A rapid non-destructive DNA extraction method for insects and other arthropods

Preparation of arthropods for morphological identification often damages or destroys DNA within the specimen. Conversely, DNA extraction methods often destroy the external physical characteristics essential for morphological identification. We have developed a rapid, simple and non-destructive DNA extraction technique for arthropod specimens. This technique was tested on four arthropod orders, using specimens that were fresh, preserved by air drying, stored in ethanol, or collected with sticky or propylene glycol traps. The technique could be completed in twenty minutes for Coleoptera, Diptera and Hemiptera, and two minutes for the subclass Acarina, without significant distortion, discolouration, or other damage to the specimens

Development of risk maps to minimize uranium exposures in the Navajo Churchrock mining district

© 2009 deLemos et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

An Evaluation of Parent Preference for Prompting Procedures

Parent participation in intervention can enhance intervention efficacy and promote generalization of skills across settings. Thus, parents should be trained to implement behavioral interventions. The purpose of the current investigation was to evaluate parent preference for and acceptability of 3 commonly used prompting procedures. We trained parents of children with disabilities to use 3 empirically validated prompting strategies (i.e., least‐to‐most, most‐to‐least, and a progressive‐prompt delay). Once the parent reached the mastery criteria with each prompting procedure, we evaluated his/her preference for each of the procedures using a concurrent‐chains arrangement. We also measured treatment acceptability of all procedures throughout the study. All participants met the mastery criteria for each of the prompting procedures and showed a preference for least‐to‐most prompting. Results suggest parents\u27 acceptability of procedures prior to training were different than posttraining/post‐child practice. In addition, acceptability rating scores obtained at the end of the investigation corresponded to preference of intervention during the concurrent‐chains arrangement. The results demonstrate the benefits of objective measures for studying preference for behavioral, skill‐acquisition procedures

