{"id":"https://openalex.org/W4313260294","doi":"https://doi.org/10.3390/rs15010100","title":"Dynamic Maize Yield Predictions Using Machine Learning on Multi-Source Data","display_name":"Dynamic Maize Yield Predictions Using Machine Learning on Multi-Source Data","publication_year":2022,"publication_date":"2022-12-24","ids":{"openalex":"https://openalex.org/W4313260294","doi":"https://doi.org/10.3390/rs15010100"},"language":"en","primary_location":{"id":"doi:10.3390/rs15010100","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15010100","pdf_url":"https://www.mdpi.com/2072-4292/15/1/100/pdf?version=1672826137","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/15/1/100/pdf?version=1672826137","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022101453","display_name":"Michele Croci","orcid":"https://orcid.org/0000-0001-7356-2774"},"institutions":[{"id":"https://openalex.org/I103320735","display_name":"Universit\u00e0 Cattolica del Sacro Cuore","ror":"https://ror.org/03h7r5v07","country_code":"IT","type":"education","lineage":["https://openalex.org/I103320735"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Michele Croci","raw_affiliation_strings":["Department of Sustainable Crop Production, Universit\u00e0 Cattolica del Sacro Cuore, 29122 Piacenza, Italy","Remote Sensing and Spatial Analysis Research Center (CRAST), Universit\u00e0 Cattolica del Sacro Cuore, 29122 Piacenza, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Sustainable Crop Production, Universit\u00e0 Cattolica del Sacro Cuore, 29122 Piacenza, Italy","institution_ids":["https://openalex.org/I103320735"]},{"raw_affiliation_string":"Remote Sensing and Spatial Analysis Research Center (CRAST), Universit\u00e0 Cattolica del Sacro Cuore, 29122 Piacenza, Italy","institution_ids":["https://openalex.org/I103320735"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072508410","display_name":"Giorgio Impollonia","orcid":"https://orcid.org/0000-0002-9878-6595"},"institutions":[{"id":"https://openalex.org/I103320735","display_name":"Universit\u00e0 Cattolica del Sacro Cuore","ror":"https://ror.org/03h7r5v07","country_code":"IT","type":"education","lineage":["https://openalex.org/I103320735"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giorgio Impollonia","raw_affiliation_strings":["Department of Sustainable Crop Production, Universit\u00e0 Cattolica del Sacro Cuore, 29122 Piacenza, Italy","Remote Sensing and Spatial Analysis Research Center (CRAST), Universit\u00e0 Cattolica del Sacro Cuore, 29122 Piacenza, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Sustainable Crop Production, Universit\u00e0 Cattolica del Sacro Cuore, 29122 Piacenza, Italy","institution_ids":["https://openalex.org/I103320735"]},{"raw_affiliation_string":"Remote Sensing and Spatial Analysis Research Center (CRAST), Universit\u00e0 Cattolica del Sacro Cuore, 29122 Piacenza, Italy","institution_ids":["https://openalex.org/I103320735"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020570515","display_name":"Michele Meroni","orcid":"https://orcid.org/0000-0002-2976-603X"},"institutions":[{"id":"https://openalex.org/I4210118689","display_name":"Joint Research Centre","ror":"https://ror.org/02qezmz13","country_code":"IT","type":"government","lineage":["https://openalex.org/I1320481043","https://openalex.org/I2800387288","https://openalex.org/I4210118689","https://openalex.org/I4210161702"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Michele Meroni","raw_affiliation_strings":["European Commission, Joint Research Centre (JRC), Via E. Fermi 2749, 21027 Ispra, Italy"],"affiliations":[{"raw_affiliation_string":"European Commission, Joint Research Centre (JRC), Via E. Fermi 2749, 21027 Ispra, Italy","institution_ids":["https://openalex.org/I4210118689"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058892239","display_name":"Stefano Amaducci","orcid":null},"institutions":[{"id":"https://openalex.org/I103320735","display_name":"Universit\u00e0 Cattolica del Sacro Cuore","ror":"https://ror.org/03h7r5v07","country_code":"IT","type":"education","lineage":["https://openalex.org/I103320735"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Stefano Amaducci","raw_affiliation_strings":["Department of Sustainable Crop Production, Universit\u00e0 Cattolica del Sacro Cuore, 29122 Piacenza, Italy","Remote Sensing and Spatial Analysis Research Center (CRAST), Universit\u00e0 Cattolica del Sacro Cuore, 29122 Piacenza, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Sustainable Crop Production, Universit\u00e0 Cattolica del Sacro Cuore, 29122 Piacenza, Italy","institution_ids":["https://openalex.org/I103320735"]},{"raw_affiliation_string":"Remote Sensing and Spatial Analysis Research Center (CRAST), Universit\u00e0 Cattolica del Sacro Cuore, 29122 Piacenza, Italy","institution_ids":["https://openalex.org/I103320735"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5022101453"],"corresponding_institution_ids":["https://openalex.org/I103320735"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":8.0018,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.97478754,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"15","issue":"1","first_page":"100","last_page":"100"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12093","display_name":"Greenhouse