{"id":"https://openalex.org/W4405552547","doi":"https://doi.org/10.3390/rs16244723","title":"Use Self-Training Random Forest for Predicting Winter Wheat Yield","display_name":"Use Self-Training Random Forest for Predicting Winter Wheat Yield","publication_year":2024,"publication_date":"2024-12-17","ids":{"openalex":"https://openalex.org/W4405552547","doi":"https://doi.org/10.3390/rs16244723"},"language":"en","primary_location":{"id":"doi:10.3390/rs16244723","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16244723","pdf_url":"https://www.mdpi.com/2072-4292/16/24/4723/pdf?version=1734523887","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/16/24/4723/pdf?version=1734523887","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112891253","display_name":"Yulin Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I157674565","display_name":"University of Li\u00e8ge","ror":"https://ror.org/00afp2z80","country_code":"BE","type":"education","lineage":["https://openalex.org/I157674565"]},{"id":"https://openalex.org/I27895137","display_name":"Gembloux Agro-Bio Tech","ror":"https://ror.org/00bmzhb16","country_code":"BE","type":"education","lineage":["https://openalex.org/I157674565","https://openalex.org/I27895137"]},{"id":"https://openalex.org/I4210093981","display_name":"Agricultural Information Institute","ror":"https://ror.org/00q62zf58","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210093981","https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]},{"id":"https://openalex.org/I4210138501","display_name":"Chinese Academy of Agricultural Sciences","ror":"https://ror.org/0313jb750","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]}],"countries":["BE","CN"],"is_corresponding":false,"raw_author_name":"Yulin Shen","raw_affiliation_strings":["Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China","TERRA, Biosystems Dynamics and Exchanges, Gembloux Agro-Bio Tech, University of Li\u00e8ge, 5030 Gembloux, Belgium"],"affiliations":[{"raw_affiliation_string":"Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China","institution_ids":["https://openalex.org/I4210093981","https://openalex.org/I4210138501"]},{"raw_affiliation_string":"TERRA, Biosystems Dynamics and Exchanges, Gembloux Agro-Bio Tech, University of Li\u00e8ge, 5030 Gembloux, Belgium","institution_ids":["https://openalex.org/I27895137","https://openalex.org/I157674565"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051334622","display_name":"Beno\u00eet Mercatoris","orcid":"https://orcid.org/0000-0002-3188-4772"},"institutions":[{"id":"https://openalex.org/I157674565","display_name":"University of Li\u00e8ge","ror":"https://ror.org/00afp2z80","country_code":"BE","type":"education","lineage":["https://openalex.org/I157674565"]},{"id":"https://openalex.org/I27895137","display_name":"Gembloux Agro-Bio Tech","ror":"https://ror.org/00bmzhb16","country_code":"BE","type":"education","lineage":["https://openalex.org/I157674565","https://openalex.org/I27895137"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Beno\u00eet Mercatoris","raw_affiliation_strings":["TERRA, Biosystems Dynamics and Exchanges, Gembloux Agro-Bio Tech, University of Li\u00e8ge, 5030 Gembloux, Belgium"],"affiliations":[{"raw_affiliation_string":"TERRA, Biosystems Dynamics and Exchanges, Gembloux Agro-Bio Tech, University of Li\u00e8ge, 5030 Gembloux, Belgium","institution_ids":["https://openalex.org/I27895137","https://openalex.org/I157674565"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006107034","display_name":"Qingzhi Liu","orcid":"https://orcid.org/0000-0003-2621-9222"},"institutions":[{"id":"https://openalex.org/I913481162","display_name":"Wageningen University & Research","ror":"https://ror.org/04qw24q55","country_code":"NL","type":"education","lineage":["https://openalex.org/I913481162"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Qingzhi Liu","raw_affiliation_strings":["Information Technology Group, Wageningen University and Research, 6704 Wageningen, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Information Technology Group, Wageningen University and Research, 6704 Wageningen, The Netherlands","institution_ids":["https://openalex.org/I913481162"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023274785","display_name":"Hongxun Yao","orcid":"https://orcid.org/0000-0003-3298-2574"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongxun Yao","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103123212","display_name":"Zongpeng Li","orcid":"https://orcid.org/0000-0002-6845-6878"},"institutions":[{"id":"https://openalex.org/I4210138501","display_name":"Chinese