{"id":"https://openalex.org/W3132322329","doi":"https://doi.org/10.1109/igarss39084.2020.9323202","title":"Toward Maturity Assessment of SNAP Bean Crops: A Best-Case Greenhouse Scenario","display_name":"Toward Maturity Assessment of SNAP Bean Crops: A Best-Case Greenhouse Scenario","publication_year":2020,"publication_date":"2020-09-26","ids":{"openalex":"https://openalex.org/W3132322329","doi":"https://doi.org/10.1109/igarss39084.2020.9323202","mag":"3132322329"},"language":"en","primary_location":{"id":"doi:10.1109/igarss39084.2020.9323202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9323202","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043643386","display_name":"Amirhossein Hassanzadeh","orcid":"https://orcid.org/0000-0002-0171-238X"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]},{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"A. Hassanzadeh","raw_affiliation_strings":["Rochester Institute of Technology and Cornell University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology and Cornell University","institution_ids":["https://openalex.org/I155173764","https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054912828","display_name":"Sean P. Murphy","orcid":"https://orcid.org/0000-0001-8500-7524"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]},{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"S.P. Murphy","raw_affiliation_strings":["Rochester Institute of Technology and Cornell University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology and Cornell University","institution_ids":["https://openalex.org/I155173764","https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061307460","display_name":"Sarah J. Pethybridge","orcid":"https://orcid.org/0000-0003-3864-4293"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]},{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"S.J. Pethybridge","raw_affiliation_strings":["Rochester Institute of Technology and Cornell University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology and Cornell University","institution_ids":["https://openalex.org/I155173764","https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085740223","display_name":"Jan van Aardt","orcid":"https://orcid.org/0000-0002-3036-0088"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]},{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J. van Aardt","raw_affiliation_strings":["Rochester Institute of Technology and Cornell University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology and Cornell University","institution_ids":["https://openalex.org/I155173764","https://openalex.org/I205783295"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072295908","display_name":"F. Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]},{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"F. Zhang","raw_affiliation_strings":["Rochester Institute of Technology and Cornell University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology and Cornell University","institution_ids":["https://openalex.org/I155173764","https://openalex.org/I205783295"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4625,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.7683578,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"7","issue":null,"first_page":"5278","last_page":"5281"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14365","display_name":"Leaf Properties and Growth Measurement","score":0.9980999827384949,"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/T14365","display_name":"Leaf Properties and Growth Measurement","score":0.9980999827384949,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9972000122070312,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9908000230789185,"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/agricultural-engineering","display_name":"Agricultural engineering","score":0.45989683270454407},{"id":"https://openalex.org/keywords/irrigation-scheduling","display_name":"Irrigation scheduling","score":0.4457889497280121},{"id":"https://openalex.org/keywords/greenhouse","display_name":"Greenhouse","score":0.4165845513343811},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4040157198905945},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.37252750992774963},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3665744662284851},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34555289149284363},{"id":"https://openalex.org/keywords/agronomy","display_name":"Agronomy","score":0.30261504650115967},{"id":"https://openalex.org/keywords/irrigation","display_name":"Irrigation","score":0.24026799201965332},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.15198343992233276},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1303044557571411}],"concepts":[{"id":"https://openalex.org/C88463610","wikidata":"https://www.wikidata.org/wiki/Q194118","display_name":"Agricultural