Estimating Pasture Land Cover in the New England Region of Northern New South Wales

Land cover across the southern Australian temperate agricultural region comprises primarily of native pasture, introduced improved pastures and crops for livestock production and also perennial remnant vegetation. A feed-base pasture audit was carried out throughout southern Australia commencing mid-year 2011 (Donald and Burge 2012; Donald et al. 2012). The purpose of the audit was to map and analyse information obtained about the pasture feed-base for livestock production by surveying Statistical Local Areas (SLAs) across the southern states. The purpose of this Feed-Base audit was to survey pastures within agricultural NSW, Victoria, Tasmania, South Australia and South-Western Australia, collate these data into an organised database, and prepare a short report and summarise by tabulating and mapping pasture species abundance and distribution. Data collected were based on “desk-top estimates” by state district agronomists and agricultural consultants. In this paper a method using satellite imagery is described on how more objective assessments of pasture types can be provided as a means to discriminate between the SLA’s major pasture classes far more objectively than by visual assessment. Satellite remote sensing may be used to define landcover classes for large regional areas. A number of procedures have been developed to discriminate between pastures, crop and woody vegetation (for example Hill et al. 1997, Emelyanova et al. 2008). In the Hill study (Hill et al. 1997) NOAA AVHRR NDVI provided spatial land cover maps of pasture cover at 1 km resolution. The classifications results in that study showed that satellite information may be used to help in the interpretation of pasture survey results, and in turn, the survey data can provide some validation data for the pasture types ascribed to the remotely sensed classes. In this study daily temporal continental scale imagery from 250 m2 resolution TERRA and AQUA satellite Moderate Resolution Imaging Spectroradiometer (MODIS) normalised difference vegetation index (NDVI) composited into weekly continental images provided a means to assess temporal profile of spectral greenness over the growing season

Radiofrequency denervation for chronic back pain: a systematic review and meta-analysis

Objectives: To assess the effectiveness of radiofrequency denervation (RD) of lumbosacral anatomical targets for the management of chronic back pain. Design: Systematic review and meta-analysis of randomised controlled trials (RCTs). Methods: A database search (Medline, Medline in Process, Embase, CINHAL and the Cochrane library) was conducted from January 2014 to April 2019 for placebo or no-treatment controlled trials of RD for the management of chronic back pain. Included trials were quality assessed using the Cochrane Risk-of-Bias Tool and the quality of outcomes assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach. Meta-analysis was conducted to calculate mean difference (MD) in post-treatment Pain Score. Results: Nineteen RCTs were included in the review. There appears to be short-term pain relief (1–3 months) provided by RD of the sacroiliac joint (five trials, MD −1.53, CI −2.62 to 0.45) and intervertebral discs (four trials, MD −0.98, CI −1.84 to 0.12), but the placebo effect is large and additional intervention effect size is small (6 months) is uncertain. Conclusions: RD of selected lumbosacral targets appears to have a small, short-term, positive effect for the management of patients with chronic back pain. However, the quality of evidence for the majority of outcomes is low or very low quality and there is still a degree of uncertainty, particularly around the duration of effect

Assessing the impacts of the first year of rotavirus vaccination in the United Kingdom

The United Kingdom (UK) added rotavirus (RV) vaccine (Rotarix GlaxoSmithKline) to the national vaccine schedule in July 2013. During the 2012–2014 rotavirus seasons, children presenting to the Bristol Royal Hospital for Children Emergency Department with gastroenteritis symptoms had stool virology analysis (real-time PCR) and clinical outcome recorded. Nosocomial cases were identified as patients with non-gastroenteritis diagnosis testing positive for rotavirus > 48h after admission. In comparison to average pre-vaccine seasons, in the first year after vaccine introduction there were 48% fewer attendances diagnosed with gastroenteritis, 53% reduction in gastroenteritis admissions and a total saving of 330 bed-days occupancy. There was an overall reduction in number of rotavirus-positive stool samples with 94% reduction in children aged under one year and a 65% reduction in those too old to have been vaccinated. In the first year after the introduction of universal vaccination against rotavirus we observed a profound reduction in gastroenteritis presentations and admissions with a substantial possible herd effect seen in older children. Extrapolating these findings to the UK population we estimate secondary healthcare savings in the first year of ca £7.5 (€10.5) million. Ongoing surveillance will be required to determine the long-term impact of the RV immunisation programme

TeacherFX - Building the Capacity of STEM, Agriculture and Digital Technologies Teachers in Western Australia

