{"id":"https://openalex.org/W4402264816","doi":"https://doi.org/10.1109/igarss53475.2024.10641757","title":"Optimizing Crop Yield Prediction: Inter-Dated Vegetation Indices &amp; Automl Ensembles in Processing Tomato Crop","display_name":"Optimizing Crop Yield Prediction: Inter-Dated Vegetation Indices &amp; Automl Ensembles in Processing Tomato Crop","publication_year":2024,"publication_date":"2024-07-07","ids":{"openalex":"https://openalex.org/W4402264816","doi":"https://doi.org/10.1109/igarss53475.2024.10641757"},"language":"en","primary_location":{"id":"doi:10.1109/igarss53475.2024.10641757","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss53475.2024.10641757","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5015891344","display_name":"Nicoleta Darra","orcid":null},"institutions":[{"id":"https://openalex.org/I109954829","display_name":"Agricultural University of Athens","ror":"https://ror.org/03xawq568","country_code":"GR","type":"education","lineage":["https://openalex.org/I109954829"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Nicoleta Darra","raw_affiliation_strings":["Agricultural University of Athens,Department of Natural Resources and Agricultural Engineering,Athens,Greece,11855"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Agricultural University of Athens,Department of Natural Resources and Agricultural Engineering,Athens,Greece,11855","institution_ids":["https://openalex.org/I109954829"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034472057","display_name":"Borja Espejo Garcia","orcid":null},"institutions":[{"id":"https://openalex.org/I109954829","display_name":"Agricultural University of Athens","ror":"https://ror.org/03xawq568","country_code":"GR","type":"education","lineage":["https://openalex.org/I109954829"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Borja Espejo Garcia","raw_affiliation_strings":["Agricultural University of Athens,Department of Natural Resources and Agricultural Engineering,Athens,Greece,11855"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Agricultural University of Athens,Department of Natural Resources and Agricultural Engineering,Athens,Greece,11855","institution_ids":["https://openalex.org/I109954829"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017549398","display_name":"Emmanouil Psomiadis","orcid":"https://orcid.org/0000-0002-1094-9397"},"institutions":[{"id":"https://openalex.org/I109954829","display_name":"Agricultural University of Athens","ror":"https://ror.org/03xawq568","country_code":"GR","type":"education","lineage":["https://openalex.org/I109954829"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Emmanouil Psomiadis","raw_affiliation_strings":["Agricultural University of Athens,Department of Natural Resources and Agricultural Engineering,Athens,Greece,11855"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Agricultural University of Athens,Department of Natural Resources and Agricultural Engineering,Athens,Greece,11855","institution_ids":["https://openalex.org/I109954829"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109698230","display_name":"Spyros Fountas","orcid":null},"institutions":[{"id":"https://openalex.org/I109954829","display_name":"Agricultural University of Athens","ror":"https://ror.org/03xawq568","country_code":"GR","type":"education","lineage":["https://openalex.org/I109954829"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Spyros Fountas","raw_affiliation_strings":["Agricultural University of Athens,Department of Natural Resources and Agricultural Engineering,Athens,Greece,11855"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Agricultural University of Athens,Department of Natural Resources and Agricultural Engineering,Athens,Greece,11855","institution_ids":["https://openalex.org/I109954829"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I109954829"],"apc_list":null,"apc_paid":null,"fwci":0.874,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.7299022,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"4320","last_page":"4324"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9965000152587891,"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/T10616","display_name":"Smart Agriculture and AI","score":0.9965000152587891,"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":0.9948999881744385,"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"}},{"id":"https://openalex.org/T14365","display_name":"Leaf Properties and Growth Measurement","score":0.9829999804496765,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/crop","display_name":"Crop","score":0.7011588215827942},{"id":"https://openalex.org/keywords/vegetation","display_name":"Vegetation (pathology)","score":0.5851259231567383},{"id":"https://openalex.org/keywords/yield","display_name":"Yield (engineering)","score":0.5216584205627441},{"id":"https://openalex.org/keywords/crop-yield","display_name":"Crop yield","score":0.412864625453949},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.37002840638160706},{"id":"https://openalex.org/keywords/agricultural-engineering","display_name":"Agricultural