{"id":"https://openalex.org/W3087922632","doi":"https://doi.org/10.3390/rs12183104","title":"Using Machine Learning for Estimating Rice Chlorophyll Content from In Situ Hyperspectral Data","display_name":"Using Machine Learning for Estimating Rice Chlorophyll Content from In Situ Hyperspectral Data","publication_year":2020,"publication_date":"2020-09-22","ids":{"openalex":"https://openalex.org/W3087922632","doi":"https://doi.org/10.3390/rs12183104","mag":"3087922632"},"language":"en","primary_location":{"id":"doi:10.3390/rs12183104","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12183104","pdf_url":"https://www.mdpi.com/2072-4292/12/18/3104/pdf?version=1600773080","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/2072-4292/12/18/3104/pdf?version=1600773080","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017449474","display_name":"Gangqiang An","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gangqiang An","raw_affiliation_strings":["School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083693426","display_name":"Minfeng Xing","orcid":"https://orcid.org/0000-0002-5369-4638"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Minfeng Xing","raw_affiliation_strings":["Center for Information and Geoscience, University of Electronic Science and Technology of China, Chengdu 611731, China","School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China"],"raw_orcid":"https://orcid.org/0000-0002-5369-4638","affiliations":[{"raw_affiliation_string":"Center for Information and Geoscience, University of Electronic Science and Technology of China, Chengdu 611731, China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100671875","display_name":"Binbin He","orcid":"https://orcid.org/0000-0002-0668-6520"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Binbin He","raw_affiliation_strings":["Center for Information and Geoscience, University of Electronic Science and Technology of China, Chengdu 611731, China","School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Information and Geoscience, University of Electronic Science and Technology of China, Chengdu 611731, China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021411883","display_name":"Chunhua Liao","orcid":"https://orcid.org/0000-0002-5504-206X"},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Chunhua Liao","raw_affiliation_strings":["Department of Geography, Western University, London, ON N6A 5C2, Canada"],"raw_orcid":"https://orcid.org/0000-0002-5504-206X","affiliations":[{"raw_affiliation_string":"Department of Geography, Western University, London, ON N6A 5C2, Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016410509","display_name":"Xiaodong Huang","orcid":"https://orcid.org/0000-0002-3573-718X"},"institutions":[{"id":"https://openalex.org/I4210116398","display_name":"Applied GeoSolutions (United States)","ror":"https://ror.org/02gnmy268","country_code":"US","type":"company","lineage":["https://openalex.org/I4210116398"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaodong Huang","raw_affiliation_strings":["Applied Geosolutions, 15 Newmarket Road, Durham, NH 03824, USA"],"raw_orcid":"https://orcid.org/0000-0002-3573-718X","affiliations":[{"raw_affiliation_string":"Applied Geosolutions, 15 Newmarket Road, Durham, NH 03824, USA","institution_ids":["https://openalex.org/I4210116398"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083012711","display_name":"Jiali Shang","orcid":"https://orcid.org/0000-0001-9114-1500"},"institutions":[{"id":"https://openalex.org/I1331897569","display_name":"Agriculture and Agri-Food Canada","ror":"https://ror.org/051dzs374","country_code":"CA","type":"government","lineage":["https://openalex.org/I1331897569","https://openalex.org/I2802286613"]},{"id":"https://openalex.org/I4390039273","display_name":"Ottawa Research and Development Centre","ror":"https://ror.org/03fx3ra47","country_code":null,"type":"facility","lineage":["https://openalex.org/I1331897569","https://openalex.org/I2802286613","https://openalex.org/I4390039273"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jiali Shang","raw_affiliation_strings":["Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, 960 Carling Avenue, Ottawa, ON K1A 0C6, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, 960 Carling Avenue, Ottawa, ON K1A 0C6, Canada","institution_ids":["https://openalex.org/I1331897569","https://openalex.org/I4390039273"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102222378","display_name":"Haiqi Kang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210163526","display_name":"Sichuan Academy of