{"id":"https://openalex.org/W2946050306","doi":"https://doi.org/10.3390/s19102359","title":"Detection of Type, Blended Ratio, and Mixed Ratio of Pu\u2019er Tea by Using Electronic Nose and Visible/Near Infrared Spectrometer","display_name":"Detection of Type, Blended Ratio, and Mixed Ratio of Pu\u2019er Tea by Using Electronic Nose and Visible/Near Infrared Spectrometer","publication_year":2019,"publication_date":"2019-05-22","ids":{"openalex":"https://openalex.org/W2946050306","doi":"https://doi.org/10.3390/s19102359","mag":"2946050306","pmid":"https://pubmed.ncbi.nlm.nih.gov/31121902"},"language":"en","primary_location":{"id":"doi:10.3390/s19102359","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19102359","pdf_url":"https://www.mdpi.com/1424-8220/19/10/2359/pdf?version=1558519387","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/1424-8220/19/10/2359/pdf?version=1558519387","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110622082","display_name":"Sai Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099004","display_name":"Guangdong Academy of Agricultural Sciences","ror":"https://ror.org/01rkwtz72","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210099004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sai Xu","raw_affiliation_strings":["Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China","Public Monitoring Center for Agro-Product of Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China","institution_ids":["https://openalex.org/I4210099004"]},{"raw_affiliation_string":"Public Monitoring Center for Agro-Product of Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China","institution_ids":["https://openalex.org/I4210099004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084780450","display_name":"Xiuxiu Sun","orcid":"https://orcid.org/0000-0002-5820-9128"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]},{"id":"https://openalex.org/I443046","display_name":"Indian River State College","ror":"https://ror.org/05axs7x03","country_code":"US","type":"education","lineage":["https://openalex.org/I443046"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiuxiu Sun","raw_affiliation_strings":["Indian River Research and Education Center, University of Florida, Ft. Pierce, FL 34945, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian River Research and Education Center, University of Florida, Ft. Pierce, FL 34945, USA","institution_ids":["https://openalex.org/I443046","https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028555717","display_name":"Huazhong Lu","orcid":"https://orcid.org/0000-0003-0791-4852"},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]},{"id":"https://openalex.org/I4210099004","display_name":"Guangdong Academy of Agricultural Sciences","ror":"https://ror.org/01rkwtz72","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210099004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huazhong Lu","raw_affiliation_strings":["College of Engineering, South China Agricultural University, Guangzhou 510640, China","Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Engineering, South China Agricultural University, Guangzhou 510640, China","institution_ids":["https://openalex.org/I101479585"]},{"raw_affiliation_string":"Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China","institution_ids":["https://openalex.org/I4210099004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100349088","display_name":"Qianqian Zhang","orcid":"https://orcid.org/0000-0001-9375-5469"},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qianqian Zhang","raw_affiliation_strings":["College of Engineering, South China Agricultural University, Guangzhou 510640, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Engineering, South China Agricultural University, Guangzhou 510640, China","institution_ids":["https://openalex.org/I101479585"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5028555717"],"corresponding_institution_ids":["https://openalex.org/I101479585","https://openalex.org/I4210099004"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":1.2583,"has_fulltext":true,"cited_by_count":28,"citation_normalized_percentile":{"value":0.77671227,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"19","issue":"10","first_page":"2359","last_page":"2359"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9968000054359436,"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/T11709","display_name":"Traditional Chinese Medicine Analysis","score":0.9765999913215637,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/electronic-nose","display_name":"Electronic nose","score":0.836774468421936},{"id":"https://openalex.org/keywords/spectrometer","display_name":"Spectrometer","score":0.730143666267395},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5611264705657959},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5582656264305115},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5306909084320068},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49507322907447815},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45083677768707275},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4308466911315918},{"id":"https://openalex.org/keywords/partial-least-squares-regression","display_name":"Partial least squares regression","score":0.4144146144390106},{"id":"https://openalex.org/keywords/near-infrared-spectroscopy","display_name":"Near-infrared spectroscopy","score":0.41418689489364624},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3937683403491974},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20622462034225464},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.19631516933441162},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.16331470012664795},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11668556928634644}],"concepts":[{"id":"https://openalex.org/C23895516","wikidata":"https://www.wikidata.org/wiki/Q550092","display_name":"Electronic nose","level":2,"score":0.836774468421936},{"id":"https://openalex.org/C33390570","wikidata":"https://www.wikidata.org/wiki/Q188463","display_name":"Spectrometer","level":2,"score":0.730143666267395},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5611264705657959},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5582656264305115},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5306909084320068},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49507322907447815},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45083677768707275},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4308466911315918},{"id":"https://openalex.org/C22354355","wikidata":"https://www.wikidata.org/wiki/Q422009","display_name":"Partial least squares