Pesticide residues in food - acute dietary exposure

Consumer risk assessment is a crucial step in the regulatory approval of pesticide use on food crops. Recently, an additional hurdle has been added to the formal consumer risk assessment process with the introduction of short-term intake or exposure assessment and a comparable short-term toxicity reference, the acute reference dose. Exposure to residues during one meal or over one day is important for short-term or acute intake. Exposure in the short term can be substantially higher than average because the consumption of a food on a single occasion can be very large compared with typical long-term or mean consumption and the food may have a much larger residue than average. Furthermore, the residue level in a single unit of a fruit or vegetable may be higher by a factor (defined as the variability factor, which we have shown to be typically ×3 for the 97.5th percentile unit) than the average residue in the lot. Available marketplace data and supervised residue trial data are examined in an investigation of the variability of residues in units of fruit and vegetables. A method is described for estimating the 97.5th percentile value from sets of unit residue data. Variability appears to be generally independent of the pesticide, the crop, crop unit size and the residue level. The deposition of pesticide on the individual unit during application is probably the most significant factor. The diets used in the calculations ideally come from individual and household surveys with enough consumers of each specific food to determine large portion sizes. The diets should distinguish the different forms of a food consumed, eg canned, frozen or fresh, because the residue levels associated with the different forms may be quite different. Dietary intakes may be calculated by a deterministic method or a probabilistic method. In the deterministic method the intake is estimated with the assumptions of large portion consumption of a ‘high residue’ food (high residue in the sense that the pesticide was used at the highest recommended label rate, the crop was harvested at the smallest interval after treatment and the residue in the edible portion was the highest found in any of the supervised trials in line with these use conditions). The deterministic calculation also includes a variability factor for those foods consumed as units (eg apples, carrots) to allow for the elevated residue in some single units which may not be seen in composited samples. In the probabilistic method the distribution of dietary consumption and the distribution of possible residues are combined in repeated probabilistic calculations to yield a distribution of possible residue intakes. Additional information such as percentage commodity treated and combination of residues from multiple commodities may be incorporated into probabilistic calculations. The IUPAC Advisory Committee on Crop Protection Chemistry has made 11 recommendations relating to acute dietary exposure.

NIR model development and robustness in prediction of melon fruit total soluble solids

Near infrared spectroscopy (NIRS) can be used for the on-line, non-invasive assessment of fruit for eating quality attributes such as total soluble solids (TSS). The robustness of multivariate calibration models, based on NIRS in a partial transmittance optical geometry, for the assessment of TSS of intact rockmelons (Cucumis melo) was assessed. The mesocarp TSS was highest around the fruit equator and increased towards the seed cavity. Inner mesocarp TSS levels decreased towards both the proximal and distal ends of the fruit, but more so towards the proximal end. The equatorial region of the fruit was chosen as representative of the fruit for near infrared assessment of TSS. The spectral window for model development was optimised at 695-1045 nm, and the data pre-treatment procedure was optimised to second-derivative absorbance without scatter correction. The 'global' modified partial least squares (MPLS) regression modelling procedure of WINISI (ver. 1.04) was found to be superior with respect to root mean squared error of prediction (RMSEP) and bias for model predictions of TSS across seasons, compared with the 'local' MPLS regression procedure. Updating of the model with samples selected randomly from the independent validation population demonstrated improvement in both RMSEP and bias with addition of approximately 15 samples.

The accuracy of varietal selection using factor analytic models for multi-environment plant breeding trials

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.

From inferential statistics to climate knowledge

Climate variability and change are risk factors for climate sensitive activities such as agriculture. Managing these risks requires "climate knowledge", i.e. a sound understanding of causes and consequences of climate variability and knowledge of potential management options that are suitable in light of the climatic risks posed. Often such information about prognostic variables (e.g. yield, rainfall, run-off) is provided in probabilistic terms (e.g. via cumulative distribution functions, CDF), whereby the quantitative assessments of these alternative management options is based on such CDFs. Sound statistical approaches are needed in order to assess whether difference between such CDFs are intrinsic features of systems dynamics or chance events (i.e. quantifying evidences against an appropriate null hypothesis). Statistical procedures that rely on such a hypothesis testing framework are referred to as "inferential statistics" in contrast to descriptive statistics (e.g. mean, median, variance of population samples, skill scores). Here we report on the extension of some of the existing inferential techniques that provides more relevant and adequate information for decision making under uncertainty.

