Items where Subject is "Statistical software"

C

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.

D

Dahanayaka, B. A., Snyman, L., Vaghefi, N. and Martin, A. (2022) Using a Hybrid Mapping Population to Identify Genomic Regions of Pyrenophora teres Associated With Virulence. Frontiers in Plant Science, 13 . ISSN 1664-462X

Durrington, G., Brider, J., Holzworth, D., Hammer, G. L. and Wu, A. (2022) CropGen: A novel tool for optimising sorghum crop design. In: TropAg 2022 International Agriculture Conference, 31 October - 2 November 2022, Brisbane, Australia.

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

F

Forknall, C. R., Verbyla, A. P., Nazarathy, Y., Yousif, A., Osama, S., Jones, S. H., Kerr, E., Schulz, B. L., Fox, G. P. and Kelly, A. M. (2023) Covariance Clustering: Modelling Covariance in Designed Experiments When the Number of Variables is Greater than Experimental Units. Journal of Agricultural, Biological and Environmental Statistics . ISSN 1537-2693

G

George-Jaeggli, B., Zhi, X., Massey-Reed, S. R., Potgieter, A. B., Hunt, C. H., Watson, J., Chapman, S. C., Laws, K., Borrell, A., Tao, Y., Mace, E. S., Jordan, D. R., Van Oosterom, E. J., Hammer, G. L. and Wu, A. (2022) Deriving radiation use efficiency from hyperspectral sensing for enhanced sorghum production. In: TropAg 2022 International Agriculture Conference, 31 October - 2 November 2022, Brisbane, Australia.

Goswami, S. (2022) Using data to create value: Interactive market intelligence for export growth. In: TropAg 2022 International Agriculture Conference, 31 October - 2 November 2022, Brisbane, Australia.

H

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.

Holzworth, D.P., Huth, N.I. and de Voil, P.G. (2010) Simplifying environmental model reuse. Environmental Modelling and Software, 25 (2). pp. 269-275. ISSN 13648152 (ISSN)

I

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. (2022) The potential for aflatoxin predictive risk modelling in sub-Saharan Africa: a review. World Mycotoxin Journal, 15 (2). pp. 101-118. ISSN 1875-0710

Kerr, D. V., Cowan, R. T. and Chaseling, J. (1999) DAIRYPRO—a knowledge-based decision support system for strategic planning on sub-tropical dairy farms. I. System description. Agricultural Systems, 59 (3). pp. 245-255. ISSN 0308-521X

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Mayer, D. G., Kinghorn, B. P. and Archer, A. A. (2005) Differential evolution – an easy and efficient evolutionary algorithm for model optimisation. Agricultural Systems, 83 (3). pp. 315-328. ISSN 0308-521X

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

Mumford, M. H., Forknall, C. R., Rodriguez, D., Eyre, J. X. and Kelly, A. M. (2023) Incorporating environmental covariates to explore genotype × environment × management (G × E × M) interactions: A one-stage predictive model. Field Crops Research, 304 . p. 109133. ISSN 0378-4290

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). pp. 90-111. ISSN 1448-5516

Stone, G., Zhang, B., Carter, J., Fraser, G., Whish, G., Paton, C. and McKeon, G. (2021) An online system for calculating and delivering long-term carrying capacity information for Queensland grazing properties. Part 1: background and development. The Rangeland Journal, 43 (3). pp. 143-157.

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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, E., Robertson, M. J., Hammer, G. L., Carberry, P. S., Holzworth, D., Meinke, H., Chapman, S. C., Hargreaves, J. N. G., Huth, N. I. and McLean, G. (2002) Development of a generic crop model template in the cropping system model APSIM. European Journal of Agronomy, 18 (1). pp. 121-140. ISSN 1161-0301

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.

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Zhang, B., Fraser, G., Carter, J., Stone, G., Irvine, S., Whish, G., Willcocks, J. and McKeon, G. (2021) An online system for calculating and delivering long-term carrying capacity information for Queensland grazing properties. Part 2: modelling and outputs. The Rangeland Journal, 43 (3). pp. 159-172.