Crop Updates 2010 - Crop Specific

This session covers twenty four papers from different authors: PLENARY 1. Challenges facing western Canadian cropping over the next 10 years, Hugh J Beckie, Research Centre, Agriculture and Agri-Food Canada, Saskatoon, Saskatchewan CROP SPECIFIC Breeding 2. The challenge of breeding canola hybrids – new opportunities for WA growers, Wallace Cowling, Research Director, Canola Breeders Western Australia Pty Ltd 3. Chickpea 2009 crop variety testing of germplasm developed by DAFWA/CLIMA/ICRISAT/COGGO alliance. Khan, TN1,3, Adhikari, K1,3, Siddique, K2, Garlinge, J1, Smith, L1, Morgan, S1 and Boyd, C1 1Department of Agriculture and Food, Western Australia (DAFWA), 2Insititute of Agriculture, The University of Western Australia (UWA), 3Centre for Legumes in Mediterranean Agriculture (CLIMA), The University of Western Australia 4. PBA Pulse Breeding Australia – 2009 Field Pea Results, Ian Pritchard1, Chris Veitch1, Colin Boyd1, Stuart Morgan1, Alan Harris1 and Tony Leonforte2, 1Department of Agriculture and Food, Western Australia, 2Department of Primary Industries, Victoria 5. PBA Pulse Breeding Australia – 2009 Chickpea Results, Ian Pritchard1, Chris Veitch1, Colin Boyd1, Murray Blyth1, Shari Dougal1 and Kristy Hobson2 1Department of Agriculture and Food, Western Australia, 2Department of Primary Industries, Victoria Decision Support 6. A tool for identifying problems in wheat paddocks, Ben Curtis and Doug Sawkins, Department of Agriculture and Food 7. DAFWA Seasonal Forecast for 2010, Stephens, D, Department of Agriculture and Food, Western Australian, Climate and Modelling Group Disease 8. Enhancement of black spot resistance in field pea, Kedar Adhikari, T Khan, S Morgan and C Boyd, Department of Agriculture and Food, 9. fungicide management of yellow spot in wheat, Ciara Beard, Kith Jayasena, Kazue Tanaka and Anne Smith, Department of Agriculture and Food 10. Resistance to infection by Beet western yellows virus in four Australian canola varieties, Brenda Coutts and Roger Jones, Department of Agriculture and Food 11. Yellow spot carryover risk from stubble in wheat-on-wheat rotations, Jean Galloway, Pip Payne and Tess Humphreys, Department of Agriculture and Food 12. Fungicides for the future: Management of Barley Powdery Mildew and Leaf Rust, Kith Jayasena, Kazue Tanaka and William MacLeod, Department of Agriculture and Food 13. 2009 canola disease survey and management options for blackleg and Sclerotinia in 2010, Ravjit Khangura, WJ MacLeod, M Aberra and H Mian, Department of Agriculture and Food 14. Impact of variety and fungicide on carryover of stubble borne inoculum and yellow spot severity in continuous wheat cropping, Geoff Thomas, Pip Payne, Tess Humphreys and Anne Smith, Department of Agriculture and Food 15. Limitations to the spread of Wheat streak mosaic virus by the Wheat curl mite in WA during 2009, Dusty Severtson, Peter Mangano, Brenda Coutts, Monica Kehoe and Roger Jones, Department of Agriculture and Food 16. Viable solutions for barley powdery mildew, Madeline A. Tucker, Australian Centre for Necrotrophic Fungal Pathogens, Murdoch University Marketing 17. The importance of varietal accreditation in a post-deregulation barley marketing environment, Neil Barker, Barley Australia 18. Can Australia wheat meet requirements for a new middle east market? Robert Loughman, Larisa Cato, Department of Agriculture and Food, and Ken Quail, BRI Australia VARIETY PERFORMANCE 19. Sowing rate and time for hybrid vs open-pollinated canola, Mohammad Amjad and Mark Seymour, Department of Agriculture and Food 20. HYOLA® National Hybrid vs OP Canola Hybrid F1 vs Retained Seed Generation Trial Results and recommendations for growers, Justin Kudnig, Mark Thompson, Anton Mannes, Michael Uttley, Chris Fletcher, Andrew Etherton, Nick Joyce and Kate Light, Pacific Seeds Australia 21. HYOLA® National Hybrid vs OP Canola Sowing Rate Trial Results and plant population recommendations for Australian growers, Justin Kudnig, Mark Thompson, Anton Mannes, Michael Uttley, Andrew Etherton, Chris Fletcher, Nick Joyce and Kate Light, Pacific Seeds Australia; Peter Hamblin, Agritech Research Young, NSW, Michael Lamond, Agrisearch, York, Western Australia 22. Desi chickpea agronomy for 2010, Alan Meldrum, Pulse Australia and Wayne Parker, Department of Agriculture and Food 23. New wheat varieties – exploit the benefits and avoid the pitfalls, Steve Penny, Sarah Ellis, Brenda Shackley, Christine Zaicou, Shahajahan Miyan, Darshan Sharma and Ben Curtis, Department of Agriculture and Food 24. The influence of genetics and environment on the level of seed alkaloid in narrow-leafed lupins, Greg Shea1, Bevan Buirchell1, David Harris2 and Bob French1, 1Department of Agriculture and Food, 2ChemCentr

Biomedical informatics and translational medicine

Biomedical informatics involves a core set of methodologies that can provide a foundation for crossing the "translational barriers" associated with translational medicine. To this end, the fundamental aspects of biomedical informatics (e.g., bioinformatics, imaging informatics, clinical informatics, and public health informatics) may be essential in helping improve the ability to bring basic research findings to the bedside, evaluate the efficacy of interventions across communities, and enable the assessment of the eventual impact of translational medicine innovations on health policies. Here, a brief description is provided for a selection of key biomedical informatics topics (Decision Support, Natural Language Processing, Standards, Information Retrieval, and Electronic Health Records) and their relevance to translational medicine. Based on contributions and advancements in each of these topic areas, the article proposes that biomedical informatics practitioners ("biomedical informaticians") can be essential members of translational medicine teams

Unmanned aerial vehicle canopy reflectance data detects potassium deficiency and green peach aphid susceptibility in canola

