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dc.contributor.authorMariang, Ian
dc.contributor.authorRoth, Guy
dc.contributor.authorWhelan, Brett
dc.contributor.authorTredea, Annette
dc.coverage.spatialNarrabri, NSWen_AU
dc.coverage.temporal2019 - 2020en_AU
dc.date.accessioned2023-06-21T02:53:06Z
dc.date.available2023-06-21T02:53:06Z
dc.date.issued2023-06-21
dc.identifier.otherhandle
dc.identifier.urihttps://hdl.handle.net/2123/31374
dc.description.abstractThis collection consists of datasets and scripts from three main components: (1) observations, (2) APSIM sensitivity analysis results and (3) APSIM ensemble steered simulation Data Assimilation outputs. The observations are collected field data on plant status ( Leaf Area Index (m3/m3), Aboveground Biomass (kg/m2) and leaf N (%)), soil moisture readings, yield data, and height and reflectance values from remote sensing of two wheat cropping experiments (2019 and 2020) at four key phenological stages of wheat growth (booting, pre-anthesis, post-anthesis and grain filling). The experiment was conducted at the Plant Breeding Institute-USyD at Narrabri, NSW.en_AU
dc.format.mediumDigitalen_AU
dc.language.isoenen_AU
dc.relation.ispartofGRDC project number UOS1807-001RSXen_AU
dc.rightsOtheren_AU
dc.subjectCrop modelen_AU
dc.subjectyield predictionen_AU
dc.subjectwheaten_AU
dc.subjectremote sensingen_AU
dc.titleGRS - Optimising crop predicted and produced yield through an intuitive and cost-effective decision support tool.en_AU
dc.typeOtheren_AU
dc.subject.asrc300205, 200206, 401304en_AU
dc.rights.otherAvailable to third parties under terms and conditions to be agreed by owners.en_AU
dc.relation.otherGRDC
usyd.facultySeS faculties schools::Faculty of Science::Plant Breeding Instituteen_AU
usyd.facultySeS faculties schools::Faculty of Science::Sydney Institute of Agriculture (SIA)en_AU
workflow.metadata.onlyNoen_AU


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