Annual forecasting of the Australian macadamia crop - integrating tree census data with statistical climate-adjustment models

To facilitate marketing and export, the Australian macadamia industry requires accurate crop forecasts. Each year, two levels of crop predictions are produced for this industry. The first is an overall longer-term forecast based on tree census data of growers in the Australian Macadamia Society (AMS). This data set currently accounts for around 70% of total production, and is supplemented by our best estimates of non-AMS orchards. Given these total tree numbers, average yields per tree are needed to complete the long-term forecasts. Yields from regional variety trials were initially used, but were found to be consistently higher than the average yields that growers were obtaining. Hence, a statistical model was developed using growers' historical yields, also taken from the AMS database. This model accounted for the effects of tree age, variety, year, region and tree spacing, and explained 65% of the total variation in the yield per tree data. The second level of crop prediction is an annual climate adjustment of these overall long-term estimates, taking into account the expected effects on production of the previous year's climate. This adjustment is based on relative historical yields, measured as the percentage deviance between expected and actual production. The dominant climatic variables are observed temperature, evaporation, solar radiation and modelled water stress. Initially, a number of alternate statistical models showed good agreement within the historical data, with jack-knife cross-validation R2 values of 96% or better. However, forecasts varied quite widely between these alternate models. Exploratory multivariate analyses and nearest-neighbour methods were used to investigate these differences. For 2001-2003, the overall forecasts were in the right direction (when compared with the long-term expected values), but were over-estimates. In 2004 the forecast was well under the observed production, and in 2005 the revised models produced a forecast within 5.1% of the actual production. Over the first five years of forecasting, the absolute deviance for the climate-adjustment models averaged 10.1%, just outside the targeted objective of 10%.

Development and testing of an evaluation procedure for commercial manure additive products.

Manure additive products can be used to reduce odour emissions (OE) from livestock farms. The standardised evaluation of these manure additive products under specific farm conditions is important. In this study, the efficacy of a manure additive (WonderTreat(TM), CKLS, Inc., Hong-Kong) was assessed under Australian conditions utilising a combination of laboratory and field-scale evaluation techniques. As a first step, the efficacy of the manure additive was assessed in a laboratory-scale trial using a series of uniformly managed digesters and standard odour, liquor ammonia and hydrogen sulphide concentration measurement procedures. This showed that the addition of WonderTreat(TM) at the 'low dose rate' (LDR) (102.6 g m-2) used during the trial significantly, but only marginally (30%; P = 0.02) reduced the OE rate (mean 13.9 OU m-2 s-1) of anaerobic pig liquor relative to an untreated control (UC) (19.9 OU m-2 s-1). However, the 'high dose rate' (HDR) (205.3 g m-2) also assessed during the trial preformed similarly (19.7 OU m-2 s-1) to the UC. No statistically significant difference in the concentrations of a range of measured water quality variables at the 5% level was observed between the treatments or controls digesters. As a second step, a field-scale assessment of the manure additive was undertaken at a commercial piggery. Two piggery manure lagoons (each with approximately 2500 m2 surface area) were included in the study; one was treated with WonderTreat(TM) while the other was used as control. The efficacy of the treatment was assessed using olfactometric evaluation of odour samples collected from the surface of the pond using a dynamic wind tunnel and ancillary equipment. No statistically significant reduction in OE rate could be demonstrated (P = 0.35), partially due to the limited number of samples taken during the assessment. However, there was a numerical reduction in the average OE rate of the treatment pond (29 OU m-2 s-1 at 1 m s-1) compared to the control lagoon (38 OU m-2 s-1 at 1 m s-1).

Climate change effects on pasture systems in south-eastern Australia.

