{"id":"https://openalex.org/W4224311935","doi":"https://doi.org/10.3390/s22093249","title":"Predicting Grape Sugar Content under Quality Attributes Using Normalized Difference Vegetation Index Data and Automated Machine Learning","display_name":"Predicting Grape Sugar Content under Quality Attributes Using Normalized Difference Vegetation Index Data and Automated Machine Learning","publication_year":2022,"publication_date":"2022-04-23","ids":{"openalex":"https://openalex.org/W4224311935","doi":"https://doi.org/10.3390/s22093249","pmid":"https://pubmed.ncbi.nlm.nih.gov/35590939"},"language":"en","primary_location":{"id":"doi:10.3390/s22093249","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22093249","pdf_url":"https://www.mdpi.com/1424-8220/22/9/3249/pdf?version=1650788427","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/22/9/3249/pdf?version=1650788427","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061183529","display_name":"Aikaterini Kasimati","orcid":"https://orcid.org/0000-0002-7620-3782"},"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":true,"raw_author_name":"Aikaterini Kasimati","raw_affiliation_strings":["Laboratory of Agricultural Machinery, Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75 Iera Odos Str., 11855 Athens, Greece"],"raw_orcid":"https://orcid.org/0000-0002-7620-3782","affiliations":[{"raw_affiliation_string":"Laboratory of Agricultural Machinery, Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75 Iera Odos Str., 11855 Athens, Greece","institution_ids":["https://openalex.org/I109954829"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019168467","display_name":"Borja Espejo-Garc\u00eda","orcid":"https://orcid.org/0000-0003-2733-680X"},"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-Garc\u00eda","raw_affiliation_strings":["Laboratory of Agricultural Machinery, Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75 Iera Odos Str., 11855 Athens, Greece"],"raw_orcid":"https://orcid.org/0000-0003-2733-680X","affiliations":[{"raw_affiliation_string":"Laboratory of Agricultural Machinery, Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75 Iera Odos Str., 11855 Athens, Greece","institution_ids":["https://openalex.org/I109954829"]}]},{"author_position":"middle","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":["Laboratory of Agricultural Machinery, Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75 Iera Odos Str., 11855 Athens, Greece"],"raw_orcid":"https://orcid.org/0000-0002-4130-7303","affiliations":[{"raw_affiliation_string":"Laboratory of Agricultural Machinery, Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75 Iera Odos Str., 11855 Athens, Greece","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":["Laboratory of Agricultural Machinery, Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75 Iera Odos Str., 11855 Athens, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory of Agricultural Machinery, Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75 Iera Odos Str., 11855 Athens, Greece","institution_ids":["https://openalex.org/I109954829"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5061183529"],"corresponding_institution_ids":["https://openalex.org/I109954829"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":7.7718,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.97276405,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"22","issue":"9","first_page":"3249","last_page":"3249"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11796","display_name":"Horticultural and Viticultural Research","score":0.9998000264167786,"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/T11796","display_name":"Horticultural and Viticultural Research","score":0.9998000264167786,"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":0.9995999932289124,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental 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/normalized-difference-vegetation-index","display_name":"Normalized Difference Vegetation Index","score":0.7123574018478394},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6510699987411499},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6106913089752197},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.534440279006958},{"id":"https://openalex.org/keywords/vegetation","display_name":"Vegetation (pathology)","score":0.4957660138607025},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49336257576942444},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4366135895252228},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.4362209439277649},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4120883345603943},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3643474578857422},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33513832092285156},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30367839336395264},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2737728953361511},{"id":"https://openalex.org/keywords/leaf-area-index","display_name":"Leaf area index","score":0.20159700512886047},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09185311198234558},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.08618563413619995}],"concepts":[{"id":"https://openalex.org/C1549246","wikidata":"https://www.wikidata.org/wiki/Q718775","display_name":"Normalized