Data

Leaf and stripe rust field data for OzWheat diversity panel (V1 and V2)

Commonwealth Scientific and Industrial Research Organisation
Dodds, Peter ; McNeil, Meredith ; Mago, Rohit ; Perera, Geetha ; Dillon, Shannon ; Figueroa, Melania ; Hayes, Ben ; Yadav, Seema ; Dinglasan, Eric ; Sperschneider, Jana ; Hickey, Lee
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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:doi10.25919/2g6n-vq97&rft.title=Leaf and stripe rust field data for OzWheat diversity panel (V1 and V2)&rft.identifier=https://doi.org/10.25919/2g6n-vq97&rft.publisher=Commonwealth Scientific and Industrial Research Organisation&rft.description=This collection contains rust resistance phenotype data for two rust diseases, leaf (LR) and stripe rust or yellow rust (YR) collected from four different field sites within Australia of the OzWheat panel 1 and 2 in 2023 and 2024. This data was collected as part of GRDC project: ACRCP Phase 5: Optimising genetic control of wheat rusts through development of RustHapSelect (ref:CSP2304-013RTX). In this project we aim to validate a new approach to bring effective and durable rust resistance loci into elite high-yielding backgrounds much faster. This will ensure breeder take-up of this material free of deleterious background effects and increase adult plant resistance in Australian wheat varieties. Applying novel genomic selection techniques to identify resistance sources in two wheat diversity panels, Vavilov diversity panel (295 lines) and the OzWheat diversity panel (589 lines) and optimise crossing strategies to introgress into new cultivars. Lineage: The data was collected from 4 different field sites:1. Hermitage Research Facility, Dept Agriculture and Fisheries QLD (GPS coordinates 28°12'40''S, 152°06'06''E)2. DPIRD, Shenton Park, WA (GPS coordinates: 31°57′1.508″ S, 115°47′38.861″ E)3. Agriculture Victoria, Horsham, VIC (GPS coordinates: 33° 54' 23.2884S, 151° 55' 8.7384'' E)4. Plant Breeding Institute, University of Sydney, NSW (GPS: 34°01'07.4S, 150°40'24.4E) Best Linear Unbiased Estimates (BLUEs) were calculated from the phenotypic data using the method described in Yadav, S., Dillon, S., McNeil, M. et al. Optimising parent selection in plant breeding: comparing metaheuristic algorithms for genotype building. Theor Appl Genet 138, 242 (2025). Rust Pathotypes across sites and years is provided in the Excel file: Rust_Pathotypes_field_2023_2024_seasons.xlsx&rft.creator=Dodds, Peter &rft.creator=McNeil, Meredith &rft.creator=Mago, Rohit &rft.creator=Perera, Geetha &rft.creator=Dillon, Shannon &rft.creator=Figueroa, Melania &rft.creator=Hayes, Ben &rft.creator=Yadav, Seema &rft.creator=Dinglasan, Eric &rft.creator=Sperschneider, Jana &rft.creator=Hickey, Lee &rft.date=2026&rft.edition=v5&rft.relation=http://doi.org/10.1007/s00122-025-05028-1&rft.relation=https://www.biorxiv.org/content/10.1101/2025.09.22.677963v1&rft_rights=Creative Commons Attribution-ShareAlike 4.0 International Licence https://creativecommons.org/licenses/by-sa/4.0/&rft_rights=Data is accessible online and may be reused in accordance with licence conditions&rft_rights=All Rights (including copyright) CSIRO 2024.&rft_subject=leaf rust&rft_subject=stripe rust&rft_subject=wheat&rft_subject=phenotype&rft_subject=field&rft_subject=Crop and pasture protection (incl. pests, diseases and weeds)&rft_subject=Crop and pasture production&rft_subject=AGRICULTURAL, VETERINARY AND FOOD SCIENCES&rft_subject=Plant pathology&rft_subject=Plant biology&rft_subject=BIOLOGICAL SCIENCES&rft_subject=Plant biology not elsewhere classified&rft.type=dataset&rft.language=English Access the data

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Creative Commons Attribution-ShareAlike 4.0 International Licence
https://creativecommons.org/licenses/by-sa/4.0/

Data is accessible online and may be reused in accordance with licence conditions

All Rights (including copyright) CSIRO 2024.

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Full description

This collection contains rust resistance phenotype data for two rust diseases, leaf (LR) and stripe rust or yellow rust (YR) collected from four different field sites within Australia of the OzWheat panel 1 and 2 in 2023 and 2024. This data was collected as part of GRDC project: ACRCP Phase 5: Optimising genetic control of wheat rusts through development of RustHapSelect (ref:CSP2304-013RTX). In this project we aim to validate a new approach to bring effective and durable rust resistance loci into elite high-yielding backgrounds much faster. This will ensure breeder take-up of this material free of deleterious background effects and increase adult plant resistance in Australian wheat varieties. Applying novel genomic selection techniques to identify resistance sources in two wheat diversity panels, Vavilov diversity panel (295 lines) and the OzWheat diversity panel (589 lines) and optimise crossing strategies to introgress into new cultivars.
Lineage: The data was collected from 4 different field sites:
1. Hermitage Research Facility, Dept Agriculture and Fisheries QLD (GPS coordinates 28°12'40''S, 152°06'06''E)
2. DPIRD, Shenton Park, WA (GPS coordinates: 31°57′1.508″ S, 115°47′38.861″ E)
3. Agriculture Victoria, Horsham, VIC (GPS coordinates: 33° 54' 23.2884"S, 151° 55' 8.7384'' E)
4. Plant Breeding Institute, University of Sydney, NSW (GPS: 34°01'07.4"S, 150°40'24.4"E)

Best Linear Unbiased Estimates (BLUEs) were calculated from the phenotypic data using the method described in Yadav, S., Dillon, S., McNeil, M. et al. Optimising parent selection in plant breeding: comparing metaheuristic algorithms for genotype building. Theor Appl Genet 138, 242 (2025).

Rust Pathotypes across sites and years is provided in the Excel file: Rust_Pathotypes_field_2023_2024_seasons.xlsx

Available: 2026-02-16

Data time period: 2023-04-01 to 2027-06-30

This dataset is part of a larger collection

Other Information

Grains Research & Development Corporation (GRDC) : CSP2304-013RTX

ACN 633 798 857