engineering","score":0.357321560382843},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33067572116851807},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.18434524536132812},{"id":"https://openalex.org/keywords/agronomy","display_name":"Agronomy","score":0.1531931459903717},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.14511215686798096},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11525806784629822}],"concepts":[{"id":"https://openalex.org/C137580998","wikidata":"https://www.wikidata.org/wiki/Q235352","display_name":"Crop","level":2,"score":0.7011588215827942},{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.5851259231567383},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.5216584205627441},{"id":"https://openalex.org/C126343540","wikidata":"https://www.wikidata.org/wiki/Q889514","display_name":"Crop yield","level":2,"score":0.412864625453949},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.37002840638160706},{"id":"https://openalex.org/C88463610","wikidata":"https://www.wikidata.org/wiki/Q194118","display_name":"Agricultural engineering","level":1,"score":0.357321560382843},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33067572116851807},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.18434524536132812},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.1531931459903717},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.14511215686798096},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11525806784629822},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss53475.2024.10641757","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss53475.2024.10641757","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Zero hunger","score":0.7599999904632568,"id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W80625533","https://openalex.org/W225220184","https://openalex.org/W1988790447","https://openalex.org/W2056132907","https://openalex.org/W2065742895","https://openalex.org/W2085755679","https://openalex.org/W2099201756","https://openalex.org/W2113004751","https://openalex.org/W2121791972","https://openalex.org/W2132862423","https://openalex.org/W2150140969","https://openalex.org/W2182361439","https://openalex.org/W2616613682","https://openalex.org/W2810559460","https://openalex.org/W2810908757","https://openalex.org/W2890565173","https://openalex.org/W2915777673","https://openalex.org/W2963935416","https://openalex.org/W2971456001","https://openalex.org/W2988471827","https://openalex.org/W2997051686","https://openalex.org/W3031909544","https://openalex.org/W3093567807","https://openalex.org/W3099701207","https://openalex.org/W3160199649","https://openalex.org/W4232872062","https://openalex.org/W4322502996","https://openalex.org/W4386913100","https://openalex.org/W4400762160","https://openalex.org/W6636950212","https://openalex.org/W6685961532"],"related_works":["https://openalex.org/W2018149064","https://openalex.org/W2002738406","https://openalex.org/W2985080412","https://openalex.org/W3006201793","https://openalex.org/W4378566980","https://openalex.org/W139018289","https://openalex.org/W2065828020","https://openalex.org/W2380001790","https://openalex.org/W2515171211","https://openalex.org/W1979405749"],"abstract_inverted_index":{"This":[0,124],"study":[1],"advances":[2],"crop":[3,139],"yield":[4,23,44,121,140],"prediction":[5,122],"by":[6],"leveraging":[7],"multi-date":[8,131],"Sentinel-2":[9],"data,":[10],"spectral":[11,29,54,135],"bands,":[12],"and":[13,36,47,80,105,133],"vegetation":[14],"indices":[15],"(VIs)":[16],"to":[17,57],"enhance":[18],"accuracy":[19],"in":[20,120,142],"processing":[21,143],"tomato":[22],"modeling.":[24],"It":[25],"identified":[26],"the":[27,37,58,87,99,127],"optimal":[28],"bands":[30,55,77,100,136],"(B4,":[31],"B6,":[32],"B7,":[33,79],"B8,":[34,78],"B8A)":[35],"ideal":[38],"period":[39],"(80-90":[40],"days":[41,104,109],"post-transplanting)":[42],"for":[43,137],"prediction.":[45],"NDVI":[46,62],"RVI":[48,71,97],"were":[49],"also":[50],"utilized":[51],"using":[52],"different":[53],"corresponding":[56],"NIR":[59],"wavelength.":[60],"Notably,":[61],"excelled":[63],"with":[64,76,96],"band":[65],"B8":[66],"at":[67,102,107],"80":[68],"days,":[69],"while":[70],"showed":[72],"similar":[73],"performance":[74,88],"trends":[75],"B8A.":[81],"By":[82],"following":[83],"an":[84,93],"inter-date":[85],"approach":[86],"was":[89],"notably":[90],"improved":[91,138],"reaching":[92],"R2of":[94],"0.60,":[95],"encompassing":[98],"B8A":[101],"75":[103],"B4":[106],"90":[108],"post-transplanting.":[110],"Moreover,":[111],"AutoML":[112],"consistently":[113],"outperformed":[114],"linear":[115],"models,":[116],"validating":[117],"its":[118],"reliability":[119],"methodologies.":[123],"investigation":[125],"highlights":[126],"potential":[128],"of":[129],"integrating":[130],"data":[132],"diverse":[134],"estimation":[141],"tomatoes.":[144]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
