MOE and MOR assessment technologies for improving graded recovery of exotic pines in Australia.

This project was designed to provide the structural softwood processing industry with the basis for improved green and dry grading to allow maximise MGP grade yields, consistent product performance and reduced processing costs. To achieve this, advanced statistical techniques were used in conjunction with state-of-the-art property measurement systems. Specifically, the project aimed to make two significant steps forward for the Australian structural softwood industry: • assessment of technologies, both existing and novel, that may lead to selection of a consistent, reliable and accurate device for the log yard and green mill. The purpose is to more accurately identify and reject material that will not make a minimum grade of MGP10 downstream; • improved correlation of grading MOE and MOR parameters in the dry mill using new analytical methods and a combination of devices. The three populations tested were stiffness-limited radiata pine, strength-limited radiata pine and Caribbean pine. Resonance tests were conducted on logs prior to sawmilling, and on boards. Raw data from existing in-line systems were captured for the green and dry boards. The dataset was analysed using classical and advanced statistical tools to provide correlations between data sets and to develop efficient strength and stiffness prediction equations. Stiffness and strength prediction algorithms were developed from raw and combined parameters. Parameters were analysed for comparison of prediction capabilities using in-line parameters, off-line parameters and a combination of in-line and off-line parameters. The results show that acoustic resonance techniques have potential for log assessment, to sort for low stiffness and/or low strength, depending on the resource. From the log measurements, a strong correlation was found between the average static MOE of the dried boards within a log and the predicted value. These results have application in segregating logs into structural and non-structural uses. Some commercial technologies are already available for this application such as Hitman LG640. For green boards it was found that in-line and laboratory acoustic devices can provide a good prediction of dry static MOE and moderate prediction for MOR.There is high potential for segregating boards at this stage of processing. Grading after the log breakdown can improve significantly the effectiveness of the mill. Subsequently, reductions in non-structural volumes can be achieved. Depending on the resource it can be expected that a 5 to 8 % reduction in non structural boards won’t be dried with an associated saving of $70 to 85/m3. For dry boards, vibration and a standard Metriguard CLT/HCLT provided a similar level of prediction on stiffness limited resource. However, Metriguard provides a better strength prediction in strength limited resources (due to this equipment’s ability to measure local characteristics). The combination of grading equipment specifically for stiffness related predictors (Metriguard or vibration) with defect detection systems (optical or X-ray scanner) provides a higher level of prediction, especially for MOR. Several commercial technologies are already available for acoustic grading on board such those from Microtec, Luxscan, Falcon engineering or Dynalyse AB for example. Differing combinations of equipment, and their strategic location within the processing chain, can dramatically improve the efficiency of the mill, the level of which will vary depending of the resource. For example, an initial acoustic sorting on green boards combined with an optical scanner associated with an acoustic system for grading dry board can result in a large reduction of the proportion of low value low non-structural produced. The application of classical MLR on several predictors proved to be effective, in particular for MOR predictions. However, the usage of a modern statistics approach(chemometrics tools) such as PLS proved to be more efficient for improving the level of prediction. Compared to existing technologies, the results of the project indicate a good improvement potential for grading in the green mill, ahead of kiln drying and subsequent cost-adding processes. The next stage is the development and refinement of systems for this purpose.

Uncertainty in length measurements of live coral trout: implications for compliance and enforcement of minimum legal size limits.

Report on evidence of shrinkage of live coral trout during professional fishing operations on the Great Barrier Reef in 2000. Excel data includes the following fields: Column A. Fish (fish number from 1 -24) Column B. Bin (1-8, container the fish was held in during the experiment) Column C. Measure (1-7, number of the measurement of each fish) Column D. Observer (1 or 2, making the measurement) Column E. Time 2 Column F. Time (time of the day the measurement was made) Column G. FL (Fork Length) Column H. TL (Total Length) Column I. Difference (difference in length between measures) Column J. Order Column K. Temperature (surface water temp under the boat)

Short- and long-term movement patterns in the freshwater whipray (Himantura dalyensis) determined by the signal processing of passive acoustic telemetry data.

