Items where Subject is "Statistical software"

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Collard, B., Mace, E., McPhail, M., Wenzl, P., Cakir, M., Fox, G., Poulsen, D. and Jordan, D. (2009) How accurate are the marker orders in crop linkage maps generated from large marker datasets? Crop & Pasture Science, 60 (4). pp. 362-372.

Courtney, A. J., Campbell, A. B., Quinn, R., O'Neill, M. F., Campbell, M. J., Shen, J. and Emery, M. (2016) TrackMapper Rises. Project Report. Department of Agriculture and Fisheries, State of Queensland.

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Ergashev, A. (2019) Real Statistics for Policy-Makers: Exercises in the Queensland Context. Manual. State of Queensland.

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Hamilton, J. and Banney, S. (2011) Preliminary investigation into the development of an electronic forage budget and land condition application, for use on existing hand-held devices, for the northern grazing industry. Project Report. Meat & Livestock Australia Limited.

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Innes, D. J., Dillon, N. L., Smyth, H., Karan, M., Holton, T. A., Bally, I. S. E. and Dietzgen, R. G. (2015) Mangomics: Information Systems Supporting Advanced Mango Breeding. In: Genomics and Proteomics. Apple Academic Press. ISBN 978-1-77188-114-2

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Keller, B., Russo, T., Rembold, F., Chauhan, Y., Battilani, P., Wenndt, A. and Connett, M. (2021) The potential for aflatoxin predictive risk modelling in sub-Saharan Africa: a review. World Mycotoxin Journal, In pre . pp. 1-18. ISSN 1875-0710

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Merz, T., Hrabar, S., Kendoul, F. and Jeffery, M. (2016) Unmanned helicopter system for miconia weed surveys. In: 20th Australasian Weeds Conference.

Munroe, S., Guerin, G., Saleeba, T., Martín-Forés, I., Blanco-Martin, B., Sparrow, B. and Tokmakoff, A. (2021) ausplotsR: An R package for rapid extraction and analysis of vegetation and soil data collected by Australia's Terrestrial Ecosystem Research Network. Journal of Vegetation Science, 32 (3). e13046. ISSN 1100-9233

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O'Hallaran, J. (2019) Challenges and opportunities for PA adoption in vegetables. In: TropAg 2019 International Tropical Agriculture Conference - Shaping the Science of Tomorrow, 11 - 13 November 2019, Brisbane, Australia.

O'Hallaran, J. (2019) Using precision information systems for advanced decision making in vegetables. In: TropAg 2019 International Tropical Agriculture Conference - Shaping the Science of Tomorrow, 11 - 13 November 2019, Brisbane, Australia.

Ovenden, J., Street, R., Peel, D., Peel, S., Courtney, T., Podlich, H., Basford, K. and Dichmont, C. (2004) 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. Project Report. QO 04010. Department of Primary Industries & Fisheries. Queensland..

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Phan, T. D., Smart, J. C. R., Stewart-Koster, B., Sahin, O., Hadwen, W. L., Dinh, L. T., Tahmasbian, I. and Capon, S. J. (2019) Applications of Bayesian Networks as Decision Support Tools for Water Resource Management under Climate Change and Socio-Economic Stressors: A Critical Appraisal. Water, 11 (12). p. 2642. ISSN 2073-4441

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Robson, A., Abbott, C., Lamb, D. and Bramley, R. (2012) Developing sugar cane yield prediction algorithms from satellite imagery. In: 34th Annual Conference Australian Society of Sugar Cane Technologists, Cairns.

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Seyoum, S., Chauhan, Y., Rachaputi, R., Fekybelu, S. and Prasanna, B. (2017) Characterising production environments for maize in eastern and southern Africa using the APSIM Model. Agricultural and Forest Meteorology, 247 . pp. 445-453. ISSN 0168-1923

Srivastava, S. K., Lewis, T., Behrendorff, L. and Phinn, S. (2020) Spatial databases and techniques to assist with prescribed fire management in the south-east Queensland bioregion. International Journal of Wildland Fire, 30 (2). ISSN 1448-5516

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Van Sprang, C. (2019) Using precision information technologies to understand crop variability. In: TropAg 2019 International Tropical Agriculture Conference - Shaping the Science of Tomorrow, 11 - 13 November 2019, Brisbane, Australia.

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Wang, M., Thorp, G., Hofman, H., White, N., Wherritt, E. and Hanan, J. (2016) Pattern-oriented modelling of plant architecture: A new approach for constructing functional-structural plant models. In: IEEE International Conference on Functional-Structural Plant Growth Modeling, Simulation, Visualization and Applications (FSPMA), 7-11 Nov. 2016, Qingdao, China.