Academy of Agricultural Sciences","ror":"https://ror.org/0313jb750","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]},{"id":"https://openalex.org/I4210147183","display_name":"Farmland Irrigation Research Institute","ror":"https://ror.org/03j2cpb79","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210147183","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongpeng Li","raw_affiliation_strings":["Henan Key Laboratory of Water-Saving Agriculture, Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences, Xinxiang 453002, China"],"affiliations":[{"raw_affiliation_string":"Henan Key Laboratory of Water-Saving Agriculture, Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences, Xinxiang 453002, China","institution_ids":["https://openalex.org/I4210147183","https://openalex.org/I4210138501"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086967001","display_name":"Zhen Chen","orcid":"https://orcid.org/0000-0002-2847-0042"},"institutions":[{"id":"https://openalex.org/I4210138501","display_name":"Chinese Academy of Agricultural Sciences","ror":"https://ror.org/0313jb750","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]},{"id":"https://openalex.org/I4210147183","display_name":"Farmland Irrigation Research Institute","ror":"https://ror.org/03j2cpb79","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210147183","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhen Chen","raw_affiliation_strings":["Henan Key Laboratory of Water-Saving Agriculture, Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences, Xinxiang 453002, China"],"affiliations":[{"raw_affiliation_string":"Henan Key Laboratory of Water-Saving Agriculture, Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences, Xinxiang 453002, China","institution_ids":["https://openalex.org/I4210147183","https://openalex.org/I4210138501"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100720713","display_name":"Wensheng Wang","orcid":"https://orcid.org/0000-0002-8842-3432"},"institutions":[{"id":"https://openalex.org/I4210093981","display_name":"Agricultural Information Institute","ror":"https://ror.org/00q62zf58","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210093981","https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]},{"id":"https://openalex.org/I4210138501","display_name":"Chinese Academy of Agricultural Sciences","ror":"https://ror.org/0313jb750","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wensheng Wang","raw_affiliation_strings":["Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China"],"affiliations":[{"raw_affiliation_string":"Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China","institution_ids":["https://openalex.org/I4210093981","https://openalex.org/I4210138501"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5086967001"],"corresponding_institution_ids":["https://openalex.org/I4210138501","https://openalex.org/I4210147183"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":0.737,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.67953997,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"16","issue":"24","first_page":"4723","last_page":"4723"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.902899980545044,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.902899980545044,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.49011144042015076},{"id":"https://openalex.org/keywords/yield","display_name":"Yield (engineering)","score":0.48680374026298523},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.4418289363384247},{"id":"https://openalex.org/keywords/forestry","display_name":"Forestry","score":0.3454636037349701},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.18036961555480957},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1777244508266449},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.05913606286048889}],"concepts":[{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.49011144042015076},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.48680374026298523},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.4418289363384247},{"id":"https://openalex.org/C97137747","wikidata":"https://www.wikidata.org/wiki/Q38112","display_name":"Forestry","level":1,"score":0.3454636037349701},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.18036961555480957},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1777244508266449},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.05913606286048889},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs16244723","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16244723","pdf_url":"https://www.mdpi.com/2072-4292/16/24/4723/pdf?version=1734523887","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:library.wur.nl:wurpubs/639844","is_oa":true,"landing_page_url":"https://research.wur.nl/en/publications/use-self-training-random-forest-for-predicting-winter-wheat-yield","pdf_url":"https://edepot.wur.nl/684662","source":{"id":"https://openalex.org/S4210201231","display_name":"Socio-Environmental