{"id":"https://openalex.org/W4226064623","doi":"https://doi.org/10.48550/arxiv.2203.05199","title":"Hyperspectral Imaging for cherry tomato","display_name":"Hyperspectral Imaging for cherry tomato","publication_year":2022,"publication_date":"2022-03-10","ids":{"openalex":"https://openalex.org/W4226064623","doi":"https://doi.org/10.48550/arxiv.2203.05199"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2203.05199","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2203.05199","pdf_url":"https://arxiv.org/pdf/2203.05199","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2203.05199","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007650182","display_name":"Yun Xiang","orcid":"https://orcid.org/0000-0003-2982-425X"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xiang, Yun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073789459","display_name":"Qijun Chen","orcid":"https://orcid.org/0000-0001-5644-1188"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Qijun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056589824","display_name":"Zhongjin Su","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Su, Zhongjin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100388702","display_name":"Lu Zhang","orcid":"https://orcid.org/0009-0007-9630-1172"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Lu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070235251","display_name":"Zuohui Chen","orcid":"https://orcid.org/0000-0003-1806-6676"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Zuohui","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103904405","display_name":"Guozhi Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Guozhi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100951301","display_name":"Zhuping Yao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao, Zhuping","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016704080","display_name":"Qi Xuan","orcid":"https://orcid.org/0000-0002-1042-470X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xuan, Qi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100582162","display_name":"Yuan Cheng","orcid":"https://orcid.org/0000-0003-1830-7951"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Yuan","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5007650182"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9990000128746033,"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":0.9990000128746033,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9761000275611877,"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/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.9603000283241272,"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":0.9748191833496094},{"id":"https://openalex.org/keywords/solanum","display_name":"Solanum","score":0.5912346839904785},{"id":"https://openalex.org/keywords/flavor","display_name":"Flavor","score":0.55866539478302},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4849886894226074},{"id":"https://openalex.org/keywords/horticulture","display_name":"Horticulture","score":0.448715478181839},{"id":"https://openalex.org/keywords/cherry-tomato","display_name":"Cherry tomato","score":0.44741761684417725},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.43036407232284546},{"id":"https://openalex.org/keywords/reflectivity","display_name":"Reflectivity","score":0.42582952976226807},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3927486538887024},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3581897020339966},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3200739026069641},{"id":"https://openalex.org/keywords/food-science","display_name":"Food science","score":0.2209758460521698},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.21004128456115723},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.19437214732170105},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.14502674341201782},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.14078032970428467},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.11919921636581421}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9748191833496094},{"id":"https://openalex.org/C2781083041","wikidata":"https://www.wikidata.org/wiki/Q146555","display_name":"Solanum","level":2,"score":0.5912346839904785},{"id":"https://openalex.org/C2780719635","wikidata":"https://www.wikidata.org/wiki/Q4173974","display_name":"Flavor","level":2,"score":0.55866539478302},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4849886894226074},{"id":"https://openalex.org/C144027150","wikidata":"https://www.wikidata.org/wiki/Q48803","display_name":"Horticulture","level":1,"score":0.448715478181839},{"id":"https://openalex.org/C2780890322","wikidata":"https://www.wikidata.org/wiki/Q6540634","display_name":"Cherry tomato","level":2,"score":0.44741761684417725},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.43036407232284546},{"id":"https://openalex.org/C108597893","wikidata":"https://www.wikidata.org/wiki/Q663650","display_name":"Reflectivity","level":2,"score":0.42582952976226807},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3927486538887024},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3581897020339966},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3200739026069641},{"id":"https://openalex.org/C31903555","wikidata":"https://www.wikidata.org/wiki/Q1637030","display_name":"Food science","level":1,"score":0.2209758460521698},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.21004128456115723},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.19437214732170105},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.14502674341201782},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.14078032970428467},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.11919921636581421}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2203.05199","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2203.05199","pdf_url":"https://arxiv.org/pdf/2203.05199","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2203.05199","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2203.05199","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2203.05199","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2203.05199","pdf_url":"https://arxiv.org/pdf/2203.05199","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4299699984","https://openalex.org/W3009337611","https://openalex.org/W3093358672","https://openalex.org/W3215443049","https://openalex.org/W3131514497","https://openalex.org/W4313025612","https://openalex.org/W2765373018","https://openalex.org/W3201222902","https://openalex.org/W2148699575","https://openalex.org/W3195536380"],"abstract_inverted_index":{"Cherry":[0],"tomato":[1,61,160],"(Solanum":[2],"Lycopersicum)":[3],"is":[4,83,94,117],"popular":[5],"with":[6,65,98,108],"consumers":[7],"over":[8,59],"the":[9,28,80,99,137,145,164],"world":[10],"due":[11],"to":[12,70],"its":[13],"special":[14],"flavor.":[15],"Soluble":[16],"solids":[17],"content":[18],"(SSC)":[19],"and":[20,41,48,79,96,127,147],"firmness":[21,43,148],"are":[22,63,77],"two":[23],"key":[24],"metrics":[25],"for":[26,39,125,129,155],"evaluating":[27],"product":[29],"qualities.":[30],"In":[31],"this":[32,134],"work,":[33],"we":[34],"develop":[35],"non-destructive":[36,156],"testing":[37,157],"techniques":[38],"SSC":[40,126,146],"fruit":[42,161],"based":[44,91],"on":[45],"hyperspectral":[46,75,141],"images":[47,57,76],"a":[49,109,152],"corresponding":[50],"deep":[51],"learning":[52],"regression":[53,92],"model.":[54],"Hyperspectral":[55],"reflectance":[56],"of":[58,101,113,122,133,140,158],"200":[60],"fruits":[62],"derived":[64],"spectrum":[66],"ranging":[67],"from":[68],"400":[69],"1000":[71],"nm.":[72],"The":[73,131],"acquired":[74],"corrected":[78],"spectral":[81],"information":[82],"extracted.":[84],"A":[85],"novel":[86],"one-dimensional(1D)":[87],"convolutional":[88],"ResNet":[89],"(Con1dResNet)":[90],"model":[93],"prosed":[95],"compared":[97],"state":[100,121],"art":[102,123],"techniques.":[103],"Experimental":[104],"results":[105,132],"show":[106],"that,":[107],"relatively":[110],"large":[111],"number":[112],"samples":[114],"our":[115],"technique":[116,124,143],"26.4\\%":[118],"better":[119],"than":[120],"33.7\\%":[128],"firmness.":[130],"study":[135],"indicate":[136],"application":[138],"potential":[139],"imaging":[142],"in":[144,163],"detection,":[149],"which":[150],"provides":[151],"new":[153],"option":[154],"cherry":[159],"quality":[162],"future.":[165]},"counts_by_year":[],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}