Agricultural Sciences","ror":"https://ror.org/05f0php28","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210163526"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiqi Kang","raw_affiliation_strings":["Crop Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu 610066, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Crop Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu 610066, China","institution_ids":["https://openalex.org/I4210163526"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5083693426"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2784},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2784},"fwci":6.3874,"has_fulltext":false,"cited_by_count":91,"citation_normalized_percentile":{"value":0.97378696,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"12","issue":"18","first_page":"3104","last_page":"3104"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9947999715805054,"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"}},{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9923999905586243,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.777459442615509},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5476564168930054},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5394147038459778},{"id":"https://openalex.org/keywords/coefficient-of-determination","display_name":"Coefficient of determination","score":0.49755147099494934},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.457329124212265},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4377167224884033},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.4143664836883545},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.3429505228996277},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30270683765411377},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.28978195786476135},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.26524287462234497},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12795153260231018}],"concepts":[{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.777459442615509},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5476564168930054},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5394147038459778},{"id":"https://openalex.org/C128990827","wikidata":"https://www.wikidata.org/wiki/Q192830","display_name":"Coefficient of determination","level":2,"score":0.49755147099494934},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.457329124212265},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4377167224884033},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.4143664836883545},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3429505228996277},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30270683765411377},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.28978195786476135},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.26524287462234497},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12795153260231018}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs12183104","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12183104","pdf_url":"https://www.mdpi.com/2072-4292/12/18/3104/pdf?version=1600773080","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:doaj.org/article:5582f00c1f42480ab9a1b79c9ae176be","is_oa":true,"landing_page_url":"https://doaj.org/article/5582f00c1f42480ab9a1b79c9ae176be","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 12, Iss 18, p 3104 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/12/18/3104/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs12183104","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 12; Issue 18; Pages: 3104","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs12183104","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12183104","pdf_url":"https://www.mdpi.com/2072-4292/12/18/3104/pdf?version=1600773080","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":[{"score":0.800000011920929,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[{"id":"https://openalex.org/G5606453042","display_name":null,"funder_award_id":"2018YFD0200301","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8526509014","display_name":null,"funder_award_id":"41601373","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W3087922632.pdf"},"referenced_works_count":49,"referenced_works":["https://openalex.org/W633320881","https://openalex.org/W1191959449","https://openalex.org/W1277711400","https://openalex.org/W1502922572","https://openalex.org/W1972226951","https://openalex.org/W1990361669","https://openalex.org/W2001187551","https://openalex.org/W2006107700","https://