Data

Mungbean UAV imagery

The University of Queensland
Dr Millicent Smith (Aggregated by) Dr Millicent Smith (Aggregated by) Miss Shanice Van Haeften (Aggregated by) Miss Shanice Van Haeften (Aggregated by) Miss Shanice Van Haeften (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:doi10.48610/62fc842&rft.title=Mungbean UAV imagery&rft.identifier=RDM ID: 71092160-1e1e-11ee-a910-a954a9d3366c&rft.publisher=The University of Queensland&rft.description=This study examined diverse mungbean accessions and varieties, and a mapping population across multiple filed trials conducted in 2021, 2022 and 2023 under rainfed conditions in Queensland, Australia. All trials were developed in a model-based row-column design using genetic relatedness (Cullis et al., 2020), which was implemented using the R statistical package ‘od’ (https://mmade.org/optimaldesign/). Regular UAV flights were conducted at the trial locations using a Matrice 300 RTK-DJI UAV fitted with a ‘MicaSense Altum-PT’ multispectral sensor. UAV flight altitudes were set at 20m and carried out on clear and still days between 10:00 to 11:00 AM local time to obtain high resolution raw images which were processed and stitched using Agisoft Metashape software. A single geo-referenced orthomosaic TIF image was generated per flight consisting of six channels (Blue, Green, Red, RedEdge, Near Infared and thermal). GRDC – Mungbean UAV Imagery – Orthomosaics folder has stitched multispectral images across the four sites (Warwick2021, Allora2022, Gatton2022, Gatton2023). In the 'Warwick2021' file there are 5 orthomosiacs, 'Allora2022' there are 9 orthomosiacs, 'Gatton2022' there are 8 orthomosaics and 'Gatton2023' there are 14 orthomosaics. Additional notes are also provided, including a timeline outlining when flights were undertaken at each trial (recorded in days after sowing; DAS), with S indicating Sowing, D indicating Desiccation and H indicating Harvest (if applicable). Naming convention for the files are as follows: Organisation_Trial_Crop_Date_Time_Sensor_Bands_Height_transparent_reflectance_packed.tif Additionally, each folder contains the relevant shapefiles (.shp) for each trial which segments out each individual plot in the trial. This shapefile includes data such as column, row and plot_id information. To find corresponding genotype for each plot_ID, you can refer to the excel document within each site folder.&rft.creator=Dr Millicent Smith&rft.creator=Dr Millicent Smith&rft.creator=Miss Shanice Van Haeften&rft.creator=Miss Shanice Van Haeften&rft.creator=Miss Shanice Van Haeften&rft.creator=Professor Lee Hickey&rft.creator=Professor Lee Hickey&rft.date=2023&rft_rights= http://guides.library.uq.edu.au/deposit_your_data/terms_and_conditions&rft_subject=eng&rft_subject=Mungbean&rft_subject=Mapping population&rft_subject=Unmanned Aerial Vehicle&rft_subject=Crop and pasture improvement (incl. selection and breeding)&rft_subject=Crop and pasture production&rft_subject=AGRICULTURAL, VETERINARY AND FOOD SCIENCES&rft.type=dataset&rft.language=English Access the data
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l.hickey@uq.edu.au
Queensland Alliance for Agriculture and Food Innovation

Full description

This study examined diverse mungbean accessions and varieties, and a mapping population across multiple filed trials conducted in 2021, 2022 and 2023 under rainfed conditions in Queensland, Australia. All trials were developed in a model-based row-column design using genetic relatedness (Cullis et al., 2020), which was implemented using the R statistical package ‘od’ (https://mmade.org/optimaldesign/). Regular UAV flights were conducted at the trial locations using a Matrice 300 RTK-DJI UAV fitted with a ‘MicaSense Altum-PT’ multispectral sensor. UAV flight altitudes were set at 20m and carried out on clear and still days between 10:00 to 11:00 AM local time to obtain high resolution raw images which were processed and stitched using Agisoft Metashape software. A single geo-referenced orthomosaic TIF image was generated per flight consisting of six channels (Blue, Green, Red, RedEdge, Near Infared and thermal). GRDC – Mungbean UAV Imagery – Orthomosaics folder has stitched multispectral images across the four sites (Warwick2021, Allora2022, Gatton2022, Gatton2023). In the 'Warwick2021' file there are 5 orthomosiacs, 'Allora2022' there are 9 orthomosiacs, 'Gatton2022' there are 8 orthomosaics and 'Gatton2023' there are 14 orthomosaics. Additional notes are also provided, including a timeline outlining when flights were undertaken at each trial (recorded in days after sowing; DAS), with S indicating Sowing, D indicating Desiccation and H indicating Harvest (if applicable). Naming convention for the files are as follows: Organisation_Trial_Crop_Date_Time_Sensor_Bands_Height_transparent_reflectance_packed.tif Additionally, each folder contains the relevant shapefiles (.shp) for each trial which segments out each individual plot in the trial. This shapefile includes data such as column, row and plot_id information. To find corresponding genotype for each plot_ID, you can refer to the excel document within each site folder.

Issued: 2023

Data time period: 2021 to 2023

Data time period: Data collected from: 2021-01-01T00:00:00Z
Data collected to: 2023-01-01T00:00:00Z

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Subjects
Agricultural, Veterinary and Food Sciences | Crop and Pasture Improvement (Incl. Selection and Breeding) | Crop and Pasture Production | Mapping population | Mungbean | Unmanned Aerial Vehicle | eng |

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local : UQ:289097

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local : UQ:06510ce

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