Difference Vegetation Index","level":3,"score":0.7123574018478394},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6510699987411499},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6106913089752197},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.534440279006958},{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.4957660138607025},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49336257576942444},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4366135895252228},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4362209439277649},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4120883345603943},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3643474578857422},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33513832092285156},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30367839336395264},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2737728953361511},{"id":"https://openalex.org/C25989453","wikidata":"https://www.wikidata.org/wiki/Q446746","display_name":"Leaf area index","level":2,"score":0.20159700512886047},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09185311198234558},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.08618563413619995},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000072480","descriptor_name":"Farms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000072480","descriptor_name":"Farms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000072480","descriptor_name":"Farms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000073893","descriptor_name":"Sugars","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000073893","descriptor_name":"Sugars","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000073893","descriptor_name":"Sugars","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D027843","descriptor_name":"Vitis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D027843","descriptor_name":"Vitis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D027843","descriptor_name":"Vitis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D058998","descriptor_name":"Remote Sensing Technology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D058998","descriptor_name":"Remote Sensing Technology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D058998","descriptor_name":"Remote Sensing Technology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":5,"locations":[{"id":"doi:10.3390/s22093249","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22093249","pdf_url":"https://www.mdpi.com/1424-8220/22/9/3249/pdf?version=1650788427","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:35590939","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35590939","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:0bb860a21a8440398800c711d3d5b0b8","is_oa":true,"landing_page_url":"https://doaj.org/article/0bb860a21a8440398800c711d3d5b0b8","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 22, Iss 9, p 3249 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/22/9/3249/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s22093249","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 22; Issue 9; Pages: 3249","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:9102316","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9102316","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s22093249","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22093249","pdf_url":"https://www.mdpi.com/1424-8220/22/9/3249/pdf?version=1650788427","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4224311935.pdf","grobid_xml":"https://content.openalex.org/works/W4224311935.grobid-xml"},"referenced_works_count":60,"referenced_works":["https://openalex.org/W52046274","https://openalex.org/W1560484089","https://openalex.org/W1570936387","https://openalex.org/W1892082890","https://openalex.org/W1967417918","https://openalex.org/W1980711477","https://openalex.org/W1988790447","https://openalex.org/W1989351818","https://openalex.org/W2002320280","https://openalex.org/W2005914865","https://openalex.org/W2018764772","https://openalex.org/W2045717778","https://openalex.org/W2056132907","https://openalex.org/W2065309816","https://openalex.org/W2065742895","https://openalex.org/W2101234009","https://openalex.org/W2131632403","https://openalex.org/W2151499786","https://openalex.org/W2151554678","https://openalex.org/W2164324816","https://openalex.org/W2165703940","https://openalex.org/W2167719861","https://openalex.org/W2182361439","https://openalex.org/W2186208902","https://openalex.org/W2600037548","https://openalex.org/W2606453977","https://openalex.org/W2617056706","https://openalex.org/W2621178107","https://openalex.org/W2741850261","https://openalex.org/W2763672874","https://openalex.org/W2766378890","https://openalex.org/W2773985483","https://openalex.org/W2782999127","https://openalex.org/W2809959615","https://openalex.org/W2809985736","https://openalex.org/W2810908757","https://openalex.org/W2888749775","https://openalex.org/W2911566102","https://openalex.org/W2913947176","https://openalex.org/W2945292609","https://openalex.org/W2955309678","https://openalex.org/W2958462897","https://openalex.org/W2959197972","https://openalex.org/W2972711576","https://openalex.org/W3014218362","https://openalex.org/W3022760892","https://openalex.org/W3088561064","