Significant features of the epidemiology of equine influenza in Queensland, Australia, 2007.

An outbreak of equine influenza (EI) caused by influenza A H3N8 subtype virus occurred in the Australian states of Queensland and New South Wales in August 2007. Infection in the Australian horse population was associated with the introduction of infection by horses from overseas. The first case of EI in Queensland was detected on 25 August 2007 at an equestrian sporting event. Infection subsequently spread locally and to other clusters through horse movements prior to the implementation of an official standstill. There were five main clusters of infected properties during this outbreak and several outliers, which were investigated to find the potential mechanism of disease spread. To contain the outbreak, Queensland was divided into infection status zones, with different movement controls applied to each zone. Vaccination was implemented strategically in infected areas and within horse subpopulations. Control and eventual eradication of EI from Queensland was achieved through a combination of quarantine, biosecurity measures, movement control, rapid diagnostic testing and vaccination.

The Application of Near Infrared Spectroscopy for the Assessment of Avocado Quality Attributes, Infrared Spectroscopy. Chapter 14

Quality and safety evaluation of agricultural products has become an increasingly important consideration in market/commercial viability and systems for such evaluations are now demanded by customers, including distributors and retailers. Unfortunately, most horticultural products struggle with delivering adequate and consistent quality to the consumer. Removing inconsistencies and providing what the consumer expects is a key factor for retaining and expanding both domestic and international markets. Most commercial quality classification systems for fruit and vegetables are based on external features of the product, for example: shape, colour, size, weight and blemishes. However, the external appearance of most fruit is generally not an accurate guide to the internal or eating quality of the fruit. Internal quality of fruit is currently subjectively judged on attributes such as volatiles, firmness, and appearance. Destructive subjective measures such as internal flesh colour, or objective measures such as extraction of juice to measure sweetness (oBrix) or assessment of dry matter (DM) content are also used, although obviously not for every fruit – just a sample to represent the whole consignment. For avocado fruit, external colour is not a maturity characteristic, and its smell is too weak and appears later in its maturity stage (Gaete-Garreton et al., 2005). Since maturity is a major component of avocado quality and palatability, it is important to harvest mature fruit, so as to ensure that fruit will ripen properly and have acceptable eating quality. Currently, commercial avocado maturity estimation is based on destructive assessment of the %DM, and sometimes percent oil, both of which are highly correlated with maturity (Clark et al., 2003; Mizrach & Flitsanov, 1999). Avocados Australia Limited (AAL (2008)) recommend a minimum maturity standard for its growers of 23 %DM (greater than 10% oil content) for the ‘Hass’ cultivar, although consumer studies indicate a preference for at least 25 %DM (Harker et al., 2007).

Genetic control of nodal root angle in sorghum and its implications on water extraction

Genotypic variability in root system architecture has been associated with root angle of seedlings and water extraction patterns of mature plants in a range of crops. The potential inclusion of root angle as a selection criterion in a sorghum breeding program requires (1) availability of an efficient screening method, (2) presence of genotypic variation with high heritability, and (3) an association with water extraction pattern. The aim of this study was to determine the feasibility for inclusion of nodal root angle as a selection criterion in sorghum breeding programs. A high-throughput phenotypic screen for nodal root angle in young sorghum plants has recently been developed and has been used successfully to identify significant variation in nodal root angle across a diverse range of inbred lines and a mapping population. In both cases, heritabilities for nodal root angle were high. No association between nodal root angle and plant size was detected. This implies that parental inbred lines could potentially be used to asses nodal root angle of their hybrids, although such predictability is compromised by significant interactions. To study effects of nodal root angle on water extraction patterns of mature plants, four inbred lines with contrasting nodal root angle at seedling stage were grown until at least anthesis in large rhizotrons. A consistent trend was observed that nodal root angle may affect the spatial distribution of root mass of mature plants and hence their ability to extract soil water, although genotypic differences were not significant. The potential implications of this for specific adaptation to drought stress are discussed. Results suggest that nodal root angle of young plants can be a useful selection criterion for specific drought adaptation, and could potentially be used in molecular breeding programs if QTLs for root angle can be identified. (C) 2012 Elsevier B.V. All rights reserved.