Whilst agriculture is Australia’s fastest growing industry, the negative perception of career opportunities by high school students and the lack of educator confidence in teaching about food and fibre concepts is a major issue currently faced by the sector. The Teacher Farm Experience (TeacherFX), a joint program of Rabobank’s Western Australia Client Council and CQUniversity Australia, aims to increase awareness, knowledge and appreciation of the agricultural industry. This free two-day program designed for teachers entailed visiting four farms in the Great Southern region of WA on the first day and professional learning on the second day. Pre- and post- event surveys were conducted to gain baseline information on the participants, their perceptions of agriculture, quality of learning materials and reaction to the experience. Additional support in the form of professional development and networking opportunities was identified as required to assist teachers to implement learnings from TeacherFX. Event survey results were overwhelmingly positive, with 100% of teachers recommending their colleagues attend a future event. However, whether this positive result will translate to change in the classroom is unknown. Additional research needs to be conducted to measure the long-term impact of the program

Spatial Variability of Soil Phosphorus in Grazing Systems

Phosphorus (P) use efficiency has been identified as a key issue for Australian grazing systems. This project examined the spatial variability in soil P concentration from two separate surveys of grazed pasture fields. A field on the central tablelands of NSW had a range in Bray P of 1.2 to 140 mg/kg and a COV of 107%. The other field on the northern tablelands of NSW reported a range in Colwell P from 13.0 to 121.1 mg/kg and a COV of 59%. Maps of the spatial variability of soil P demonstrated that there is a relationship with field elevation. Application of critical P values to both fields enabled an estimation of the value of site specific fertiliser management. For one field, fertiliser inputs could potentially be isolated to 37% and the other 56% if nutrient additions were targeted at responsive areas. The opportunity for increased fertiliser use efficiency through site specific management (SSM) warrants further investigation. Research is required into both the value of SSM and the techniques that might enable the development of this strategy

SMARTFARM learning hub: Next generation precision agriculture technologies for agricultural education

Background The industry demands on higher education of agricultural students are rapidly changing. New precision agriculture technologies are revolutionizing the farming industry but the education sector is failing to keep pace. We report on the development of the SMARTfarm Learning Hub that will increase the skill base of students using a range of new agricultural technologies and innovations. The Hub is a world first; it links real industry technologies with educator resources and student learning packages. This gives higher education providers and their student’s online access to data and systems from commercial scale smart-farms across Australia and the world. Aims The SMARTfarm Learning Hub project will integrate infrastructure (web site and industry tools) with the development of case study learning modules, methodologies and templates to enable project communication. This will be undertaken in an action research context providing both research outcomes and critical feedback to improve the learning modules, educator and student experience. Description of intervention The SMARTfarm Learning Hub is based around a central landing page that provides links to cloud based technologies across Australia and the globe. Participating universities have farms with a diverse range of enterprises and environmental conditions from highly productive dairy systems in Tasmania to tropical beef production in North Queensland and the arid rangelands of New Mexico. This is real data from real agricultural landscapes, and is matched with learning materials developed to challenge student’s critical thinking and problem solving skills. Design and methods Selected learning modules will be evaluated under an action research methodology. Student engagement and attitudes will be assessed during delivery of learning modules in real classroom situations as they are integrated into teaching units through pre and post surveys and semi-structured interviews. A further study will be undertaken which determines employer perceptions of the value of certain skills gained by students through participation in SMARTfarm Learning Hub modules. This will involve quantitative assessment of employers’ perceptions through ranking of student CV’s (with and without various skills gained from the Hub) as well as qualitative assessment of the perceived value of these skills. Results Utilization of the SMARTfarm Learning Hub is tracked using the Square Space metrics tools. SMARTfarm Learning Hub web site was launched in mid-December 2015 and since this time has reached 890 unique visitors an average of 127 per month. Conclusions When fully developed, we expect the SMARTfarm Learning Hub will maximize transitions from secondary to tertiary study as it will become a point of commonality between different AQF levels with student familiarity providing confidence to move to the next level. In time, it is planned that specific learning packages will engage high school agriculture teachers in the development of their own landscape resources. Packages will be tailored so that schools are able to deploy some of the sensor platforms and technologies on their own school farms or on a local property to which they have ready access for field evaluation. There will be a strong focus on providing information regarding potential progression of study within the teaching materials developed

The interaction of silver(II) complexes with biological macromolecules and antioxidants

