Process studies of odour emissions from effluent ponds using machine-based odour measurement

Replicable experimental studies using a novel experimental facility and a machine-based odour quantification technique were conducted to demonstrate the relationship between odour emission rates and pond loading rates. The odour quantification technique consisted of an electronic nose, AromaScan A32S, and an artificial neural network. Odour concentrations determined by olfactometry were used along with the AromaScan responses to train the artificial neural network. The trained network was able to predict the odour emission rates for the test data with a correlation coefficient of 0.98. Time averaged odour emission rates predicted by the machine-based odour quantification technique, were strongly correlated with volatile solids loading rate, demonstrating the increased magnitude of emissions from a heavily loaded effluent pond. However, it was not possible to obtain the same relationship between volatile solids loading rates and odour emission rates from the individual data. It is concluded that taking a limited number of odour samples over a short period is unlikely to provide a representative rate of odour emissions from an effluent pond. A continuous odour monitoring instrument will be required for that more demanding task.

Soil nitrogen—crop response calibration relationships and criteria for winter cereal crops grown in Australia

More than 1200 wheat and 120 barley experiments conducted in Australia to examine yield responses to applied nitrogen (N) fertiliser are contained in a national database of field crops nutrient research (BFDC National Database). The yield responses are accompanied by various pre-plant soil test data to quantify plant-available N and other indicators of soil fertility status or mineralisable N. A web application (BFDC Interrogator), developed to access the database, enables construction of calibrations between relative crop yield ((Y0/Ymax) × 100) and N soil test value. In this paper we report the critical soil test values for 90% RY (CV90) and the associated critical ranges (CR90, defined as the 70% confidence interval around that CV90) derived from analysis of various subsets of these winter cereal experiments. Experimental programs were conducted throughout Australia’s main grain-production regions in different eras, starting from the 1960s in Queensland through to Victoria during 2000s. Improved management practices adopted during the period were reflected in increasing potential yields with research era, increasing from an average Ymax of 2.2 t/ha in Queensland in the 1960s and 1970s, to 3.4 t/ha in South Australia (SA) in the 1980s, to 4.3 t/ha in New South Wales (NSW) in the 1990s, and 4.2 t/ha in Victoria in the 2000s. Various sampling depths (0.1–1.2 m) and methods of quantifying available N (nitrate-N or mineral-N) from pre-planting soil samples were used and provided useful guides to the need for supplementary N. The most regionally consistent relationships were established using nitrate-N (kg/ha) in the top 0.6 m of the soil profile, with regional and seasonal variation in CV90 largely accounted for through impacts on experimental Ymax. The CV90 for nitrate-N within the top 0.6 m of the soil profile for wheat crops increased from 36 to 110 kg nitrate-N/ha as Ymax increased over the range 1 to >5 t/ha. Apparent variation in CV90 with seasonal moisture availability was entirely consistent with impacts on experimental Ymax. Further analyses of wheat trials with available grain protein (~45% of all experiments) established that grain yield and not grain N content was the major driver of crop N demand and CV90. Subsets of data explored the impact of crop management practices such as crop rotation or fallow length on both pre-planting profile mineral-N and CV90. Analyses showed that while management practices influenced profile mineral-N at planting and the likelihood and size of yield response to applied N fertiliser, they had no significant impact on CV90. A level of risk is involved with the use of pre-plant testing to determine the need for supplementary N application in all Australian dryland systems. In southern and western regions, where crop performance is based almost entirely on in-crop rainfall, this risk is offset by the management opportunity to split N applications during crop growth in response to changing crop yield potential. In northern cropping systems, where stored soil moisture at sowing is indicative of minimum yield potential, erratic winter rainfall increases uncertainty about actual yield potential as well as reducing the opportunity for effective in-season applications.

Getting value out of your sensory testing - the difference from control test

Non-parametric difference tests such as triangle and duo-trio tests traditionally are used to establish differences or similarities between products. However they only supply the researcher with partial answers and often further testing is required to establish the nature, size and direction of differences. This paper looks at the advantages of the difference from control (DFC) test (also known as degree of difference test) and discusses appropriate applications of the test. The scope and principle of the test, panel composition and analysis of results are presented with the aid of suitable examples. Two of the major uses of the DFC test are in quality control and shelf-life testing. The role DFC takes in these areas and the use of other tests to complement the testing is discussed. Controls or standards are important in both these areas and the use of standard products, mental and written standards and blind controls are highlighted. The DFC test has applications in products where the duo-trio and triangle tests cannot be used because of the normal heterogeneity of the product. While the DFC test is a simple difference test it can be structured to give the researcher more valuable data and scope to make informed decisions about their product.

