{"id":"https://openalex.org/W4402768574","doi":"https://doi.org/10.3390/s24186111","title":"Estimation Model for Maize Multi-Components Based on Hyperspectral Data","display_name":"Estimation Model for Maize Multi-Components Based on Hyperspectral Data","publication_year":2024,"publication_date":"2024-09-21","ids":{"openalex":"https://openalex.org/W4402768574","doi":"https://doi.org/10.3390/s24186111","pmid":"https://pubmed.ncbi.nlm.nih.gov/39338856"},"language":"en","primary_location":{"id":"doi:10.3390/s24186111","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24186111","pdf_url":"https://www.mdpi.com/1424-8220/24/18/6111/pdf?version=1727399660","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/24/18/6111/pdf?version=1727399660","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022812446","display_name":"Hang Xue","orcid":"https://orcid.org/0000-0002-9422-2995"},"institutions":[{"id":"https://openalex.org/I106645853","display_name":"Changchun University of Science and Technology","ror":"https://ror.org/007mntk44","country_code":"CN","type":"education","lineage":["https://openalex.org/I106645853"]},{"id":"https://openalex.org/I121691239","display_name":"Beihua University","ror":"https://ror.org/013jjp941","country_code":"CN","type":"education","lineage":["https://openalex.org/I121691239"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hang Xue","raw_affiliation_strings":["College of Electronic and Information Engineering, Beihua University, Jilin 132021, China","College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun 130022, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic and Information Engineering, Beihua University, Jilin 132021, China","institution_ids":["https://openalex.org/I121691239"]},{"raw_affiliation_string":"College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun 130022, China","institution_ids":["https://openalex.org/I106645853"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101196873","display_name":"Xiping Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I106645853","display_name":"Changchun University of Science and Technology","ror":"https://ror.org/007mntk44","country_code":"CN","type":"education","lineage":["https://openalex.org/I106645853"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiping Xu","raw_affiliation_strings":["College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun 130022, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun 130022, China","institution_ids":["https://openalex.org/I106645853"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101257475","display_name":"Xiang Meng","orcid":"https://orcid.org/0009-0004-7349-1725"},"institutions":[{"id":"https://openalex.org/I121691239","display_name":"Beihua University","ror":"https://ror.org/013jjp941","country_code":"CN","type":"education","lineage":["https://openalex.org/I121691239"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiang Meng","raw_affiliation_strings":["College of Electronic and Information Engineering, Beihua University, Jilin 132021, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic and Information Engineering, Beihua University, Jilin 132021, China","institution_ids":["https://openalex.org/I121691239"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101257475"],"corresponding_institution_ids":["https://openalex.org/I121691239"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":1.5486,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.80592132,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"24","issue":"18","first_page":"6111","last_page":"6111"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9995999932289124,"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":0.9995999932289124,"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/T11324","display_name":"Spectroscopy Techniques in Biomedical and Chemical Research","score":0.980400025844574,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.9621000289916992,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8871701955795288},{"id":"https://openalex.org/keywords/partial-least-squares-regression","display_name":"Partial least squares regression","score":0.6789302825927734},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5865834355354309},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5627524256706238},{"id":"https://openalex.org/keywords/variable-elimination","display_name":"Variable elimination","score":0.5423136949539185},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48429909348487854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4538707137107849},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.40749943256378174},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.40065112709999084},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19882187247276306}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8871701955795288},{"id":"https://openalex.org/C22354355","wikidata":"https://www.wikidata.org/wiki/Q422009","display_name":"Partial least squares regression","level":2,"score":0.6789302825927734},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5865834355354309},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5627524256706238},{"id":"https://openalex.org/C169272836","wikidata":"https://www.wikidata.org/wiki/Q5668307","display_name":"Variable elimination","level":3,"score":0.5423136949539185},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48429909348487854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4538707137107849},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40749943256378174},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40065112709999084},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19882187247276306},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.0}],"mesh":[{"descriptor_ui":"D000081862","descriptor_name":"Hyperspectral Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D000081862","descriptor_name":"Hyperspectral Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D000081862","descriptor_name":"Hyperspectral Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D000081862","descriptor_name":"Hyperspectral Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003313","descriptor_name":"Zea mays","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D003313","descriptor_name":"Zea mays","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D003313","descriptor_name":"Zea mays","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D003313","descriptor_name":"Zea mays","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D012639","descriptor_name":"Seeds","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D012639","descriptor_name":"Seeds","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D012639","descriptor_name":"Seeds","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D012639","descriptor_name":"Seeds","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D013057","descriptor_name":"Spectrum