Climate change projections for Australia predict increasing temperatures, changes to rainfall patterns, and elevated atmospheric carbon dioxide (CO2) concentrations. The aims of this study were to predict plant production responses to elevated CO2 concentrations using the SGS Pasture Model and DairyMod, and then to quantify the effects of climate change scenarios for 2030 and 2070 on predicted pasture growth, species composition, and soil moisture conditions of 5 existing pasture systems in climates ranging from cool temperate to subtropical, relative to a historical baseline. Three future climate scenarios were created for each site by adjusting historical climate data according to temperature and rainfall change projections for 2030, 2070 mid-and 2070 high-emission scenarios, using output from the CSIRO Mark 3 global climate model. In the absence of other climate changes, mean annual pasture production at an elevated CO2 concentration of 550 ppm was predicted to be 24-29% higher than at 380 ppm CO2 in temperate (C-3) species-dominant pastures in southern Australia, with lower mean responses in a mixed C-3/C-4 pasture at Barraba in northern New South Wales (17%) and in a C-4 pasture at Mutdapilly in south-eastern Queensland (9%). In the future climate scenarios at the Barraba and Mutdapilly sites in subtropical and subhumid climates, respectively, where climate projections indicated warming of up to 4.4 degrees C, with little change in annual rainfall, modelling predicted increased pasture production and a shift towards C-4 species dominance. In Mediterranean, temperate, and cool temperate climates, climate change projections indicated warming of up to 3.3 degrees C, with annual rainfall reduced by up to 28%. Under future climate scenarios at Wagga Wagga, NSW, and Ellinbank, Victoria, our study predicted increased winter and early spring pasture growth rates, but this was counteracted by a predicted shorter spring growing season, with annual pasture production higher than the baseline under the 2030 climate scenario, but reduced by up to 19% under the 2070 high scenario. In a cool temperate environment at Elliott, Tasmania, annual production was higher than the baseline in all 3 future climate scenarios, but highest in the 2070 mid scenario. At the Wagga Wagga, Ellinbank, and Elliott sites the effect of rainfall declines on pasture production was moderated by a predicted reduction in drainage below the root zone and, at Ellinbank, the use of deeper rooted plant systems was shown to be an effective adaptation to mitigate some of the effect of lower rainfall.

Nitrogen use for high productivity and sustainability in cashew.

Interest in cashew production in Australia has been stimulated by domestic and export market opportunities and suitability of large areas of tropical Australia. Economic models indicate that cashew production is profitable at 2.8 t ha-1 nut-in-shell (NIS). Balanced plant nutrition is essential to achieve economic yields in Australia, with nitrogen (N) of particular importance because of its capacity to modify growth, affect nut yield and cause environmental degradation through soil acidification and off-site contamination. The study on a commercial cashew plantation at Dimbulah, Australia, investigated the effect of N rate and timing on cashew growth, nut production, N leaching and soil chemical properties over five growth cycles (1995-1999). Nitrogen was applied during the main periods of vegetative (December-April) and reproductive (June-October) growth. Commercial NIS yields (up to 4.4 t ha-1 from individual trees) that exceeded the economic threshold of 2.8 t ha-1 were achieved. The yield response was mainly determined by canopy size as mean nut weight, panicle density and nuts per panicle were largely unaffected by N treatments. Nitrogen application confined to the main period of vegetative growth (December-April) produced a seasonal growth pattern that corresponded most consistently with highest NIS yield. This N timing also reduced late season flowering and undesirable post-November nut drop. Higher yields were not produced at N rates greater than 17 g m-2 of canopy surface area (equating to 210 kg N ha-1 for mature size trees). High yields were attained when N concentrations in Mveg leaves in May-June were about 2%, but this assessment occurs at a time when it is not feasible to correct N deficiency. The Mflor leaf of the preceding November, used in conjunction with the Mveg leaf, was proposed as a diagnostic tool to guide N rate decisions. Leaching of nitrate-N and acidification of the soil profile was recorded to 0.9 m. This is an environmental and sustainability hazard, and demonstrates that improved methods of N management are required.

Wood properties and processing outcomes for plantation grown African mahogany (Khaya senegalensis) trees from Clare, Queensland (18 and 20 year-old trees) and Katherine, Northern Territory (14 year-old trees).