https://openalex.org/W3126156081","https://openalex.org/W3127812658","https://openalex.org/W3134816142","https://openalex.org/W3134831088","https://openalex.org/W3155755426","https://openalex.org/W3161063006","https://openalex.org/W3171946070","https://openalex.org/W3175053552","https://openalex.org/W4213308398","https://openalex.org/W4239510810","https://openalex.org/W6675354045","https://openalex.org/W6685961532","https://openalex.org/W6791327565"],"related_works":["https://openalex.org/W3207046288","https://openalex.org/W4396689146","https://openalex.org/W4200112873","https://openalex.org/W2955796858","https://openalex.org/W2004826645","https://openalex.org/W2048488252","https://openalex.org/W2940614149","https://openalex.org/W4288365262","https://openalex.org/W2787485953","https://openalex.org/W3217432596"],"abstract_inverted_index":{"Wine":[0],"grapes":[1],"need":[2],"frequent":[3],"monitoring":[4],"to":[5,22,37,73,93,236],"achieve":[6],"high":[7],"yields":[8],"and":[9,16,26,29,61,99,121,144,151,179,183,192,202,207,225,253,269,275,300,308,315,366],"quality.":[10,76],"Non-destructive":[11],"methods,":[12],"such":[13],"as":[14,311,313],"proximal":[15,135],"remote":[17,146],"sensing,":[18],"are":[19,34,326],"commonly":[20],"used":[21,36],"estimate":[23],"crop":[24,75,354],"yield":[25],"quality":[27,53,114,355],"characteristics,":[28],"spectral":[30],"vegetation":[31],"indices":[32],"(VIs)":[33],"often":[35],"present":[38],"site-specific":[39],"information.":[40],"Analysis":[41],"of":[42,55,84,112,169,205,220,282,298,353],"laboratory":[43],"samples":[44],"is":[45,59],"the":[46,52,81,91,149,170,200,262,280,291,319,351],"most":[47],"popular":[48],"method":[49],"for":[50,109,128,266,290],"determining":[51],"characteristics":[54],"grapes,":[56],"although":[57],"it":[58],"time-consuming":[60],"expensive.":[62],"In":[63,101],"recent":[64],"years,":[65],"several":[66],"machine":[67,87,165,332],"learning-based":[68],"methods":[69,185],"have":[70],"been":[71],"developed":[72],"predict":[74],"Although":[77],"these":[78],"techniques":[79,120],"require":[80],"extensive":[82],"involvement":[83],"experts,":[85],"automated":[86],"learning":[88,166,333],"(AutoML)":[89],"offers":[90],"possibility":[92],"improve":[94],"this":[95,102],"task,":[96],"saving":[97],"time":[98],"resources.":[100],"paper,":[103],"we":[104],"propose":[105],"an":[106],"innovative":[107],"approach":[108],"robust":[110],"prediction":[111],"grape":[113,231],"attributes":[115],"by":[116],"combining":[117,272],"open-source":[118],"AutoML":[119,254,343],"Normalized":[122],"Difference":[123],"Vegetation":[124],"Index":[125],"(NDVI)":[126],"data":[127,208,228],"vineyards":[129],"obtained":[130],"from":[131,141],"four":[132],"different":[133,203],"platforms-two":[134],"vehicle-mounted":[136],"canopy":[137,241],"reflectance":[138],"sensors,":[139],"orthomosaics":[140],"UAV":[142,307],"images":[143],"Sentinel-2":[145],"sensing":[147],"imagery-during":[148],"2019":[150,268],"2020":[152],"growing":[153,212],"seasons.":[154],"We":[155],"investigated":[156],"AutoML,":[157],"extending":[158],"our":[159],"earlier":[160],"work":[161,330,365],"on":[162,331],"manually":[163,247,337],"fine-tuned":[164,248],"methods.":[167],"Results":[168,216],"two":[171,211],"approaches":[172],"using":[173],"Ordinary":[174],"Least":[175],"Square":[176],"(OLS),":[177],"Theil-Sen":[178],"Huber":[180],"regression":[181],"models":[182,244],"tree-based":[184],"were":[186,197,214,336],"compared.":[187],"Support":[188],"Vector":[189],"Machines":[190],"(SVMs)":[191],"Automatic":[193],"Relevance":[194],"Determination":[195],"(ARD)":[196],"included":[198],"in":[199,229,234],"analysis":[201],"combinations":[204,297],"sensors":[206,274,299],"collected":[209],"over":[210],"seasons":[213],"investigated.":[215],"showed":[217],"promising":[218],"performance":[219,347],"Unmanned":[221],"Aerial":[222],"Vehicle":[223],"(UAV)":[224],"Spectrosense+":[226,309],"GPS":[227],"predicting":[230],"sugars,":[232],"especially":[233],"mid":[235],"late":[237],"season":[238],"with":[239,245,261,328],"full":[240],"growth.":[242],"Regression":[243],"both":[246,267,304],"ML":[249],"(R\u00b2":[250,255],"=":[251,256],"0.61)":[252],"0.65)":[257],"provided":[258],"similar":[259],"results,":[260],"latter":[263],"slightly":[264],"improved":[265,285],"2020.":[270],"When":[271],"multiple":[273],"growth":[276,301],"stages":[277,302],"per":[278],"year,":[279],"coefficient":[281],"determination":[283],"R\u00b2":[284,322],"even":[286],"more":[287],"averaging":[288],"0.66":[289],"best-fitting":[292],"regressions.":[293],"Also,":[294],"when":[295],"considering":[296],"across":[303],"cropping":[305],"seasons,":[306],"GPS,":[310],"well":[312],"V\u00e9raison":[314],"Flowering,":[316],"each":[317],"had":[318],"highest":[320],"average":[321],"values.":[323],"These":[324,339],"performances":[325],"consistent":[327],"previous":[329],"algorithms":[334],"that":[335,342],"fine-tuned.":[338],"results":[340],"suggest":[341],"has":[344],"greater":[345],"long-term":[346],"potential.":[348],"To":[349],"increase":[350],"efficiency":[352],"prediction,":[356],"a":[357],"balance":[358],"must":[359],"be":[360],"struck":[361],"between":[362],"manual":[363],"expert":[364],"AutoML.":[367]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":6}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}