date: 2017-01-24T11:21:27Z pdf:PDFVersion: 1.7 pdf:docinfo:title: A network-based approach for semi-quantitative knowledge mining and its application to yield variability xmp:CreatorTool: IOPP access_permission:can_print_degraded: true subject: Environmental Research Letters, 11(2016) 123001. doi:10.1088/1748-9326/11/12/123001 crossmarkMajorVersionDate: 2016-11-28 dc:format: application/pdf; version=1.7 pdf:docinfo:custom:robots: noindex pdf:docinfo:creator_tool: IOPP access_permission:fill_in_form: true pdf:encrypted: false dc:title: A network-based approach for semi-quantitative knowledge mining and its application to yield variability modified: 2017-01-24T11:21:27Z cp:subject: Environmental Research Letters, 11(2016) 123001. doi:10.1088/1748-9326/11/12/123001 pdf:docinfo:custom:CrossMarkDomains[1]: iop.org robots: noindex pdf:docinfo:subject: Environmental Research Letters, 11(2016) 123001. doi:10.1088/1748-9326/11/12/123001 pdf:docinfo:custom:crossmarkMajorVersionDate: 2016-11-28 pdf:docinfo:creator: Bernhard Schauberger meta:author: Susanne Rolinski meta:creation-date: 2016-11-25T16:21:27Z created: 2016-11-25T16:21:27Z access_permission:extract_for_accessibility: true Creation-Date: 2016-11-25T16:21:27Z pdf:docinfo:custom:doi: 10.1088/1748-9326/11/12/123001 Author: Susanne Rolinski producer: iText® 5.5.10 ©2000-2015 iText Group NV (AGPL-version) pdf:docinfo:producer: iText® 5.5.10 ©2000-2015 iText Group NV (AGPL-version) doi: 10.1088/1748-9326/11/12/123001 pdf:unmappedUnicodeCharsPerPage: 0 dc:description: Environmental Research Letters, 11(2016) 123001. doi:10.1088/1748-9326/11/12/123001 Keywords: yield variability; crop models; interaction network; plant process; wheat; maize; rice access_permission:modify_annotations: true dc:creator: Susanne Rolinski description: Environmental Research Letters, 11(2016) 123001. doi:10.1088/1748-9326/11/12/123001 dcterms:created: 2016-11-25T16:21:27Z Last-Modified: 2017-01-24T11:21:27Z dcterms:modified: 2017-01-24T11:21:27Z title: A network-based approach for semi-quantitative knowledge mining and its application to yield variability xmpMM:DocumentID: uuid:28853871-0747-467c-8413-1f499574495e Last-Save-Date: 2017-01-24T11:21:27Z CrossMarkDomains[1]: iop.org pdf:docinfo:keywords: yield variability; crop models; interaction network; plant process; wheat; maize; rice pdf:docinfo:modified: 2017-01-24T11:21:27Z meta:save-date: 2017-01-24T11:21:27Z Content-Type: application/pdf X-Parsed-By: org.apache.tika.parser.DefaultParser creator: Susanne Rolinski dc:subject: yield variability; crop models; interaction network; plant process; wheat; maize; rice access_permission:assemble_document: true xmpTPg:NPages: 17 pdf:charsPerPage: 269 access_permission:extract_content: true access_permission:can_print: true meta:keyword: yield variability; crop models; interaction network; plant process; wheat; maize; rice access_permission:can_modify: true pdf:docinfo:created: 2016-11-25T16:21:27Z