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Environmental covariate data, envirotype classifications, and analysis code for wheat G×E and trialling efficiency in the Australian wheatbelt

The University of Queensland
Dr Javier Fernandez (Aggregated by) Dr Javier Fernandez (Aggregated by) Ms Carla Gho Brito (Aggregated by) Professor Scott Chapman (Aggregated by) Professor Scott Chapman (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.48610/b4394a5&rft.title=Environmental covariate data, envirotype classifications, and analysis code for wheat G×E and trialling efficiency in the Australian wheatbelt&rft.identifier=RDM ID: 8dc9cd5a-5ce4-4249-a908-dd5c79f8ae87&rft.publisher=The University of Queensland&rft.description=This dataset supports three related studies on genotype-by-environment (G×E) interaction, envirotyping, and trial network efficiency for wheat variety trials across the Australian wheatbelt: Evaluation of trialling efficiency of the Australian wheatbelt (Arief et al.); Envirotypes for wheat G×E in Australia: Integrating multiple environmental indices to characterise variety trials (Fernandez et al.); and Multiple-covariate random regression for improved yield prediction across the Australian wheatbelt (Ramakers et al.). It contains environmental covariate data derived for National Variety Trials (NVT) on wheat main season trials, envirotype classifications produced from these covariates, and the analysis code used to generate and validate these classifications, fit multiple-covariate random regression models, and evaluate trial network efficiency. Associated code is licensed under MIT License.&rft.creator=Dr Javier Fernandez&rft.creator=Dr Javier Fernandez&rft.creator=Ms Carla Gho Brito&rft.creator=Professor Scott Chapman&rft.creator=Professor Scott Chapman&rft.date=2026&rft_rights= https://guides.library.uq.edu.au/deposit-your-data/license-reuse-data-agreement&rft_subject=eng&rft_subject=Crop and pasture improvement (incl. selection and breeding)&rft_subject=Crop and pasture production&rft_subject=AGRICULTURAL, VETERINARY AND FOOD SCIENCES&rft_subject=Agricultural systems analysis and modelling&rft_subject=Agriculture, land and farm management&rft_subject=Statistical theory&rft_subject=Statistics&rft_subject=MATHEMATICAL SCIENCES&rft_subject=Environmental management&rft_subject=ENVIRONMENTAL SCIENCES&rft.type=dataset&rft.language=English Access the data
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[email protected]
School of Agriculture and Food Sustainability

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This dataset supports three related studies on genotype-by-environment (G×E) interaction, envirotyping, and trial network efficiency for wheat variety trials across the Australian wheatbelt: "Evaluation of trialling efficiency of the Australian wheatbelt" (Arief et al.); "Envirotypes for wheat G×E in Australia: Integrating multiple environmental indices to characterise variety trials" (Fernandez et al.); and "Multiple-covariate random regression for improved yield prediction across the Australian wheatbelt" (Ramakers et al.). It contains environmental covariate data derived for National Variety Trials (NVT) on wheat main season trials, envirotype classifications produced from these covariates, and the analysis code used to generate and validate these classifications, fit multiple-covariate random regression models, and evaluate trial network efficiency. Associated code is licensed under MIT License.

Issued: 22 09 2026

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Subjects
Agricultural, Veterinary and Food Sciences | Agricultural Systems Analysis and Modelling | Agriculture, Land and Farm Management | Crop and Pasture Improvement (Incl. Selection and Breeding) | Crop and Pasture Production | Environmental Sciences | Environmental Management | Mathematical Sciences | Statistical Theory | Statistics | eng |

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Identifiers
ACN 633 798 857