Patterns of movement in aquatic animals reflect ecologically important behaviours. Cyclical changes in the abiotic environment influence these movements, but when multiple processes occur simultaneously, identifying which is responsible for the observed movement can be complex. Here we used acoustic telemetry and signal processing to define the abiotic processes responsible for movement patterns in freshwater whiprays (Himantura dalyensis). Acoustic transmitters were implanted into the whiprays and their movements detected over 12 months by an array of passive acoustic receivers, deployed throughout 64 km of the Wenlock River, Qld, Australia. The time of an individual's arrival and departure from each receiver detection field was used to estimate whipray location continuously throughout the study. This created a linear-movement-waveform for each whipray and signal processing revealed periodic components within the waveform. Correlation of movement periodograms with those from abiotic processes categorically illustrated that the diel cycle dominated the pattern of whipray movement during the wet season, whereas tidal and lunar cycles dominated during the dry season. The study methodology represents a valuable tool for objectively defining the relationship between abiotic processes and the movement patterns of free-ranging aquatic animals and is particularly expedient when periods of no detection exist within the animal location data.

Rotary veneering of plantation-grown spotted gum (Corymbia citriodora subsp. variegata) and Dunn's white gum (Eucalyptus dunnii)

This report evaluates the wood and veneer properties of plantation-grown spotted gum (Corymbia citriodora subsp. variegata, or CCV) and Dunn's white gum (Eucalyptus dunnii), grown at different stockings, in thinning trials near Ellangowan in north-east New South Wales (mean annual rainfall 1050 mm) and Kingaroy in south-east Queensland (mean annual rainfall 873 mm). Thinning trials were established at age seven years. Both species showed a significant increase in stem diameter growth of the dominant trees in response to thinning. At age 10 years, trees from the unthinned (950–1270 stems ha-1) and 300 stems ha-1 treatments were selected for veneering. Five dominant trees were felled from each combination of species x sites x thinning treatment. Diameter at breast height over bark of the selected trees ranged from 20 cm to 27 cm at Ellangowan, and 19 cm to 26 cm at Kingaroy. From each tree, 1.5 m long billets were removed at two positions: a butt billet from 0.3–1.8 m above ground and a top billet from approximately 5.5–7.0 m. Log end splitting was assessed 24 hours after harvesting and again after steaming, approximately four days after harvesting. Disks from just above both billets were collected for assessment of wood properties. Billets were peeled on a spindleless veneer lathe to produce a full veneer ribbon with a target green thickness of 2.8 to 3.0 mm. The 1.55 m wide (tangential dimension) veneer sheets were dried and graded according to AS/NZ Standard 2269:2008, which describes four veneer grades. Veneer samples taken along the length of the veneer ribbon, at regular intervals of 1.55 m, were tested for stiffness, shrinkage and density. Veneer length measurements were used to calculate the radial distance of each sample from the central axis of the billet. Overall veneer gross recoveries ranged from 50% to 70%. They were significantly lower at the Kingaroy site, for both species. The veneer recoveries achieved were 2–3 times higher than typical green off saw recoveries from small plantation hardwood logs of similar diameter. Most of the veneer recovered was classified as D-grade. CCV trees from the Ellangowan site yielded up to 38% of the better C-grade and higher grade veneers. The main limiting factors that prevented veneer from meeting higher grades were the presence of kino defects and encased knots. Splits in E. dunnii veneer also contributed to reduced grade quality. Log end splits were higher for E. dunnii than for CCV, and logs from Ellangowan exhibited more severe splitting. Split index was generally higher for top than for butt billets. Split index was strongly correlated with the average veneer grade from corresponding billets. The Ellangowan site, where rainfall was higher and trees grew faster, yielded significantly denser and stiffer veneers than did the drier sites near Kingaroy, where tree growth was slower. The difference was more pronounced for E. dunnii than for CCV. Differences in measured wood properties between thinned and unthinned treatments were generally small and not significant. On average, 10% of billet volume was lost during the peeling rounding-up process. Much of the wood laid down following thinning was removed during rounding-up, meaning the effect of thinning on veneer properties could not be effectively assessed. CCV was confirmed as having high veneer density and very good veneer stiffness, exceeding 15 GPa, making it very suitable for structural products. E. dunnii also demonstrated good potential as a useful structural plywood resource, achieving stiffness above 10 GPa. Veneer stiffness and density in CCV increased from pith to bark at both sites, while for E. dunnii there was a radial increase in these properties at the Ellangowan site only. At the drier Kingaroy site, veneer stiffness and density declined from mid-radius to the log periphery. This may be associated with prolonged drought from 2005 to 2009, corresponding to the later years of tree growth at the Kingaroy site. CCV appeared to be less sensitive to drought conditions. Standing tree acoustic velocity, determined by the Fakopp time-of-flight method, provided a reliable prediction of average veneer stiffness for both species (R2=0.78 for CCV and R2=0.90 for E. dunnii) suggesting that the Fakopp method may be a useful indicator of tree and stand quality, in terms of veneer stiffness in standing trees.

