{"id":"https://openalex.org/W7106316167","doi":"https://doi.org/10.48550/arxiv.2511.15173","title":"Data-driven Prediction of Species-Specific Plant Responses to Spectral-Shifting Films from Leaf Phenotypic and Photosynthetic Traits","display_name":"Data-driven Prediction of Species-Specific Plant Responses to Spectral-Shifting Films from Leaf Phenotypic and Photosynthetic Traits","publication_year":2025,"publication_date":"2025-11-19","ids":{"openalex":"https://openalex.org/W7106316167","doi":"https://doi.org/10.48550/arxiv.2511.15173"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2511.15173","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.15173","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2511.15173","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Kang, Jun Hyeun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kang, Jun Hyeun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Son, Jung Eek","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Son, Jung Eek","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Ahn, Tae In","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ahn, Tae In","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"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/T11268","display_name":"Light effects on plants","score":0.8907999992370605,"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"}},"topics":[{"id":"https://openalex.org/T11268","display_name":"Light effects on plants","score":0.8907999992370605,"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"}},{"id":"https://openalex.org/T12093","display_name":"Greenhouse Technology and Climate Control","score":0.08209999650716782,"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"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.010400000028312206,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/photosynthesis","display_name":"Photosynthesis","score":0.640999972820282},{"id":"https://openalex.org/keywords/greenhouse","display_name":"Greenhouse","score":0.6399999856948853},{"id":"https://openalex.org/keywords/crop","display_name":"Crop","score":0.6342999935150146},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.597599983215332},{"id":"https://openalex.org/keywords/crop-yield","display_name":"Crop yield","score":0.40230000019073486},{"id":"https://openalex.org/keywords/chlorophyll","display_name":"Chlorophyll","score":0.39169999957084656},{"id":"https://openalex.org/keywords/sunlight","display_name":"Sunlight","score":0.36550000309944153},{"id":"https://openalex.org/keywords/yield","display_name":"Yield (engineering)","score":0.35519999265670776}],"concepts":[{"id":"https://openalex.org/C183688256","wikidata":"https://www.wikidata.org/wiki/Q11982","display_name":"Photosynthesis","level":2,"score":0.640999972820282},{"id":"https://openalex.org/C32198211","wikidata":"https://www.wikidata.org/wiki/Q165044","display_name":"Greenhouse","level":2,"score":0.6399999856948853},{"id":"https://openalex.org/C137580998","wikidata":"https://www.wikidata.org/wiki/Q235352","display_name":"Crop","level":2,"score":0.6342999935150146},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.597599983215332},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.48899999260902405},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.4659000039100647},{"id":"https://openalex.org/C126343540","wikidata":"https://www.wikidata.org/wiki/Q889514","display_name":"Crop yield","level":2,"score":0.40230000019073486},{"id":"https://openalex.org/C2776373379","wikidata":"https://www.wikidata.org/wiki/Q43177","display_name":"Chlorophyll","level":2,"score":0.39169999957084656},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.36739999055862427},{"id":"https://openalex.org/C170853661","wikidata":"https://www.wikidata.org/wiki/Q193788","display_name":"Sunlight","level":2,"score":0.36550000309944153},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.35519999265670776},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.353300005197525},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.3522999882698059},{"id":"https://openalex.org/C144027150","wikidata":"https://www.wikidata.org/wiki/Q48803","display_name":"Horticulture","level":1,"score":0.34929999709129333},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3221000134944916},{"id":"https://openalex.org/C3020368824","wikidata":"https://www.wikidata.org/wiki/Q6546192","display_name":"Light