Analysis","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D013057","descriptor_name":"Spectrum Analysis","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D013057","descriptor_name":"Spectrum Analysis","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D013057","descriptor_name":"Spectrum Analysis","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D016018","descriptor_name":"Least-Squares Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016018","descriptor_name":"Least-Squares Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016018","descriptor_name":"Least-Squares Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016018","descriptor_name":"Least-Squares Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.3390/s24186111","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24186111","pdf_url":"https://www.mdpi.com/1424-8220/24/18/6111/pdf?version=1727399660","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},{"id":"pmid:39338856","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39338856","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11435721","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11435721","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11435721/pdf/sensors-24-06111.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:fb33c8a4c7af4e418c5fa43a81cfb4f9","is_oa":true,"landing_page_url":"https://doaj.org/article/fb33c8a4c7af4e418c5fa43a81cfb4f9","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":"Sensors, Vol 24, Iss 18, p 6111 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s24186111","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24186111","pdf_url":"https://www.mdpi.com/1424-8220/24/18/6111/pdf?version=1727399660","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7200000286102295,"id":"https://metadata.un.org/sdg/6","display_name":"Clean water and sanitation"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322174","display_name":"People's Government of Jilin Province","ror":"https://ror.org/02fzqav45"},{"id":"https://openalex.org/F4320327282","display_name":"Department of Science and Technology of Jilin Province","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4402768574.pdf","grobid_xml":"https://content.openalex.org/works/W4402768574.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W3176672984","https://openalex.org/W3197515274","https://openalex.org/W4205399562","https://openalex.org/W4205573239","https://openalex.org/W4207011075","https://openalex.org/W4211131339","https://openalex.org/W4224250179","https://openalex.org/W4224444616","https://openalex.org/W4225372963","https://openalex.org/W4283779771","https://openalex.org/W4289985768","https://openalex.org/W4293145116","https://openalex.org/W4296229166","https://openalex.org/W4307944308","https://openalex.org/W4309928777","https://openalex.org/W4313005747","https://openalex.org/W4313475529","https://openalex.org/W4313479912","https://openalex.org/W4318220194","https://openalex.org/W4319018340","https://openalex.org/W4323041537","https://openalex.org/W4324309866","https://openalex.org/W4362509393","https://openalex.org/W4385764063","https://openalex.org/W4386379997","https://openalex.org/W4391257219","https://openalex.org/W4391648899","https://openalex.org/W4392005541","https://openalex.org/W4393855757","https://openalex.org/W4399046300","https://openalex.org/W4399332495","https://openalex.org/W6805858881","https://openalex.org/W6848597711","https://openalex.org/W6851205445"],"related_works":["https://openalex.org/W4394758899","https://openalex.org/W2047610499","https://openalex.org/W1950282396","https://openalex.org/W2073566205","https://openalex.org/W2387140374","https://openalex.org/W2437021460","https://openalex.org/W53778728","https://openalex.org/W3025059132","https://openalex.org/W1973576348","https://openalex.org/W2341468012"],"abstract_inverted_index":{"Assessing":[0],"the":[1,41,50,64,68,72,84,92,100,113,139,156,165,169,181,184,189,197,201,218,224,240,253],"quality":[2,245],"of":[3,31,40,44,53,67,74,158,183,228,242,255],"corn":[4,36,69,229,243],"seeds":[5,46,70],"necessitates":[6],"evaluating":[7],"their":[8],"water,":[9],"fat,":[10],"protein,":[11],"and":[12,28,83,111,133,142,149,208],"starch":[13],"content.":[14],"This":[15,211,231],"study":[16,232],"integrates":[17],"hyperspectral":[18,214],"imaging":[19],"technology":[20,215,258],"with":[21,217],"chemometric":[22],"analysis":[23,98,162],"techniques":[24,59],"to":[25,62,154,178],"achieve":[26],"non-invasive":[27],"rapid":[29],"detection":[30],"multiple":[32],"key":[33],"components":[34,199],"in":[35,200,259],"seeds.":[37,230],"Hyperspectral":[38],"images":[39],"embryo":[42],"surface":[43],"maize":[45],"were":[47,60,81,118,152,204],"collected":[48],"within":[49],"wavelength":[51,122],"range":[52],"1100~2498":[54],"nm.":[55],"Subsequently,":[56],"image":[57],"segmentation":[58],"applied":[61],"extract":[63],"germ":[65],"structure":[66],"as":[71,91],"region":[73],"interest.":[75],"Seven":[76],"spectral":[77,109],"data":[78],"preprocessing":[79,94],"algorithms":[80,117],"employed,":[82],"Detrending":[85],"Transformation":[86],"(DT)":[87],"algorithm":[88,167,175,220],"was":[89,176],"identified":[90],"optimal":[93],"method":[95],"through":[96],"comparative":[97],"using":[99],"Partial":[101],"Least":[102],"Squares":[103],"Regression":[104],"(PLSR)":[105],"model.":[106],"To":[107],"reduce":[108],"redundancy":[110],"streamline":[112],"prediction":[114,171,191],"model,":[115,186],"three":[116],"employed":[119,177],"for":[120,196,239,252],"characteristic":[121,144],"extraction:":[123],"Successive":[124],"Projections":[125],"Algorithm":[126],"(SPA),":[127],"Competitive":[128],"Adaptive":[129],"Reweighted":[130],"Sampling":[131],"(CARS),":[132],"Uninformative":[134],"Variable":[135],"Elimination":[136],"(UVE).":[137],"Using":[138],"original":[140],"spectra":[141],"extracted":[143],"wavelengths,":[145],"PLSR,":[146],"BP,":[147],"RBF,":[148],"LSSVM":[150,185],"models":[151],"constructed":[153],"detect":[155,223],"content":[157,227],"four":[159,198],"components.":[160],"The":[161,173,193],"indicated":[163],"that":[164,213],"CARS-LSSVM":[166],"had":[168],"best":[170],"performance.":[172,192],"PSO":[174],"further":[179],"optimize":[180],"parameters":[182],"thereby":[187],"improving":[188],"model's":[190],"R":[194],"values":[195],"test":[202],"set":[203],"0.9884,":[205],"0.9490,":[206],"0.9864,":[207],"0.9687,":[209],"respectively.":[210],"indicates":[212],"combined":[216],"DT-CARS-PSO-LSSVM":[219],"can":[221],"effectively":[222],"main":[225],"component":[226],"not":[233],"only":[234],"provides":[235],"a":[236],"scientific":[237],"basis":[238],"evaluation":[241],"seed":[244],"but":[246],"also":[247],"opens":[248],"up":[249],"new":[250],"avenues":[251],"development":[254],"non-destructive":[256],"testing":[257],"related":[260],"fields.":[261]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