There is growing evidence that potassium deficiency in crop plants increases their susceptibility to herbivorous arthropods. The ability to remotely detect potassium deficiency in plants would be advantageous in targeting arthropod sampling and spatially optimizing potassium fertilizer to reduce yield loss due to the arthropod infestations. Four potassium fertilizer regimes were established in field plots of canola, with soil and plant nutrient concentrations tested on three occasions: 69 (seedling), 96 (stem elongation), and 113 (early flowering) days after sowing (DAS). On these dates, unmanned aerial vehicle (UAV) multi-spectral images of each plot were acquired at 15 and 120 m above ground achieving spatial (pixel) resolutions of 8.1 and 65 mm, respectively. At 69 and 96 DAS, field plants were transported to a laboratory with controlled lighting and imaged with a 240-band (390–890 nm) hyperspectral camera. At 113 DAS, all plots had become naturally infested with green peach aphids (Hemiptera: Aphididae), and intensive aphid counts were conducted. Potassium deficiency caused significant: (1) increase in concentrations of nitrogen in youngest mature leaves, (2) increase in green peach aphid density, (3) decrease in vegetation cover, (4) decrease in normalized difference vegetation indices (NDVI) and decrease in canola seed yield. UAV imagery with 65 mm spatial resolution showed higher classification accuracy (72–100 %) than airborne imagery with 8 mm resolution (69–94 %), and bench top hyperspectral imagery acquired from field plants in laboratory conditions (78–88 %). When non-leaf pixels were removed from the UAV data, classification accuracies increased for 8 mm and 65 mm resolution images acquired 96 and 113 DAS. The study supports findings that UAV-acquired imagery has potential to identify regions containing nutrient deficiency and likely increased arthropod performance

Unmanned aerial vehicle canopy reflectance data detects potassium deficiency and green peach aphid susceptibility in canola

There is growing evidence that potassium deficiency in crop plants increases their susceptibility to herbivorous arthropods. The ability to remotely detect potassium deficiency in plants would be advantageous in targeting arthropod sampling and spatially optimizing potassium fertilizer to reduce yield loss due to the arthropod infestations. Four potassium fertilizer regimes were established in field plots of canola, with soil and plant nutrient concentrations tested on three occasions: 69 (seedling), 96 (stem elongation), and 113 (early flowering) days after sowing (DAS). On these dates, unmanned aerial vehicle (UAV) multi-spectral images of each plot were acquired at 15 and 120 m above ground achieving spatial (pixel) resolutions of 8.1 and 65 mm, respectively. At 69 and 96 DAS, field plants were transported to a laboratory with controlled lighting and imaged with a 240-band (390–890 nm) hyperspectral camera. At 113 DAS, all plots had become naturally infested with green peach aphids (Hemiptera: Aphididae), and intensive aphid counts were conducted. Potassium deficiency caused significant: (1) increase in concentrations of nitrogen in youngest mature leaves, (2) increase in green peach aphid density, (3) decrease in vegetation cover, (4) decrease in normalized difference vegetation indices (NDVI) and decrease in canola seed yield. UAV imagery with 65 mm spatial resolution showed higher classification accuracy (72–100 %) than airborne imagery with 8 mm resolution (69–94 %), and bench top hyperspectral imagery acquired from field plants in laboratory conditions (78–88 %). When non-leaf pixels were removed from the UAV data, classification accuracies increased for 8 mm and 65 mm resolution images acquired 96 and 113 DAS. The study supports findings that UAV-acquired imagery has potential to identify regions containing nutrient deficiency and likely increased arthropod performance

Application of a Mechanistic Model to Explore Management Strategies for Biological Control of an Agricultural Pest

Despite the known benefits of integrated pest management, adoption in Australian broadacre crops has been slow, in part due to the lack of understanding about how pests and natural enemies interact. We use a previously developed process-based model to predict seasonal patterns in the population dynamics of a canola pest, the green peach aphid (Myzus persicae), and an associated common primary parasitic wasp (Diaeretiella rapae), found in this cropping landscape. The model predicted aphid population outbreaks in autumn and spring. Diaeretiella rapae was able to suppress these outbreaks, but only in scenarios with a sufficiently high number of female wasps in the field (a simulated aphid:wasp density ratio of at least 5:1 was required). Model simulations of aphid-specific foliar pesticide applications facilitated biological control. However, a broad-spectrum pesticide negated the control provided by D. rapae, in one case leading to a predicted 15% increase in aphid densities compared to simulations in which no pesticide was applied. Biological and chemical control could therefore be used in combination for the successful management of the aphid while conserving the wasp. This modelling framework provides a versatile tool for further exploring how chemical applications can impact pests and candidate species for biological control.Madeleine G. Barton, Hazel Parry, Paul A. Umina, Matthew R. Binns, Thomas Heddle, Ary A. Hoffmann, Joanne Holloway, Dustin Severtson, Maarten Van Helden, Samantha Ward, Rachel Wood, and Sarina Macfadye