intensity","level":2,"score":0.3075999915599823},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.30329999327659607},{"id":"https://openalex.org/C2780138947","wikidata":"https://www.wikidata.org/wiki/Q393855","display_name":"Dry matter","level":2,"score":0.2989000082015991},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.2964000105857849},{"id":"https://openalex.org/C2776615292","wikidata":"https://www.wikidata.org/wiki/Q7574996","display_name":"Specific leaf area","level":3,"score":0.2768000066280365},{"id":"https://openalex.org/C130073038","wikidata":"https://www.wikidata.org/wiki/Q1211967","display_name":"Phenotypic trait","level":4,"score":0.2700999975204468},{"id":"https://openalex.org/C2985179745","wikidata":"https://www.wikidata.org/wiki/Q131449","display_name":"Plant species","level":2,"score":0.258899986743927},{"id":"https://openalex.org/C70839106","wikidata":"https://www.wikidata.org/wiki/Q655362","display_name":"Plant morphology","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C47702885","wikidata":"https://www.wikidata.org/wiki/Q5441227","display_name":"Feedforward neural network","level":3,"score":0.2547999918460846}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2511.15173","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.15173","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2511.15173","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.15173","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.5569416284561157,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,213],"application":[1],"of":[2,26,38,43,50,86,173,220],"spectral-shifting":[3],"films":[4],"in":[5,55,109,139],"greenhouses":[6,110],"to":[7,11,34,71,88,152,181,199,256],"shift":[8,260],"green":[9],"light":[10,13,30,80,127,130],"red":[12],"has":[14,53],"shown":[15],"variable":[16],"growth":[17,65,90],"responses":[18,85],"across":[19],"crop":[20,52,64,167],"species.":[21,45],"However,":[22],"the":[23,35,39,57,83,136,237,254],"yield":[24,209],"enhancement":[25],"crops":[27,87,106],"under":[28,92,175],"altered":[29],"quality":[31,61],"is":[32],"related":[33],"collective":[36],"effects":[37,261],"specific":[40],"biophysical":[41],"characteristics":[42],"each":[44,140],"Considering":[46],"only":[47],"one":[48],"attribute":[49],"a":[51,158,205,216,223],"limitations":[54],"understanding":[56],"relationship":[58],"between":[59,240],"sunlight":[60],"adjustments":[62],"and":[63,78,99,104,117,129,193,243,248],"performance.":[66],"Therefore,":[67],"this":[68],"study":[69,233],"aims":[70],"comprehensively":[72],"link":[73],"multiple":[74],"plant":[75],"phenotypic":[76,242],"traits":[77],"daily":[79,126],"integral":[81],"considering":[82],"physiological":[84],"their":[89],"outcomes":[91],"SF":[93,211],"using":[94,262],"artificial":[95],"intelligence.":[96],"Between":[97],"2021":[98],"2024,":[100],"various":[101],"leafy,":[102],"fruiting,":[103],"root":[105],"were":[107,133,145,179],"grown":[108],"covered":[111],"with":[112,210],"either":[113],"PEF":[114],"or":[115],"SF,":[116],"leaf":[118,120,241],"reflectance,":[119],"mass":[121],"per":[122],"area,":[123],"chlorophyll":[124],"content,":[125],"integral,":[128],"saturation":[131],"point":[132],"measured":[134],"from":[135],"plants":[137],"cultivated":[138],"condition.":[141],"210":[142],"data":[143,151,164,178],"points":[144],"collected,":[146],"but":[147],"there":[148,203],"was":[149,161,204,227],"insufficient":[150],"train":[153,182],"deep":[154],"learning":[155],"models,":[156,184],"so":[157],"variational":[159],"autoencoder":[160],"used":[162,180,229],"for":[163,230],"augmentation.":[165],"Most":[166],"yields":[168],"showed":[169],"an":[170],"average":[171],"increase":[172],"22.5%":[174],"SF.":[176,263],"These":[177],"several":[183],"including":[185],"logistic":[186],"regression,":[187],"decision":[188],"tree,":[189],"random":[190],"forest,":[191],"XGBoost,":[192],"feedforward":[194],"neural":[195],"network":[196],"(FFNN),":[197],"aiming":[198],"binary":[200],"classify":[201],"whether":[202],"significant":[206],"effect":[207],"on":[208,222],"application.":[212],"FFNN":[214],"achieved":[215],"high":[217],"classification":[218],"accuracy":[219],"91.4%":[221],"test":[224],"dataset":[225],"that":[226],"not":[228],"training.":[231],"This":[232],"provide":[234],"insight":[235],"into":[236],"complex":[238],"interactions":[239],"photosynthetic":[244],"traits,":[245],"environmental":[246],"conditions,":[247],"solar":[249,258],"spectral":[250,259],"components":[251],"by":[252],"improving":[253],"ability":[255],"predict":[257]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-11-23T00:00:00"}