contradicted the poor pixel-scale accuracy associated with this approach, due to fortuitous compensating errors. Further studies are needed to extrapolate the multi-temporal approaches to other geographical areas and to improve the lead time for deriving cropped-area estimates before harvest.

Enhanced diagnostic platforms for Post Entry Quarantine (PEQ)

Enhanced diagnostic platforms for Post Entry Quarantine (PEQ) and market access (Phase 1).

PA0187 Enhanced On-farm Monitoring and Mitigation of Pesticide and Nutrient Transport

Enhanced On-farm Monitoring and Mitigation of Pesticide and Nutrient Transport.

Telomere dynamics in the Sydney rock oyster (Saccostrea glomerata): an investigation into the effects of age, tissue type, location and time of sampling.

Telomere length has been purported as a biomarker for age and could offer a non-lethal method for determining the age of wild-caught individuals. Molluscs, including oysters and abalone, are the basis of important fisheries globally and have been problematic to accurately age. To determine whether telomere length could provide an alternative means of ageing molluscs, we evaluated the relationship between telomere length and age using the commercially important Sydney rock oyster (Saccostrea glomerata). Telomere lengths were estimated from tissues of known age individuals from different age classes, locations and at different sampling times. Telomere length tended to decrease with age only in young oysters less than 18 months old, but no decrease was observed in older oysters aged 2-4 years. Regional and temporal differences in telomere attrition rates were also observed. The relationship between telomere length and age was weak, however, with individuals of identical age varying significantly in their telomere length making it an imprecise age biomarker in oysters.

Soil carbon stock in the tropical rangelands of Australia: Effects of soil type and grazing pressure, and determination of sampling requirement.

On-going, high-profile public debate about climate change has focussed attention on how to monitor the soil organic carbon stock (C(s)) of rangelands (savannas). Unfortunately, optimal sampling of the rangelands for baseline C(s) - the critical first step towards efficient monitoring - has received relatively little attention to date. Moreover, in the rangelands of tropical Australia relatively little is known about how C(s) is influenced by the practice of cattle grazing. To address these issues we used linear mixed models to: (i) unravel how grazing pressure (over a 12-year period) and soil type have affected C(s) and the stable carbon isotope ratio of soil organic carbon (delta(13)C) (a measure of the relative contributions of C(3) and C(4) vegetation to C(s)); (ii) examine the spatial covariation of C(s) and delta(13)C; and, (iii) explore the amount of soil sampling required to adequately determine baseline C(s). Modelling was done in the context of the material coordinate system for the soil profile, therefore the depths reported, while conventional, are only nominal. Linear mixed models revealed that soil type and grazing pressure interacted to influence C(s) to a depth of 0.3 m in the profile. At a depth of 0.5 m there was no effect of grazing on C(s), but the soil type effect on C(s) was significant. Soil type influenced delta(13)C to a soil depth of 0.5 m but there was no effect of grazing at any depth examined. The linear mixed model also revealed the strong negative correlation of C(s) with delta(13)C, particularly to a depth of 0.1 m in the soil profile. This suggested that increased C(s) at the study site was associated with increased input of C from C(3) trees and shrubs relative to the C(4) perennial grasses; as the latter form the bulk of the cattle diet, we contend that C sequestration may be negatively correlated with forage production. Our baseline C(s) sampling recommendation for cattle-grazing properties of the tropical rangelands of Australia is to: (i) divide the property into units of apparently uniform soil type and grazing management; (ii) use stratified simple random sampling to spread at least 25 soil sampling locations about each unit, with at least two samples collected per stratum. This will be adequate to accurately estimate baseline mean C(s) to within 20% of the true mean, to a nominal depth of 0.3 m in the profile.