A flexible hierarchical approach for facial age estimation based on multiple features

Age estimation from facial images is increasingly receiving attention to solve age-based access control, age-adaptive targeted marketing, amongst other applications. Since even humans can be induced in error due to the complex biological processes involved, finding a robust method remains a research challenge today. In this paper, we propose a new framework for the integration of Active Appearance Models (AAM), Local Binary Patterns (LBP), Gabor wavelets (GW) and Local Phase Quantization (LPQ) in order to obtain a highly discriminative feature representation which is able to model shape, appearance, wrinkles and skin spots. In addition, this paper proposes a novel flexible hierarchical age estimation approach consisting of a multi-class Support Vector Machine (SVM) to classify a subject into an age group followed by a Support Vector Regression (SVR) to estimate a specific age. The errors that may happen in the classification step, caused by the hard boundaries between age classes, are compensated in the specific age estimation by a flexible overlapping of the age ranges. The performance of the proposed approach was evaluated on FG-NET Aging and MORPH Album 2 datasets and a mean absolute error (MAE) of 4.50 and 5.86 years was achieved respectively. The robustness of the proposed approach was also evaluated on a merge of both datasets and a MAE of 5.20 years was achieved. Furthermore, we have also compared the age estimation made by humans with the proposed approach and it has shown that the machine outperforms humans. The proposed approach is competitive with current state-of-the-art and it provides an additional robustness to blur, lighting and expression variance brought about by the local phase features.

Extraction methods in soil phosphorus characterisation : Limitations and applications

The quantification and characterisation of soil phosphorus (P) is of agricultural and environmental importance and different extraction methods are widely used to asses the bioavailability of P and to characterize soil P reserves. However, the large variety of extractants, pre-treatments and sample preparation procedures complicate the comparison of published results. In order to improve our understanding of the behaviour and cycling of P in soil, it is crucial to know the scientific relevance of the methods used for various purposes. The knowledge of the factors affecting the analytical outcome is a prerequisite for justified interpretation of the results. The aim of this thesis was to study the effects of sample preparation procedures on soil P and to determine the dependence of the recovered P pool on the chemical nature of extractants. Sampling is a critical step in soil testing and sampling strategy is dependent on the land-use history and the purpose of sampling. This study revealed that pre-treatments changed soil properties and air-drying was found to affect soil P, particularly extractable organic P, by disrupting organic matter. This was evidenced by an increase in the water-extractable small-sized (<0.2 µm) P that, at least partly, took place at the expense of the large-sized (>0.2 µm) P. However, freezing induced only insignificant changes and thus, freezing can be taken to be a suitable method for storing soils from the boreal zone that naturally undergo periodic freezing. The results demonstrated that chemical nature of the extractant affects its sensitivity to detect changes in soil P solubility. Buffered extractants obscured the alterations in P solubility induced by pH changes; however, water extraction, though sensitive to physicochemical changes, can be used to reveal short term changes in soil P solubility. As for the organic P, the analysis was found to be sensitive to the sample preparation procedures: filtering may leave a large proportion of extractable organic P undetected, whereas the outcome of centrifugation was found to be affected by the ionic strength of the extractant. Widely used sequential fractionation procedures proved to be able to detect land-use -derived differences in the distribution of P among fractions of different solubilities. However, interpretation of the results from extraction experiments requires better understanding of the biogeochemical function of the recovered P fraction in the P cycle in differently managed soils under dissimilar climatic conditions.

Temporal and spatial patterns of soil water extraction and drought resistance among genotypes of a perennial C-4 grass

The objective of this study was to investigate patterns of soil water extraction and drought resistance among genotypes of bermudagrass (Cynodon spp.) a perennial C-4 grass. Four wild Australian ecotypes (1-1, 25a1, 40-1, and 81-1) and four cultivars (CT2, Grand Prix, Legend, and Wintergreen) were examined in field experiments with rainfall excluded to monitor soil water extraction at 30-190 cm depths. In the study we defined drought resistance as the ability to maintain green canopy cover under drought. The most drought resistant genotypes (40-1 and 25a1) maintained more green cover (55-85% vs 5-10%) during water deficit and extracted more soil water (120-160 mm vs 77-107 mm) than drought sensitive genotypes, especially at depths from 50 to 110 cm, though all genotypes extracted water to 190 cm. The maintenance of green cover and higher soil water extraction were associated with higher stomatal conductance, photosynthetic rate and relative water content. For all genotypes, the pattern of water use as a percentage of total water use was similar across depth and time We propose the observed genetic variation was related to different root characteristics (root length density, hydraulic conductivity, root activity) although shoot sensitivity to drying soil cannot be ruled out.

Variation in water extraction with maize plant density and its impact on model application

The use of maize simulation models to determine the optimum plant population for rainfed environments allows the evaluation of plant populations over multiple years and locations at a lower cost than traditional field experimentation. However the APSIM maize model that has been used to conduct some of these 'virtual' experiments assumes that the maximum rate of soil water extraction by the crop root system is constant across plant populations. This untested assumption may cause grain yield to be overestimated in lower plant populations. A field experiment was conducted to determine whether maximum rates of water extraction vary with plant population, and the maximum rate of soil water extraction was estimated for three plant populations (2.4, 3.5 and 5.5 plants m(-2)) under water limited conditions. Maximum soil water extraction rates in the field experiment decreased linearly with plant population, and no difference was detected between plant populations for the crop lower limit of soil water extraction. Re-analysis of previous maize simulation experiments demonstrated that the use of inappropriately high extraction-rate parameters at low plant populations inflated predictions of grain yield, and could cause erroneous recommendations to be made for plant population. The results demonstrate the importance of validating crop simulation models across the range of intended treatments. (C) 2013 Elsevier E.V. All rights reserved.