Large-chamber methane and nitrous oxide measurements are comparable to the backward Lagrangian stochastic method

Measurement of individual emission sources (e.g., animals or pen manure) within intensive livestock enterprises is necessary to test emission calculation protocols and to identify targets for decreased emissions. In this study, a vented, fabric-covered large chamber (4.5 × 4.5 m, 1.5 m high; encompassing greater spatial variability than a smaller chamber) in combination with on-line analysis (nitrous oxide [N2O] and methane [CH4] via Fourier Transform Infrared Spectroscopy; 1 analysis min-1) was tested as a means to isolate and measure emissions from beef feedlot pen manure sources. An exponential model relating chamber concentrations to ambient gas concentrations, air exchange (e.g., due to poor sealing with the surface; model linear when ≈ 0 m3 s-1), and chamber dimensions allowed data to be fitted with high confidence. Alternating manure source emission measurements using the large-chamber and the backward Lagrangian stochastic (bLS) technique (5-mo period; bLS validated via tracer gas release, recovery 94-104%) produced comparable N2O and CH4 emission values (no significant difference at P < 0.05). Greater precision of individual measurements was achieved via the large chamber than for the bLS (mean ± standard error of variance components: bLS half-hour measurements, 99.5 ± 325 mg CH4 s-1 and 9.26 ± 20.6 mg N2O s-1; large-chamber measurements, 99.6 ± 64.2 mg CH4 s-1 and 8.18 ± 0.3 mg N2O s-1). The large-chamber design is suitable for measurement of emissions from manure on pen surfaces, isolating these emissions from surrounding emission sources, including enteric emissions. © © American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.

Estimating daily methane production in individual cattle with irregular feed intake patterns from short-term methane emission measurements

Spot measurements of methane emission rate (n = 18 700) by 24 Angus steers fed mixed rations from GrowSafe feeders were made over 3- to 6-min periods by a GreenFeed emission monitoring (GEM) unit. The data were analysed to estimate daily methane production (DMP; g/day) and derived methane yield (MY; g/kg dry matter intake (DMI)). A one-compartment dose model of spot emission rate v. time since the preceding meal was compared with the models of Wood (1967) and Dijkstra et al. (1997) and the average of spot measures. Fitted values for DMP were calculated from the area under the curves. Two methods of relating methane and feed intakes were then studied: the classical calculation of MY as DMP/DMI (kg/day); and a novel method of estimating DMP from time and size of preceding meals using either the data for only the two meals preceding a spot measurement, or all meals for 3 days prior. Two approaches were also used to estimate DMP from spot measurements: fitting of splines on a 'per-animal per-day' basis and an alternate approach of modelling DMP after each feed event by least squares (using Solver), summing (for each animal) the contributions from each feed event by best-fitting a one-compartment model. Time since the preceding meal was of limited value in estimating DMP. Even when the meal sizes and time intervals between a spot measurement and all feeding events in the previous 72 h were assessed, only 16.9% of the variance in spot emission rate measured by GEM was explained by this feeding information. While using the preceding meal alone gave a biased (underestimate) of DMP, allowing for a longer feed history removed this bias. A power analysis taking into account the sources of variation in DMP indicated that to obtain an estimate of DMP with a 95% confidence interval within 5% of the observed 64 days mean of spot measures would require 40 animals measured over 45 days (two spot measurements per day) or 30 animals measured over 55 days. These numbers suggest that spot measurements could be made in association with feed efficiency tests made over 70 days. Spot measurements of enteric emissions can be used to define DMP but the number of animals and samples are larger than are needed when day-long measures are made.