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University of Adelaide National Sodic field trial reference dataset for GRDC Machine Learning Project- UOA2002-007RTX.

Adelaide University
David, Rakesh ; Schilling, Rhiannon
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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:doi10.25909/19246104.v2&rft.title=University of Adelaide National Sodic field trial reference dataset for GRDC Machine Learning Project- UOA2002-007RTX.&rft.identifier=10.25909/19246104.v2&rft.publisher=The University of Adelaide&rft.description=The collection includes raw and processed data for machine learning compliance. Includes data from the National Sodic Field Trials - 16 wheat varieties grown at two sites with sodic subsoils - Mallala and Roseworthy (368 plots), spanning 2017-2019. Raw data available as excel includes soil cores information, grain yield, biomass, plant physiology, tolerance sensitive traits, genetic markers. In addition to the raw data the collection includes pre-processed versions of the dataset compliant with machine learning analytics.UA and External funding agency data collection. Please contact Rhiannon Schilling (PIRSA-SARDI) [email protected] to request access to data&rft.creator=David, Rakesh &rft.creator=Schilling, Rhiannon &rft.edition=2&rft_rights= https://www.adelaide.edu.au/library/restricted-access&rft_subject=Agronomy&rft_subject=Crop and pasture improvement (incl. selection and breeding)&rft_subject=SODIC SOILS&rft_subject=Field trial data&rft_subject=Wheat&rft.type=dataset&rft.language=English Access the data
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The collection includes raw and processed data for machine learning compliance. Includes data from the National Sodic Field Trials - 16 wheat varieties grown at two sites with sodic subsoils - Mallala and Roseworthy (368 plots), spanning 2017-2019. Raw data available as excel includes soil cores information, grain yield, biomass, plant physiology, tolerance sensitive traits, genetic markers. In addition to the raw data the collection includes pre-processed versions of the dataset compliant with machine learning analytics.

UA and External funding agency data collection. Please contact Rhiannon Schilling (PIRSA-SARDI) [email protected] to request access to data

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Subjects
Agronomy | Crop and pasture improvement (incl. selection and breeding) | Field trial data | SODIC SOILS | Wheat |

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Identifiers
ACN 633 798 857