regression","level":2,"score":0.4144146144390106},{"id":"https://openalex.org/C43571822","wikidata":"https://www.wikidata.org/wiki/Q599037","display_name":"Near-infrared spectroscopy","level":2,"score":0.41418689489364624},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3937683403491974},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20622462034225464},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.19631516933441162},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.16331470012664795},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11668556928634644},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s19102359","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19102359","pdf_url":"https://www.mdpi.com/1424-8220/19/10/2359/pdf?version=1558519387","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:31121902","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31121902","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:doaj.org/article:966be73addd2457487a3187042fb384c","is_oa":true,"landing_page_url":"https://doaj.org/article/966be73addd2457487a3187042fb384c","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 19, Iss 10, p 2359 (2019)","raw_type":"article"},{"id":"pmh:oai:europepmc.org:5547344","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6566589","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"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":null,"raw_type":"Text"},{"id":"pmh:oai:mdpi.com:/1424-8220/19/10/2359/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/s19102359","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":"Sensors","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s19102359","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19102359","pdf_url":"https://www.mdpi.com/1424-8220/19/10/2359/pdf?version=1558519387","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":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.4300000071525574}],"awards":[{"id":"https://openalex.org/G3235094250","display_name":null,"funder_award_id":"31571561","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4133174517","display_name":null,"funder_award_id":"201920","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"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2946050306.pdf","grobid_xml":"https://content.openalex.org/works/W2946050306.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W178813604","https://openalex.org/W1523728029","https://openalex.org/W1973214009","https://openalex.org/W1996195892","https://openalex.org/W1996621989","https://openalex.org/W2013158245","https://openalex.org/W2062594268","https://openalex.org/W2077935401","https://openalex.org/W2085113815","https://openalex.org/W2097215200","https://openalex.org/W2158639075","https://openalex.org/W2319795220","https://openalex.org/W2352890937","https://openalex.org/W2353157675","https://openalex.org/W2353811498","https://openalex.org/W2401162735","https://openalex.org/W2500751094","https://openalex.org/W2547183676","https://openalex.org/W2590898438","https://openalex.org/W2592686753","https://openalex.org/W2603597171","https://openalex.org/W2734941369","https://openalex.org/W2783662494","https://openalex.org/W2790978579","https://openalex.org/W2810874584","https://openalex.org/W2901834364","https://openalex.org/W6631375296","https://openalex.org/W6670269920","https://openalex.org/W6712976521","https://openalex.org/W6996008502"],"related_works":["https://openalex.org/W2024869860","https://openalex.org/W2391447249","https://openalex.org/W2094946501","https://openalex.org/W2037752115","https://openalex.org/W4221006215","https://openalex.org/W3158648238","https://openalex.org/W2017786325","https://openalex.org/W3115262167","https://openalex.org/W2343541729","https://openalex.org/W3132103859"],"abstract_inverted_index":{"The":[0,161,259],"objective":[1],"of":[2,22,94,104,138,190,229,243,262],"this":[3],"study":[4],"was":[5,56,141],"to":[6,13,156,176,198,218],"find":[7],"an":[8],"intelligent":[9],"and":[10,19,41,63,74,119,129,163,207,253],"fast":[11],"method":[12,62,115],"detect":[14],"the":[15,33,60,89,92,100,111,136,145,150,158,182,188,200,220,227,235,241,254,289],"type,":[16],"blended":[17,260],"ratio,":[18],"mixed":[20],"ratio":[21,261],"ancient":[23],"Pu'er":[24,34,244,263],"tea,":[25],"which":[26,195,233],"is":[27,292,303],"significant":[28],"in":[29,32,142,192],"maintaining":[30],"order":[31],"tea":[35,52,245,264],"industry.":[36],"An":[37],"electronic":[38],"nose":[39],"(E-nose)":[40],"a":[42,64,250,271,296],"visible":[43],"near":[44],"infrared":[45],"spectrometer":[46,152,209,252,273,298],"(VIS/NIR":[47],"spectrometer)":[48],"were":[49,80,133],"applied":[50,81],"for":[51,82,116,148],"sampling.":[53],"Feature":[54],"extraction":[55,114,257,284,302],"conducted":[57],"using":[58,88,249,270],"both":[59],"traditional":[61,90,183,255,275,282,300],"convolutional":[65],"neural":[66],"network":[67],"(CNN)":[68],"technique.":[69],"Linear":[70],"discriminant":[71],"analysis":[72,93,165],"(LDA)":[73],"partial":[75],"least":[76],"square":[77],"regression":[78],"(PLSR)":[79],"pattern":[83],"recognition.":[84],"After":[85],"sampling":[86],"while":[87],"method,":[91,184],"variance":[95],"(ANOVA)":[96],"results":[97,123,166],"showed":[98,124,167],"that":[99,125,168],"mean":[101],"differential":[102],"value":[103],"each":[105],"sensor":[106],"should":[107,246,265,285],"be":[108,247,267,286],"selected":[109],"as":[110],"optimal":[112],"feature":[113,256,276,283,301],"E-nose":[117,139],"data,":[118],"raw":[120],"data":[121,140,153],"comparison":[122],"19":[126],"peak/valley":[127],"values":[128,132],"two":[130],"slope":[131],"extracted.":[134],"While":[135],"format":[137,147,159],"accord":[143],"with":[144,274,281,299],"input":[146],"CNN,":[149],"VIS/NIR":[151,208,251,272,297],"required":[154],"matrixing":[155],"meet":[157],"requirements.":[160],"LDA":[162],"PLSR":[164],"CNN":[169],"has":[170,187],"superior":[171],"detection":[172,201,221,236],"ability,":[173,222],"being":[174],"able":[175],"acquire":[177],"more":[178,213],"local":[179],"features":[180,214],"than":[181],"but":[185,223],"it":[186,224],"risk":[189,228],"mixing":[191],"redundant":[193,231],"information,":[194,232],"can":[196,211],"act":[197],"reduce":[199],"ability.":[202,237],"Multi-source":[203,278],"information":[204,279],"fusion":[205,280],"(E-nose":[206],"fusion)":[210],"collect":[212],"from":[215],"different":[216],"angles":[217],"improve":[219],"also":[225,266],"contains":[226],"adding":[230],"reduces":[234],"For":[238],"practical":[239],"detection,":[240],"type":[242],"recognizable":[248],"method.":[258],"identifiable":[268],"by":[269],"extraction.":[277],"used":[287],"if":[288],"accuracy":[290],"requirement":[291],"extremely":[293],"high;":[294],"otherwise,":[295],"preferred.":[304]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}