engineering","level":1,"score":0.45989683270454407},{"id":"https://openalex.org/C2777589951","wikidata":"https://www.wikidata.org/wiki/Q6073845","display_name":"Irrigation scheduling","level":3,"score":0.4457889497280121},{"id":"https://openalex.org/C32198211","wikidata":"https://www.wikidata.org/wiki/Q165044","display_name":"Greenhouse","level":2,"score":0.4165845513343811},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4040157198905945},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.37252750992774963},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3665744662284851},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34555289149284363},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.30261504650115967},{"id":"https://openalex.org/C88862950","wikidata":"https://www.wikidata.org/wiki/Q11453","display_name":"Irrigation","level":2,"score":0.24026799201965332},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.15198343992233276},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1303044557571411}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss39084.2020.9323202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9323202","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1516941203","https://openalex.org/W2011821416","https://openalex.org/W2038782607","https://openalex.org/W2046404820","https://openalex.org/W2084139018","https://openalex.org/W2091213485","https://openalex.org/W2109606373","https://openalex.org/W2118996198","https://openalex.org/W2152039022","https://openalex.org/W2166056814","https://openalex.org/W2600798029","https://openalex.org/W2778376722","https://openalex.org/W2798681343","https://openalex.org/W2805142011","https://openalex.org/W2894822940","https://openalex.org/W2980103036","https://openalex.org/W3121267384","https://openalex.org/W6631021411","https://openalex.org/W6677508755","https://openalex.org/W6750826425","https://openalex.org/W6768974539"],"related_works":["https://openalex.org/W4206419925","https://openalex.org/W2207671162","https://openalex.org/W2901944323","https://openalex.org/W1596354123","https://openalex.org/W4392707306","https://openalex.org/W4379177019","https://openalex.org/W4242556379","https://openalex.org/W3018564381","https://openalex.org/W2964620473","https://openalex.org/W1666098593"],"abstract_inverted_index":{"Precision":[0],"agriculture":[1],"applications,":[2],"which":[3],"include":[4],"spatially-explicit":[5],"irrigation":[6],"scheduling,":[7],"nutrient":[8],"application,":[9],"and":[10,36,70,98,125,136],"disease":[11,68],"management,":[12],"could":[13,27],"greatly":[14],"benefit":[15],"from":[16],"accurate":[17,60],"assessment":[18],"of":[19,32,67,80],"crop":[20,33,57,83],"physiological":[21],"stages.":[22],"Such":[23],"an":[24,55],"identification":[25],"strategy":[26],"contribute":[28],"to":[29,76,145,153],"improved":[30,37],"timing":[31],"management":[34,69],"interventions":[35],"yields.":[38],"Snap":[39],"bean":[40,82],"as":[41,129],"a":[42,105,119],"crop,":[43],"valued":[44],"at":[45],"over":[46,88],"$400":[47],"million":[48],"dollars":[49],"annually":[50],"in":[51,65,104,118],"the":[52],"USA,":[53],"is":[54],"example":[56],"that":[58,149],"require":[59],"maturity":[61,91],"stage":[62],"classification,":[63],"especially":[64],"context":[66],"harvest":[71],"scheduling.":[72],"This":[73],"study":[74],"aimed":[75],"assess":[77],"growth":[78],"classification":[79,109],"snap":[81],"via":[84],"machine":[85],"learning":[86],"approaches":[87],"four":[89],"major":[90],"stages,":[92],"namely":[93],"vegetative":[94],"growth,":[95],"budding,":[96],"flowering,":[97],"pod":[99],"formation":[100],"using":[101],"hyperspectral":[102],"data,":[103],"greenhouse":[106],"setting.":[107],"Our":[108],"results":[110,139],"show":[111,140],"high":[112],"discrimination":[113],"(mean-per-class":[114],"accuracy":[115],"=":[116],"0.69-0.82)":[117],"one-vs-rest":[120],"fashion":[121],"with":[122],"both":[123],"parametric":[124],"non-parametric":[126],"classifiers,":[127],"such":[128],"logistic":[130],"regression,":[131],"na\u00efve":[132],"Bayes,":[133],"random":[134],"forest,":[135],"perceptron.":[137],"These":[138],"promise":[141],"for":[142],"potential":[143],"extension":[144],"remote":[146],"sensing":[147],"solutions":[148],"would":[150],"allow":[151],"growers":[152],"better":[154],"manage":[155],"their":[156],"crops.":[157]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
