{"id":"https://openalex.org/W7163374371","doi":"https://doi.org/10.48550/arxiv.2606.02796","title":"A Measurement-Driven Digital Twin Architecture for Plant-Level Biomass Estimation and Growth Forecasting in Hydroponic Systems","display_name":"A Measurement-Driven Digital Twin Architecture for Plant-Level Biomass Estimation and Growth Forecasting in Hydroponic Systems","publication_year":2026,"publication_date":"2026-06-01","ids":{"openalex":"https://openalex.org/W7163374371","doi":"https://doi.org/10.48550/arxiv.2606.02796"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.02796","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.02796","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.2606.02796","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137715031","display_name":"Morgan Mayborne","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mayborne, Morgan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016610643","display_name":"Abhisesh Silwal","orcid":"https://orcid.org/0000-0002-1710-6704"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Silwal, Abhisesh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5021717710","display_name":"George Von Kantor","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kantor, George","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/T12093","display_name":"Greenhouse Technology and Climate Control","score":0.7226999998092651,"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/T12093","display_name":"Greenhouse Technology and Climate Control","score":0.7226999998092651,"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/T10616","display_name":"Smart Agriculture and AI","score":0.12380000203847885,"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/T13391","display_name":"Innovations in Aquaponics and Hydroponics Systems","score":0.06800000369548798,"subfield":{"id":"https://openalex.org/subfields/1104","display_name":"Aquatic 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/biomass","display_name":"Biomass (ecology)","score":0.590399980545044},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5425000190734863},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4810999929904938},{"id":"https://openalex.org/keywords/yield","display_name":"Yield (engineering)","score":0.4675999879837036},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.421099990606308},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4059999883174896}],"concepts":[{"id":"https://openalex.org/C115540264","wikidata":"https://www.wikidata.org/wiki/Q2945560","display_name":"Biomass (ecology)","level":2,"score":0.590399980545044},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5425000190734863},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4810999929904938},{"id":"https://openalex.org/C88463610","wikidata":"https://www.wikidata.org/wiki/Q194118","display_name":"Agricultural engineering","level":1,"score":0.4708000123500824},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.4675999879837036},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.4381999969482422},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.421099990606308},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4059999883174896},{"id":"https://openalex.org/C89992363","wikidata":"https://www.wikidata.org/wiki/Q5961558","display_name":"Track (disk drive)","level":2,"score":0.3637000024318695},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.3635999858379364},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.35359999537467957},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.2953000068664551},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.29089999198913574},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.27000001072883606},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.26600000262260437},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2637999951839447},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.25369998812675476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.02796","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.02796","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.2606.02796","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.02796","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Alternatives":[0],"to":[1,10,12,25,44,71,114],"soil-based":[2],"horticulture,":[3],"such":[4],"as":[5,99],"hydroponics,":[6],"have":[7],"been":[8],"developed":[9,24],"respond":[11],"food":[13],"distribution":[14],"concerns":[15],"for":[16,51],"dense":[17],"urban":[18],"centers.":[19],"A":[20],"new":[21],"system":[22],"was":[23,85,112],"track":[26],"an":[27,61,100],"individual":[28],"lettuce":[29],"plant's":[30],"growth":[31,48,132],"in":[32,79,143],"a":[33,52,89,106,148],"hydroponic":[34,63],"environment,":[35],"utilizing":[36],"streams":[37],"of":[38,96,109,120],"measured":[39,87],"information":[40],"and":[41,68,73,140],"available":[42],"models":[43,57],"continuously":[45,86],"update":[46],"the":[47,97,121,127,144],"trajectory":[49],"estimates":[50],"plant.":[53],"These":[54],"\"digital":[55],"twin\"":[56],"were":[58],"integrated":[59],"into":[60,126],"operating":[62],"greenhouse,":[64],"with":[65,88],"custom":[66,90,128],"horticultural":[67],"sensor":[69],"hardware":[70],"grow":[72],"measure":[74],"relevant":[75],"information.":[76],"To":[77],"aid":[78],"updating":[80],"model":[81],"parameters,":[82],"plant":[83],"yield":[84,137],"neural":[91],"network,":[92,103],"using":[93],"RGB-D":[94],"images":[95],"plants":[98],"input.":[101],"The":[102],"trained":[104],"on":[105],"collected":[107],"dataset":[108],"1300":[110],"images,":[111],"able":[113],"estimate":[115],"mass":[116],"within":[117],"1.5":[118],"g":[119,150],"ground-truth":[122],"value.":[123],"After":[124],"integration":[125],"system,":[129],"digital":[130],"twin":[131],"projections":[133],"could":[134],"approximate":[135],"future":[136],"between":[138],"one":[139],"four":[141],"days":[142],"future,":[145],"maintaining":[146],"around":[147],"2":[149],"forecasting":[151],"error.":[152]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-04T00:00:00"}