Silver is widely used for its antimicrobial properties, but microbial resistance to heavy metals is increasing. Silver(II) compounds are more oxidizing and therefore have the potential to overcome resistance via extensive attack on cellular components, but have traditionally been hard to stabilize for biological applications. Here, the high oxidation state cation was stabilised using pyridinecarboxylate ligands, of which the 2,6-dicarboxypyridine Ag(II) complex (Ag2,6P) was found to have the best tractability. This complex was found to be more stable in phosphate buffer than DMSO, allowing studies of its interaction with water soluble antioxidants and biological macromolecules, with the aim of demonstrating its potential to oxidize them, as well as determining the reaction products. Spectrophotometric analysis showed that Ag2,6P was rapidly reduced by the antioxidants glutathione, ascorbic acid and vitamin E; the unsaturated lipids arachidonic and linoleic acids, model carbohydrate β-cyclodextrin, and protein cytochrome c also reacted readily. Analysis of the reaction with glutathione by NMR and electrospray mass spectrometry confirmed that the glutathione was oxidized to the disulfide form. Mass spectrometry also clearly showed the addition of multiple oxygen atoms to the unsaturated fatty acids, suggesting a radical mechanism, and cross-linking of linoleic acid was observed. The seven hydroxyl groups of β-cyclodextrin were found to be completely oxidized to the corresponding carboxylates. Treatment of cytochrome c with Ag2,6P led to protein aggregation and fragmentation, and dose-dependent oxidative damage was demonstrated by oxyblotting. Thus Ag2,6P was found to be highly oxidizing to a wide variety of polar and nonpolar biological molecules

Opportunities and Barriers Perceived by Secondary School Agriculture Teachers in Implementing the GPS Cows Learning Module

Within the agriculture sector the use of digital technologies is rapidly expanding. There is a growing shortage of skilled people considering a career within this sector to support the uptake of agricultural technology. The GPS Cows program is designed to improve secondary school student’s knowledge and skills of emerging agricultural technologies. It highlights a range of opportunities and potential career options available to students in agriculture. This collaborative project combines the expertise and passion of researchers, industry professionals and educators in both Australia and the USA. A pilot workshop was run with ten teachers from nine Queensland and New South Wales secondary schools. Teachers participated in lectures and practical workshops, developed data analysis skills and took part in a World Café style focus group. The focus group findings highlighted that for the GPS Cows program to be implemented in secondary school classrooms, excellent resources from the GPS Cows team are needed, combined with ongoing support and guidance. Nevertheless, the participating teachers felt that their students would both engage and enjoy participating in the GPS Cows program and realise the opportunities the agricultural sector offers

Livestock vocalisation classification in farm soundscapes

Livestock vocalisations have been shown to contain information related to animal welfare and behaviour. Automated sound detection has the potential to facilitate a continuous acoustic monitoring system, for use in a range Precision Livestock Farming (PLF) applications. There are few examples of automated livestock vocalisation classification algorithms, and we have found none capable of being easily adapted and applied to different species' vocalisations. In this work, a multi-purpose livestock vocalisation classification algorithm is presented, utilising audio-specific feature extraction techniques, and machine learning models. To test the multi-purpose nature of the algorithm, three separate data sets were created targeting livestock-related vocalisations, namely sheep, cattle, and Maremma sheepdogs. Audio data was extracted from continuous recordings conducted on-site at three different operational farming enterprises, reflecting the conditions of real deployment. A comparison of Mel-Frequency Cepstral Coefficients (MFCCs) and Discrete Wavelet Transform-based (DWT) features was conducted. Classification was determined using a Support Vector Machine (SVM) model. High accuracy was achieved for all data sets (sheep: 99.29%, cattle: 95.78%, dogs: 99.67%). Classification performance alone was insufficient to determine the most suitable feature extraction method for each data set. Computational timing results revealed the DWT-based features to be markedly faster to produce (14.81 - 15.38% decrease in execution time). The results indicate the development of a highly accurate livestock vocalisation classification algorithm, which forms the foundation for an automated livestock vocalisation detection system

Developing a landscape risk assessment for the redheaded cockchafer ('Adoryphorus couloni') in dairy pastures using precision agriculture sensors

The redheaded cockchafer ('Adoryphorus couloni') (Burmeister) (RHC) is an important pest of semi-improved and improved pastures of south-eastern Australia. The third instar larvae of the RHC feed on the organic and root matter found in the soil causing reduced pasture growth and in severe cases death of plants. The control of the RHC is complicated by its lifecycle which involves the insect spending the majority of its life underground with only a brief time as an adult beetle flying. The RHC is particularly hard to control as there are no insecticides registered for use against the pest or any effective cultural control methods. ... This thesis aims to identify possible relationships between third instar RHC larvae with environmental variables which can be measured using precision agriculture sensors