A new data source for fisheries resource assessment: genetic estimates of the effective number of spawners. Final Report to the Fisheries Research and Development Corporation.

The development of innovative methods of stock assessment is a priority for State and Commonwealth fisheries agencies. It is driven by the need to facilitate sustainable exploitation of naturally occurring fisheries resources for the current and future economic, social and environmental well being of Australia. This project was initiated in this context and took advantage of considerable recent achievements in genomics that are shaping our comprehension of the DNA of humans and animals. The basic idea behind this project was that genetic estimates of effective population size, which can be made from empirical measurements of genetic drift, were equivalent to estimates of the successful number of spawners that is an important parameter in process of fisheries stock assessment. The broad objectives of this study were to 1. Critically evaluate a variety of mathematical methods of calculating effective spawner numbers (Ne) by a. conducting comprehensive computer simulations, and by b. analysis of empirical data collected from the Moreton Bay population of tiger prawns (P. esculentus). 2. Lay the groundwork for the application of the technology in the northern prawn fishery (NPF). 3. Produce software for the calculation of Ne, and to make it widely available. The project pulled together a range of mathematical models for estimating current effective population size from diverse sources. Some of them had been recently implemented with the latest statistical methods (eg. Bayesian framework Berthier, Beaumont et al. 2002), while others had lower profiles (eg. Pudovkin, Zaykin et al. 1996; Rousset and Raymond 1995). Computer code and later software with a user-friendly interface (NeEstimator) was produced to implement the methods. This was used as a basis for simulation experiments to evaluate the performance of the methods with an individual-based model of a prawn population. Following the guidelines suggested by computer simulations, the tiger prawn population in Moreton Bay (south-east Queensland) was sampled for genetic analysis with eight microsatellite loci in three successive spring spawning seasons in 2001, 2002 and 2003. As predicted by the simulations, the estimates had non-infinite upper confidence limits, which is a major achievement for the application of the method to a naturally-occurring, short generation, highly fecund invertebrate species. The genetic estimate of the number of successful spawners was around 1000 individuals in two consecutive years. This contrasts with about 500,000 prawns participating in spawning. It is not possible to distinguish successful from non-successful spawners so we suggest a high level of protection for the entire spawning population. We interpret the difference in numbers between successful and non-successful spawners as a large variation in the number of offspring per family that survive – a large number of families have no surviving offspring, while a few have a large number. We explored various ways in which Ne can be useful in fisheries management. It can be a surrogate for spawning population size, assuming the ratio between Ne and spawning population size has been previously calculated for that species. Alternatively, it can be a surrogate for recruitment, again assuming that the ratio between Ne and recruitment has been previously determined. The number of species that can be analysed in this way, however, is likely to be small because of species-specific life history requirements that need to be satisfied for accuracy. The most universal approach would be to integrate Ne with spawning stock-recruitment models, so that these models are more accurate when applied to fisheries populations. A pathway to achieve this was established in this project, which we predict will significantly improve fisheries sustainability in the future. Regardless of the success of integrating Ne into spawning stock-recruitment models, Ne could be used as a fisheries monitoring tool. Declines in spawning stock size or increases in natural or harvest mortality would be reflected by a decline in Ne. This would be good for data-poor fisheries and provides fishery independent information, however, we suggest a species-by-species approach. Some species may be too numerous or experiencing too much migration for the method to work. During the project two important theoretical studies of the simultaneous estimation of effective population size and migration were published (Vitalis and Couvet 2001b; Wang and Whitlock 2003). These methods, combined with collection of preliminary genetic data from the tiger prawn population in southern Gulf of Carpentaria population and a computer simulation study that evaluated the effect of differing reproductive strategies on genetic estimates, suggest that this technology could make an important contribution to the stock assessment process in the northern prawn fishery (NPF). Advances in the genomics world are rapid and already a cheaper, more reliable substitute for microsatellite loci in this technology is available. Digital data from single nucleotide polymorphisms (SNPs) are likely to super cede ‘analogue’ microsatellite data, making it cheaper and easier to apply the method to species with large population sizes.