Systems Modeling","issn_l":"2663-3027","issn":["2663-3027"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISSN: 2072-4292","raw_type":"Article/Letter to editor"},{"id":"pmh:oai:doaj.org/article:5b1e138ef0c94ecf93ab71686c3b8f35","is_oa":true,"landing_page_url":"https://doaj.org/article/5b1e138ef0c94ecf93ab71686c3b8f35","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 16, Iss 24, p 4723 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs16244723","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16244723","pdf_url":"https://www.mdpi.com/2072-4292/16/24/4723/pdf?version=1734523887","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.7400000095367432}],"awards":[],"funders":[{"id":"https://openalex.org/F4320329860","display_name":"National Science and Technology Major Project","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4405552547.pdf","grobid_xml":"https://content.openalex.org/works/W4405552547.grobid-xml"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W2123234588","https://openalex.org/W2746791238","https://openalex.org/W3163590545","https://openalex.org/W3183350468","https://openalex.org/W4200170688","https://openalex.org/W4200400107","https://openalex.org/W4206381465","https://openalex.org/W4220683592","https://openalex.org/W4283387420","https://openalex.org/W4289653753","https://openalex.org/W4289731316","https://openalex.org/W4292454738","https://openalex.org/W4293086963","https://openalex.org/W4310875148","https://openalex.org/W4311612128"],"related_works":["https://openalex.org/W230091440","https://openalex.org/W2233261550","https://openalex.org/W2810751659","https://openalex.org/W258997015","https://openalex.org/W2997094352","https://openalex.org/W3216976533","https://openalex.org/W100620283","https://openalex.org/W2495260952","https://openalex.org/W4366179611","https://openalex.org/W2996078371"],"abstract_inverted_index":{"The":[0,94],"effectiveness":[1],"of":[2,38,56,104,107,112,126,129,134,147,150,155,165,168,171,176,204],"supervised":[3],"ML":[4,22,205],"heavily":[5],"depends":[6],"on":[7],"having":[8],"a":[9,18,32,47,53,190],"large,":[10],"accurate,":[11],"and":[12,90,110,132,153,174,192],"diverse":[13],"annotated":[14,42,57,197],"dataset,":[15,118,161],"which":[16],"poses":[17],"challenge":[19],"in":[20,115,144,158,207],"applying":[21],"for":[23,195],"yield":[24,210],"prediction.":[25],"To":[26],"address":[27],"this":[28],"issue,":[29],"we":[30,45],"developed":[31],"self-training":[33,185],"random":[34,48,141,186],"forest":[35,49,142,187],"algorithm":[36,188],"capable":[37],"automatically":[39,69],"expanding":[40,196],"the":[41,71,88,116,120,139,159,201],"dataset.":[43],"Specifically,":[44],"trained":[46],"regressor":[50],"model":[51,60,100],"using":[52],"small":[54],"amount":[55],"data.":[58],"This":[59],"was":[61],"then":[62],"utilized":[63],"to":[64],"generate":[65],"new":[66],"annotations,":[67],"thereby":[68,199],"extending":[70],"training":[72],"dataset":[73,122],"through":[74],"self-training.":[75],"Our":[76],"experiments":[77],"involved":[78],"collecting":[79],"data":[80],"from":[81],"over":[82],"30":[83],"winter":[84,208],"wheat":[85,209],"varieties":[86],"during":[87],"2019\u20132020":[89],"2021\u20132022":[91],"growing":[92],"seasons.":[93],"testing":[95],"results":[96,164,181],"indicated":[97],"that":[98,183],"our":[99,184],"achieved":[101],"an":[102,124,145,166],"R2":[103,125,146,167],"0.84,":[105],"RMSE":[106,128,149,170],"627.94":[108],"kg/ha,":[109,131,152,173],"MAE":[111,133,154,175],"516.94":[113],"kg/ha":[114,157],"test":[117,160],"while":[119],"validation":[121,163],"yielded":[123],"0.81,":[127,148],"692.96":[130],"550.62":[135],"kg/ha.":[136,178],"In":[137],"comparison,":[138],"standard":[140],"resulted":[143],"681.02":[151],"568.97":[156],"with":[162],"0.79,":[169],"736.24":[172],"585.85":[177],"Overall,":[179],"these":[180],"demonstrate":[182],"is":[189],"practical":[191],"effective":[193],"solution":[194],"datasets,":[198],"enhancing":[200],"prediction":[202],"accuracy":[203],"models":[206],"forecasting.":[211]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-08T06:56:09.383167","created_date":"2025-10-10T00:00:00"}
