{"help": "https://data.nsw.gov.au/data/api/3/action/help_show?name=package_show", "success": true, "result": {"author": "Department of Primary Industries", "author_email": null, "contact_info": "False", "contact_point": "nsw.agriculture@dpi.nsw.gov.au", "creator_user_id": "e7566293-9e02-472b-a047-be6af40e0fdd", "data_state": "inactive", "dctype": "Dataset", "id": "0b841d74-1da8-4b67-94a6-b9276ea7e6ea", "isopen": true, "jurisdiction": "NSW Government ", "language": "English", "license_id": "cc-by", "license_title": "Creative Commons Attribution", "license_url": "http://www.opendefinition.org/licenses/cc-by", "maintainer": null, "maintainer_email": null, "metadata_created": "2022-12-13T23:20:53.880010", "metadata_modified": "2022-12-14T01:06:57.025022", "name": "mtme-rice-breeding-data", "notes": "This data was used in the manuscript 'Genomic selection for genotype performance and stability using information on multiple traits and multiple environments' by J. Bancic, B. Ovenden, G. Gorjanc and D.J. Tolhurst. \r\n\r\nThis paper develops a single-stage genomic selection (GS) approach which incorporates information on multiple traits and multiple environments within a partially separable factor analytic framework. The factor analytic linear mixed model is an effective method for analysing multi-environment trial (MET) datasets, but is yet to be extended to GS for multiple traits and multiple environments. The advantage of using all sources of information is that breeders can utilise genotype by environment by trait interaction (GETI) to obtain more accurate predictions across correlated traits and environments. The partially separable factor analytic linear mixed model (SFA-LMM) developed in this paper is based on a three-way separable structure, which includes a factor analytic matrix between traits, a factor analytic matrix between environments and a genomic relationship matrix between genotypes. An additional specific variance matrix is then added to enable a different genotype by environment interaction (GEI) pattern for each trait and a different genotype by trait interaction (GTI) pattern for each environment. The results show that the SFA-LMM and all other factor analytic linear mixed models provide a better fit than the completely separable approaches. Selection from the SFA-LMM is then demonstrated using a selection index based on measures of genotype performance and stability. This research represents an important continuation in the advancement of plant breeding analyses, particularly with the advent of high-throughput phenotypic datasets involving a very large number of traits and environments.\r\n\r\nThese datasets include the phenotypic data, marker data and genomic relationship matrix used in the analysis. Phenotypic data includes grain yield, days to flowering, mature plant height and grain protein. Marker data was derived from Diversity Arrays next generation sequencing (DArTSeq).\r\n\r\nThis research was conducted as collaboration between The Roslin Institute (University of Edinburgh) and the Australian Rice Breeding Program. The Australian Rice Breeding Program is funded under the Australian Rice Partnership II project, a partnership between NSW Department of Primary Industries, AgriFutures and SunRice. ", "num_resources": 3, "num_tags": 8, "organization": {"id": "403a945c-a44d-412e-9f06-50cf89492ac0", "name": "department-of-primary-industries-dpi", "title": "Department of Primary Industries (DPI)", "type": "organization", "description": "DPI works to increase the value of primary industries and drive economic growth across NSW.\r\n\r\nAs part of the Department of Industry, DPI manages a broad range of initiatives including natural resource management, research and development, pest and disease management, food safety, industry engagement, and market access and competition.\r\n\r\nDPI\u2019s divisions include Agriculture, Fisheries, Biosecurity and Food Safety, Water, Land & Natural Resources, Strategy & Policy and Business Operations.\r\n\r\nSee: http://www.dpi.nsw.gov.au\r\n", "image_url": "2019-01-30-041840.426012DPI-logo-colour-rgb.jpg", "created": "2018-06-15T18:53:19.465872", "is_organization": true, "approval_status": "approved", "state": "active"}, "owner_org": "403a945c-a44d-412e-9f06-50cf89492ac0", "private": false, "spatial": "", "spatial_coverage": "New South Wales (NSW81093)", "state": "active", "syndicate": "true", "syndicated_id": "null", "temporal_coverage_from": "2016-10-01", "temporal_coverage_to": "2018-06-01", "title": "MTME Rice Breeding Data", "type": "dataset", "unpublished": "false", "update_freq": "never", "url": null, "version": null, "groups": [{"description": "One of the main elements of [Primary Industries](http://search.records.nsw.gov.au/functions/6) is agriculture, which involves the growing of crops and the raising of animals for domestic and export purposes. Agriculture is supported by the New South Wales Government through the provision of information, and carrying out research on a broad range of topics of relevance to the rural sector. These include the identification of pests (both plant and animal) and methods of eradication, the study of soil (including soil fertility and the prevention of erosion), irrigation methods, agricultural chemicals and efficient production methods for various types of crops and livestock. \r\n\r\nThe function covers the marketing of agricultural produce, and protection and regulation of the industries by providing or arranging financial assistance, preventing the spread of disease by quarantine, impounding animals and requiring notification of some diseases. The function also includes agricultural education, through the provision of specialised agricultural colleges and continuing education programs. \r\n\r\nThe term also covers the various activities associated with assisting the fisheries, forestry and mining industries. It includes the protection, development and regulation of these industries, setting standards, instigating research and marketing the products.", "display_name": "Primary Industries", "id": "3f4ee8ce-ea03-4927-a8db-57da52476311", "image_display_url": "", "name": "primary-industries", "title": "Primary Industries"}], "resources": [{"cache_last_updated": null, "cache_url": null, "ckan_url": "https://data.nsw.gov.au", "created": "2022-12-13T23:23:45.857763", "datastore_active": true, "datastore_contains_all_records_of_source_file": true, "description": "This genomic relationship matrix was constructed from the filtered and centred molecular marker data.", "format": "CSV", "hash": "3c108e8a119d2b4349c7e766c8042f4f", "id": "bc5fe0c1-47ab-4a3e-80d1-4c4b0e35c6ac", "ignore_hash": false, "last_modified": "2022-12-14T00:31:47.034204", "metadata_modified": "2022-12-14T00:31:52.038678", "mimetype": "text/csv", "mimetype_inner": null, "name": "Genomic Relationship Matrix", "original_url": "https://data.nsw.gov.au/data/dataset/0b841d74-1da8-4b67-94a6-b9276ea7e6ea/resource/bc5fe0c1-47ab-4a3e-80d1-4c4b0e35c6ac/download/grm1.csv", "package_id": "0b841d74-1da8-4b67-94a6-b9276ea7e6ea", "position": 0, "resource_id": "bc5fe0c1-47ab-4a3e-80d1-4c4b0e35c6ac", "resource_type": null, "set_url_type": false, "size": 894843, "state": "active", "task_created": "2022-12-14 00:31:47.261365", "tracking_summary": {"total": 19, "recent": 1}, "url": "https://data.nsw.gov.au/data/dataset/0b841d74-1da8-4b67-94a6-b9276ea7e6ea/resource/bc5fe0c1-47ab-4a3e-80d1-4c4b0e35c6ac/download/grm1.csv", "url_type": "upload"}, {"cache_last_updated": null, "cache_url": null, "created": "2022-12-13T23:25:10.876059", "datastore_active": true, "datastore_contains_all_records_of_source_file": false, "description": "This file contains filtered and centred marker data on 267 rice genotypes derived from DArTSeq genotyping. 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