Panel of real-time PCRs for the multiplexed detection of two tomato-infecting begomoviruses and their cognate whitefly vector species

A new approach for the simultaneous identification of the viruses and vectors responsible for tomato yellow leaf curl disease (TYLCD) epidemics is presented. A panel of quantitative multiplexed real-time PCR assays was developed for the sensitive and reliable detection of Tomato yellow leaf curl virus-Israel (TYLCV-IL), Tomato leaf curl virus (ToLCV), Bemisia tabaci Middle East Asia Minor 1 species (MEAM1, B biotype) and B.tabaci Mediterranean species (MED, Q biotype) from either plant or whitefly samples. For quality-assurance purposes, two internal control assays were included in the assay panel for the co-amplification of solanaceous plant DNA or B.tabaci DNA. All assays were shown to be specific and reproducible. The multiplexed assays were able to reliably detect as few as 10 plasmid copies of TYLCV-IL, 100 plasmid copies of ToLCV, 500fg B.tabaci MEAM1 and 300fg B.tabaci MED DNA. Evaluated methods for routine testing of field-collected whiteflies are presented, including protocols for processing B.tabaci captured on yellow sticky traps and for bulking of multiple B.tabaci individuals prior to DNA extraction. This work assembles all of the essential features of a validated and quality-assured diagnostic method for the identification and discrimination of tomato-infecting begomovirus and B.tabaci vector species in Australia. This flexible panel of assays will facilitate improved quarantine, biosecurity and disease-management programmes both in Australia and worldwide.

Optimisation of resin extraction from an Australian arid grass ‘Triodia pungens’ and its preliminary evaluation as an anti-termite timber coating

Spinifex grasses are the dominant vegetative component in Australian grassland habitats, covering approximately 26% of the Australian landmass. Our ongoing work explores the utility of both the cellulosic and resinous components of this abundant biomass for modern applications and a potential economy for our Aboriginal collaborators. This study is focused on the optimisation of a resin extraction process using solvent, and the subsequent evaluation, via a field trial, of the potential use and efficacy of the resin as an anti-termite coating material. Termiticidal performance was evaluated by re-dissolving the extracted resin in acetone and coating on pine timber blocks. The resin-coated and control blocks were then exposed to a colony of Mastotermes darwiniensis’ (Froggatt) termites, which are the most primitive alive and destructive species in subterranean area, at a trial site in northeast Australia, for six months. The results clearly showed that spinifex resin effectively protected the timber from termite attack, while the uncoated control samples were extensively damaged. By demonstrating an enhanced termite resistance, we here report that plant resins that are produced by arid/semi-arid grasses could be potentially used as treatments to prevent termite attack.

Robust features of future climate change impacts on sorghum yields in West Africa

West Africa is highly vulnerable to climate hazards and better quantification and understanding of the impact of climate change on crop yields are urgently needed. Here we provide an assessment of near-term climate change impacts on sorghum yields in West Africa and account for uncertainties both in future climate scenarios and in crop models. Towards this goal, we use simulations of nine bias-corrected CMIP5 climate models and two crop models (SARRA-H and APSIM) to evaluate the robustness of projected crop yield impacts in this area. In broad agreement with the full CMIP5 ensemble, our subset of bias-corrected climate models projects a mean warming of +2.8 °C in the decades of 2031–2060 compared to a baseline of 1961–1990 and a robust change in rainfall in West Africa with less rain in the Western part of the Sahel (Senegal, South-West Mali) and more rain in Central Sahel (Burkina Faso, South-West Niger). Projected rainfall deficits are concentrated in early monsoon season in the Western part of the Sahel while positive rainfall changes are found in late monsoon season all over the Sahel, suggesting a shift in the seasonality of the monsoon. In response to such climate change, but without accounting for direct crop responses to CO2, mean crop yield decreases by about 16–20% and year-to-year variability increases in the Western part of the Sahel, while the eastern domain sees much milder impacts. Such differences in climate and impacts projections between the Western and Eastern parts of the Sahel are highly consistent across the climate and crop models used in this study. We investigate the robustness of impacts for different choices of cultivars, nutrient treatments, and crop responses to CO2. Adverse impacts on mean yield and yield variability are lowest for modern cultivars, as their short and nearly fixed growth cycle appears to be more resilient to the seasonality shift of the monsoon, thus suggesting shorter season varieties could be considered a potential adaptation to ongoing climate changes. Easing nitrogen stress via increasing fertilizer inputs would increase absolute yields, but also make the crops more responsive to climate stresses, thus enhancing the negative impacts of climate change in a relative sense. Finally, CO2 fertilization would significantly offset the negative climate