openalex.org/W2020520344","https://openalex.org/W2024925469","https://openalex.org/W2039336203","https://openalex.org/W2063907334","https://openalex.org/W2072254696","https://openalex.org/W2080333585","https://openalex.org/W2089464686","https://openalex.org/W2095823889","https://openalex.org/W2097970470","https://openalex.org/W2098247895","https://openalex.org/W2102148524","https://openalex.org/W2113283209","https://openalex.org/W2125230412","https://openalex.org/W2128438912","https://openalex.org/W2129483042","https://openalex.org/W2142827986","https://openalex.org/W2148828119","https://openalex.org/W2158755893","https://openalex.org/W2159961845","https://openalex.org/W2167881994","https://openalex.org/W2408673549","https://openalex.org/W2492537454","https://openalex.org/W2539185528","https://openalex.org/W2715659545","https://openalex.org/W2754531448","https://openalex.org/W2789665835","https://openalex.org/W2791891890","https://openalex.org/W2859848446","https://openalex.org/W2889742210","https://openalex.org/W2890513934","https://openalex.org/W2910835070","https://openalex.org/W2911964244","https://openalex.org/W2918294784","https://openalex.org/W2945020384","https://openalex.org/W2945222626","https://openalex.org/W2987256200","https://openalex.org/W3015135619","https://openalex.org/W4250067071","https://openalex.org/W6643427982","https://openalex.org/W6757329102","https://openalex.org/W6762664141"],"related_works":["https://openalex.org/W2801661703","https://openalex.org/W4382982879","https://openalex.org/W4383721055","https://openalex.org/W4311044000","https://openalex.org/W2755828367","https://openalex.org/W2659933339","https://openalex.org/W2364784002","https://openalex.org/W2909099826","https://openalex.org/W4214620440","https://openalex.org/W4309845446"],"abstract_inverted_index":{"Chlorophyll":[0],"is":[1,225],"an":[2,17,34],"essential":[3],"pigment":[4],"for":[5,19,244],"photosynthesis":[6],"in":[7,37,48,58,148],"crops,":[8],"and":[9,23,53,83,116,128,144,155,171,183,205,217,235,237],"leaf":[10],"chlorophyll":[11,31,94,151,231,247],"content":[12,32,95,152,232,248],"can":[13],"be":[14],"used":[15,90],"as":[16],"indicator":[18],"crop":[20,30],"growth":[21],"status":[22],"help":[24],"guide":[25],"nitrogen":[26],"fertilizer":[27],"applications.":[28],"Estimating":[29],"plays":[33],"important":[35],"role":[36],"precision":[38],"agriculture.":[39],"In":[40],"this":[41],"study,":[42],"a":[43,98,226],"variable,":[44],"rate":[45],"of":[46,104,108,130,139,153,233,249],"change":[47],"reflectance":[49],"between":[50],"wavelengths":[51],"\u2018a\u2019":[52],"\u2018b\u2019":[54],"(RCRWa-b),":[55],"derived":[56],"from":[57],"situ":[59],"hyperspectral":[60],"remote":[61],"sensing":[62],"data":[63],"combined":[64],"with":[65],"four":[66,110,137],"advanced":[67],"machine":[68,111,241],"learning":[69,112,242],"techniques,":[70],"Gaussian":[71],"process":[72],"regression":[73,77,81,86],"(GPR),":[74],"random":[75],"forest":[76],"(RFR),":[78],"support":[79],"vector":[80],"(SVR),":[82],"gradient":[84],"boosting":[85],"tree":[87],"(GBRT),":[88],"were":[89,114,146],"to":[91,192,229],"estimate":[92,230],"the":[93,109,150,156,160,194,246],"(measured":[96],"by":[97],"portable":[99],"soil\u2013plant":[100],"analysis":[101],"development":[102],"meter)":[103],"rice.":[105,250],"The":[106,133,187],"performances":[107],"models":[113],"assessed":[115],"compared":[117],"using":[118],"root":[119],"mean":[120,124],"square":[121],"error":[122,126],"(RMSE),":[123],"absolute":[125],"(MAE),":[127],"coefficient":[129],"determination":[131],"(R2).":[132],"results":[134],"revealed":[135],"that":[136,223],"features":[138],"RCRWa-b,":[140],"RCRW551.0\u2013565.6,":[141],"RCRW739.5\u2013743.5,":[142],"RCRW684.4\u2013687.1":[143],"RCRW667.9\u2013672.0,":[145],"effective":[147],"estimating":[149,245],"rice,":[154,234],"RFR":[157,236],"model":[158,189],"generated":[159],"highest":[161],"prediction":[162],"accuracy":[163],"(training":[164,197],"set:":[165,176,198,210],"RMSE":[166,177,199,211],"=":[167,173,178,181,185,200,203,207,212,215,219],"1.54,":[168],"MAE":[169,180,202,214],"=1.23":[170],"R2":[172,184,206,218],"0.95;":[174],"validation":[175,209],"2.64,":[179],"1.99":[182],"0.80).":[186],"GPR":[188,238],"was":[190],"found":[191],"have":[193],"strongest":[195],"generalization":[196],"2.83,":[201],"2.16":[204],"0.77;":[208],"2.97,":[213],"2.30":[216],"0.76).":[220],"We":[221],"conclude":[222],"RCRWa-b":[224],"useful":[227],"variable":[228],"are":[239],"powerful":[240],"algorithms":[243]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2020-10-01T00:00:00"}