Khaya senegalensis, African mahogany, a high-value hardwood, was introduced in the Northern Territory (NT) in the 1950s; included in various trials there and at Weipa, Q in the 1960s-1970s; planted on ex mine sites at Weipa (160 ha) until 1985; revived in farm plantings in Queensland and in trials in the NT in the 1990s; adopted for large-scale, annual planting in the Douglas-Daly region, NT from 2006 and is to have the planted area in the NT extended to at least 20,000 ha. The recent serious interest from plantation growers, including Forest Enterprises Australia Ltd (FEA), has seen the establishment of some large scale commercial plantations. FEA initiated the current study to process relatively young plantation stands from both Northern Territory and Queensland plantations to investigate the sawn wood and veneer recovery and quality from trees ranging from 14 years (NT – 36 trees) to 18-20 years (North Queensland – 31 trees). Field measures of tree size and straightness were complemented with log end splitting assessment and cross-sectional disc sample collection for laboratory wood properties measurements including colour and shrinkage. End-splitting scores assessed on sawn logs were relatively low compared to fast grown plantation eucalypts and did not impact processing negatively. Heartwood proportion in individual trees ranged from 50% up to 92 % of butt cross-sectional disc area for the visually-assessed dark coloured central heartwood and lighter coloured transition wood combined. Dark central heartwood proportion was positively related to tree size (R2 = 0.57). Chemical tests failed to assist in determining heartwood – sapwood boundary. Mean basic density of whole disc samples was 658 kg/m3 and ranged among trees from 603 to 712 kg/m3. When freshly sawn, the heartwood of African mahogany was orange-red to red. Transition wood appeared to be pinkish and the sapwood was a pale yellow colour. Once air dried the heartwood colour generally darkens to pinkish-brown or orange-brown and the effect of prolonged time and sun exposure is to darken and change the heartwood to a red-brown colour. A portable colour measurement spectrophotometer was used to objectively assess colour variation in CIE L*, a* and b* values over time with drying and exposure to sunlight. Capacity to predict standard colour values accurately after varying periods of direct sunlight exposure using results obtained on initial air-dried surfaces decreased with increasing time to sun exposure. The predictions are more accurate for L* values which represent brightness than for variation in the a* values (red spectrum). Selection of superior breeding trees for colour is likely to be based on dried samples exposed to sunlight to reliably highlight wood colour differences. A generally low ratio between tangential and radial shrinkages was found, which was reflected in a low incidence of board distortion (particularly cupping) during drying. A preliminary experiment was carried out to investigate the quality of NIR models to predict shrinkage and density. NIR spectra correlated reasonably well with radial shrinkage and air dried density. When calibration models were applied to their validation sets, radial shrinkage was predicted to an accuracy of 76% with Standard Error of Prediction of 0.21%. There was also a strong predictive power for wood density. These are encouraging results suggesting that NIR spectroscopy has good potential to be used as a non-destructive method to predict shrinkage and wood density using 12mm diameter increment core samples. Average green off saw recovery was 49.5% (range 40 to 69%) for Burdekin Agricultural College (BAC) logs and 41.9% (range 20 to 61%) for Katherine (NT) logs. These figures are about 10% higher than compared to 30-year-old Khaya study by Armstrong et al. (2007) however they are inflated as the green boards were not docked to remove wane prior to being tallied. Of the recovered sawn, dried and dressed volume from the BAC logs, based on the cambial face of boards, 27% could potentially be used for select grade, 40% for medium feature grade and 26% for high feature grades. The heart faces had a slightly higher recovery of select (30%) and medium feature (43%) grade boards with a reduction in the volume of high feature (22%) and reject (6%) grade boards. Distribution of board grades for the NT site aged 14 years followed very similar trends to those of the BAC site boards with an average (between facial and cambial face) 27% could potentially be used for select grade, 42% for medium feature grade, 26% for high feature grade and 5% reject. Relatively to some other subtropical eucalypts, there was a low incidence of borer attack. The major grade limiting defects for both medium and high feature grade boards recovered from the BAC site were knots and wane. The presence of large knots may reflect both management practices and the nature of the genetic material at the site. This stand was not managed for timber production with a very late pruning implemented at about age 12 years. The large amount of wane affected boards is indicative of logs with a large taper and the presence of significant sweep. Wane, knots and skip were the major grade limiting defects for the NT site reflecting considerable amounts of sweep with large taper as might be expected in younger trees. The green veneer recovered from billets of seven Khaya trees rotary peeled on a spindleless lathe produced a recovery of 83% of green billet volume. Dried veneer recovery ranged from 40 to 74 % per billet with an average of 64%. All of the recovered grades were suitable for use in structural ply in accordance to AS/NZ 2269: 2008. The majority of veneer sheets recovered from all billets was C grade (27%) with 20% making D grade and 13% B grade. Total dry sliced veneer recovery from the logs of the two largest logs from each location was estimated to be 41.1%. Very positive results have been recorded in this small scale study. The amount of colour development observed and the very reasonable recoveries of both sawn and veneer products, with a good representation of higher grades in the product distribution, is encouraging. The prospects for significant improvement in these results from well managed and productive stands grown for high quality timber should be high. Additionally, the study has shown the utility of non-destructive evaluation techniques for use in tree improvement programs to improve the quality of future plantations. A few trees combined several of the traits desired of individuals for a first breeding population. Fortunately, the two most promising trees (32, 19) had already been selected for breeding on external traits, and grafts of them are established in the seed orchard.