Management Guidelines for New Warm-Season Grasses in Australia

After more than 30 years in which ‘Tifgreen’ and ‘Tifdwarf’ were the only greens-quality varieties available, the choice for golf courses and bowls clubs in northern Australia has been expanded to include six new Cynodon hybrids [Cynodon dactylon (L.) Pers x Cynodon transvaalensis Burtt-Davy]. Five of these – ‘Champion Dwarf’ (Texas), ‘MS-Supreme’ (Mississippi), FloraDwarf™ (Florida), ‘TifEagle’ (Georgia), MiniVerde™ (Arizona) - are from US breeding programs, while the sixth, ‘TL2’ (marketed as Novotek™) was selected in north Queensland. The finer, denser and lower growing habit of the “ultradwarf” cultivars allows very low mowing heights (e.g. 2.5 mm) to be imposed, resulting in denser and smoother putting and bowls surfaces. In addition to the Cynodon hybrids, four new greens quality seashore paspalum (Paspalum vaginatum O. Swartz) cultivars including ‘Sea Isle 2000’, Sea Isle Supreme™, Velvetene™ and Sea Dwarf™ (where tolerance of salty water is required) expands the range of choices for greens in difficult environments. The project was developed to determine (a) the appropriate choice of cultivar for different environments and budgets, and (b) best management practices for the new cultivars which differ from the Cynodon hybrid industry standards ‘Tifgreen’ and ‘Tifdwarf’. Management practices, particularly fertilising, mowing heights and frequency, and thatch control were investigated to determine optimum management inputs and provide high quality playing surfaces with the new grasses. To enable effective trialling of these new and old cultivars it was essential to have a number of regional sites participating in the study. Drought and financial hardship of many clubs presented an initial setback with numerous clubs wanting to be involved in the study but were unable to commit due to their financial position at the time. The study was fortunate to have seven regional sites from Queensland, New South Wales, Victoria and South Australia volunteer to be involved in the study which would add to the results being collected at the centralised test facility being constructed at DEEDI’s Redlands Research Station. The major research findings acquired from the eight trial sites included: • All of the new second generation “ultradwarf” couchgrasses tend to produce a large amount of thatch with MiniVerde™ being the greatest thatch producer, particularly compared to ‘Tifdwarf’ and ‘Tifgreen’. The maintenance of the new Cynodon hybrids will require a program of regular dethatching/grooming as well as regular light dustings of sand. Thatch prevention should begin 3 to 4 weeks after planting a new “ultradwarf” couchgrass green, with an emphasis on prevention rather than control. • The “ultradwarfs” produced faster green speeds than the current industry standards ‘Tifgreen’ and ‘Tifdwarf’. However, all Cynodon hybrids were considerably faster than the seashore paspalums (e.g. comparable to the speed diference of Bentgrass and couchgrass) under trial conditions. Green speed was fastest being cut at 3.5 mm and rolled (compared to 3.5 mm cut, no roll and 2.7 mm cut, no roll). • All trial sites reported the occurrence of disease in the Cynodon hybrids with the main incidence of disease occurring during the dormancy period (autumn and winter). The main disease issue reported was “patch diseases” which includes both Gaumannomyces and Rhizoctonia species. There was differences in the severity of the disease between cultivars, however, the severity of the disease was not consistent between cultivars and is largely attributed to an environment (location) effect. In terms of managing the occurrence of disease, the incidence of disease is less severe where there is a higher fertility rate (about 3 kgN/100m2/year) or a preventitatve fungicide program is adopted. • Cynodon hybrid and seashore paspalum cultivars maintained an acceptable to ideal surface being cut between 2.7 mm and 5.0 mm. “Ultradwarf” cultivars can tolerate mowing heights as low as 2.5 mm for short periods but places the plant under high levels of stress. Greens being maintained at a continually lower cutting height (e.g. 2.7 mm) of both species is achievable, but would need to be cut daily for best results. Seashore paspalums performed best when cut at a height of between 2.7 mm and 3.0 mm. If a lower cutting height is adopted, regular and repeated mowings are required to reduce scalping and produce a smooth surface. • At this point in time the optimum rate of nitrogen (N) for the Cynodon hybrids is 3 kg/100m2/year and while the seashore paspalums is 2 to 3 kg/100m2/year. • Dormancy occurred for all Cynodon and seashore paspalum culitvars from north in Brisbane (QLD) to south in Mornington Peninsula (VIC) and west to Novar Gardens (SA). Cynodon and Paspalum growth in both Victoria and South Australia was less favourable as a result of the cooler climates. • After combining the data collected from all eight sites, the results indicated that there can be variation (e.g. turfgrass quality, colour, disease resistance, performace) depending on the site and climatic conditions. Such evidence highlights the need to undertake genotype by environment (G x E) studies on new and old cultivars prior to conversion or establishment. • For a club looking to select either a Cynodon hybrid or seashore paspalum cultivar for use at their club they need to: - Review the research data. - Look at trial plots. - Inspect greens in play that have the new grasses. - Select 2 to 3 cultivars that are considered to be the better types. - Establish them in large (large enough to putt on) plots/nursery/practice putter. Ideally the area should be subjected to wear. - Maintain them exactly as they would be on the golf course/lawn bowls green. This is a critical aspect. Regular mowing, fertilising etc. is essential. - Assess them over at least 2 to 3 years. - Make a selection and establish it in a playing green so that it is subjected to typical wear.