High-Throughput Prediction of Acacia and Eucalypt Lignin Syringyl/Guaiacyl Content Using FT-Raman Spectroscopy and Partial Least Squares Modeling

High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials.

Probiotic Bacillus amyloliquefaciens Strain H57 Improves the Performance of Pregnant and Lactating Ewes Fed a Diet Based on Palm Kernel Meal

Probiotic supplements are single or mixed strain cultures of live microorganisms that benefit the host by improving the properties of the indigenous microflora (Seo et al 2010). In a pilot study at the University of Queensland, Norton et al (2008) found that Bacillus amyloliquefaciens Strain H57 (H57), primarily investigated as an inoculum to make high-quality hay, improved feed intake and nitrogen utilisation over several weeks in pregnant ewes. The purpose of the following study was to further challenge the potential of H57 -to show it survives the steam-pelleting process, and that it improves the performance of ewes fed pellets based on an agro-industrial by-product with a reputation for poor palatability, palm kernel meal (PKM), (McNeill 2013). Thirty-two first-parity White Dorper ewes (day 37 of pregnancy, mean liveweight = 47.3 kg, mean age = 15 months) were inducted into individual pens in the animal house at the University of Queensland, Gatton. They were adjusted onto PKM-based pellets (g/kg drymatter (DM): PKM, 408; sorghum, 430; chick pea hulls, 103; minerals and vitamins; Crude protein, 128; ME: 11.1MJ/kg DM) until day 89 of pregnancy and thereafter fed a predominately pelleted diet incorporating with or without H57 spores (10 9 colony forming units (cfu)/kg pellet, as fed), plus 100g/ewe/day oaten chaff, until day 7 of lactation. From day 7 to 20 of lactation the pelleted component of the diet was steadily reduced to be replaced by a 50:50 mix of lucerne: oaten chaff, fed ad libitum, plus 100g/ewe/day of ground sorghum grain with or without H57 (10 9 cfu/ewe/day). The period of adjustment in pregnancy (day 37-89) extended beyond expectations due to some evidence of mild ruminal acidosis after some initially high intakes that were followed by low intakes. During that time the diet was modified, in an attempt to improve palatability, by the addition of oaten chaff and the removal of an acidifying agent (NH4Cl) that was added initially to reduce the risk of urinary calculi. Eight ewes were removed due to inappetence, leaving 24 ewes to start the trial at day 90 of pregnancy. From day 90 of pregnancy until day 63 of lactation, liveweights of the ewes and their lambs were determined weekly and at parturition. Feed intakes of the ewes were determined weekly. Once lambing began, 1 ewe was removed as it gave birth to twin lambs (whereas the rest gave birth to a single lamb), 4 due to the loss of their lambs (2 to dystocia), and 1 due to copper toxicity. The PKM pellets were suspected to be the cause of the copper toxicity and so were removed in early lactation. Hence, the final statistical analysis using STATISTICA 8 (Repeated measures ANOVA for feed intake, One-way ANOVA for liveweight change and birth weight) was completed on 23 ewes for the pregnancy period (n = 11 fed H57; n = 12 control), and 18 ewes or lambs for the lactation period (n = 8 fed H57; n = 10 control). From day 90 of pregnancy until parturition the H57 supplemented ewes ate 17 more DM (g/day: 1041 vs 889, sed = 42.4, P = 0.04) and gained more liveweight (g/day: 193 vs 24.0, sed = 25.4, P = 0.0002), but produced lambs with a similar birthweight (kg: 4.18 vs 3.99, sed = 0.19, P = 0.54). Over the 63 days of lactation the H57 ewes ate similar amounts of DM but grew slower than the control ewes (g/day: 1.5 vs 97.0, sed = 21.7, P = 0.012). The lambs of the H57 ewes grew faster than those of the control ewes for the first 21 days of lactation (g/day: 356 vs 265, sed = 16.5, P = 0.006). These data support the findings of Norton et al (2008) and Kritas et al (2006) that certain Bacillus spp. supplements can improve the performance of pregnant and lactating ewes. In the current study we particularly highlighted the capacity of H57 to stimulate immature ewes to continue to grow maternal tissue through pregnancy, possibly through an enhanced appetite, which appeared then to stimulate a greater capacity to partition nutrients to their lambs through milk, at least for the first few weeks of lactation, a critical time for optimising lamb survival. To conclude, H57 can survive the steam pelleting process to improve feed intake and maternal liveweight gain in late pregnancy, and performance in early lactation, of first-parity ewes fed a diet based on PKM.

Flying-Fox Roost Disturbance and Hendra Virus Spillover Risk

Bats of the genus Pteropus (flying-foxes) are the natural host of Hendra virus (HeV) which periodically causes fatal disease in horses and humans in Australia. The increased urban presence of flying-foxes often provokes negative community sentiments because of reduced social amenity and concerns of HeV exposure risk, and has resulted in calls for the dispersal of urban flying-fox roosts. However, it has been hypothesised that disturbance of urban roosts may result in a stress-mediated increase in HeV infection in flying-foxes, and an increased spillover risk. We sought to examine the impact of roost modification and dispersal on HeV infection dynamics and cortisol concentration dynamics in flying-foxes. The data were analysed in generalised linear mixed models using restricted maximum likelihood (REML). The difference in mean HeV prevalence in samples collected before (4.9%), during (4.7%) and after (3.4%) roost disturbance was small and non-significant (P = 0.440). Similarly, the difference in mean urine specific gravity-corrected urinary cortisol concentrations was small and non-significant (before = 22.71 ng/mL, during = 27.17, after = 18.39) (P= 0.550). We did find an underlying association between cortisol concentration and season, and cortisol concentration and region, suggesting that other (plausibly biological or environmental) variables play a role in cortisol concentration dynamics. The effect of roost disturbance on cortisol concentration approached statistical significance for region, suggesting that the relationship is not fixed, and plausibly reflecting the nature and timing of disturbance. We also found a small positive statistical association between HeV excretion status and urinary cortisol concentration. Finally, we found that the level of flying-fox distress associated with roost disturbance reflected the nature and timing of the activity, highlighting the need for a ‘best practice’ approach to dispersal or roost modification activities. The findings usefully inform public discussion and policy development in relation to Hendra virus and flying-fox management.

Statistical methods for analysis of multi-harvest data from perennial pasture variety selection trials

Variety selection in perennial pasture crops involves identifying best varieties from data collected from multiple harvest times in field trials. For accurate selection, the statistical methods for analysing such data need to account for the spatial and temporal correlation typically present. This paper provides an approach for analysing multi-harvest data from variety selection trials in which there may be a large number of harvest times. Methods are presented for modelling the variety by harvest effects while accounting for the spatial and temporal correlation between observations. These methods provide an improvement in model fit compared to separate analyses for each harvest, and provide insight into variety by harvest interactions. The approach is illustrated using two traits from a lucerne variety selection trial. The proposed method provides variety predictions allowing for the natural sources of variation and correlation in multi-harvest data.