Technology and Climate Control","score":0.9815999865531921,"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":0.9815999865531921,"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/T12310","display_name":"Crop Yield and Soil Fertility","score":0.9805999994277954,"subfield":{"id":"https://openalex.org/subfields/1102","display_name":"Agronomy and Crop 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":0.9775000214576721,"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/principal-component-analysis","display_name":"Principal component analysis","score":0.624732494354248},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5130733251571655},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4752380847930908},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.4741377532482147},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4640663266181946},{"id":"https://openalex.org/keywords/yield","display_name":"Yield (engineering)","score":0.43497782945632935},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4319508373737335},{"id":"https://openalex.org/keywords/production","display_name":"Production (economics)","score":0.41097280383110046},{"id":"https://openalex.org/keywords/agricultural-engineering","display_name":"Agricultural engineering","score":0.3523399829864502},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3222578763961792}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.624732494354248},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5130733251571655},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4752380847930908},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.4741377532482147},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4640663266181946},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.43497782945632935},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4319508373737335},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.41097280383110046},{"id":"https://openalex.org/C88463610","wikidata":"https://www.wikidata.org/wiki/Q194118","display_name":"Agricultural engineering","level":1,"score":0.3523399829864502},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3222578763961792},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/rs15010100","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15010100","pdf_url":"https://www.mdpi.com/2072-4292/15/1/100/pdf?version=1672826137","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:e50d1d7744534c6bbacc656ddacefc77","is_oa":true,"landing_page_url":"https://doaj.org/article/e50d1d7744534c6bbacc656ddacefc77","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 15, Iss 1, p 100 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/1/100/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15010100","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":"Remote Sensing; Volume 15; Issue 1; Pages: 100","raw_type":"Text"},{"id":"pmh:oai:publicatt.unicatt.it:10807/230861","is_oa":true,"landing_page_url":"https://hdl.handle.net/10807/230861","pdf_url":null,"source":{"id":"https://openalex.org/S4306400564","display_name":"PubliCatt (Universit\u00e0 Cattolica del Sacro Cuore)","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.3390/rs15010100","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15010100","pdf_url":"https://www.mdpi.com/2072-4292/15/1/100/pdf?version=1672826137","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4313260294.pdf","grobid_xml":"https://content.openalex.org/works/W4313260294.grobid-xml"},"referenced_works_count":96,"referenced_works":["https://openalex.org/W429766147","https://openalex.org/W612661449","https://openalex.org/W1484867920","https://openalex.org/W1598808445","https://openalex.org/W1657213141","https://openalex.org/W1967720470","https://openalex.org/W1976835088","https://openalex.org/W1978617972","https://openalex.org/W1981552604","https://openalex.org/W1986072339","https://openalex.org/W1987415163","https://openalex.org/W1994552280","https://openalex.org/W2007342648","https://openalex.org/W2021662310","https://openalex.org/W2035450210","https://openalex.org/W2038136715","https://openalex.org/W2039604550","https://openalex.org/W2040417533","https://openalex.org/W2043791654","https://openalex.org/W2056251274","https://openalex.org/W2056435747","https://openalex.org/W2067069641","https://openalex.org/W2071110539","https://openalex.org/W2075844317","https://openalex.org/W2077562320","https://openalex.org/W2087506358","https://openalex.org/W2091085232","https://openalex.org/W2093136488","https://openalex.org/W2112056217","https://openalex.org/W2113410727","https://openalex.org/W2137672422","https://openalex.org/W2139303505","https://openalex.org/W2140308441","https://openalex.org/W2148333466","https://openalex.org/W2165498247","https://openalex.org/W2186316341","https://openalex.org/W2195361594","https://openalex.org/W2295124130","https://openalex.org/W2401339497","https://openalex.org/W2414117070","https://openalex.org/W2499691472","https://openalex.org/W2587466508","https://openalex.org/W2725897987","https://openalex.org/W2767072270","https://openalex.org/W2768533279","https://openalex.org/W2790628032","https://openalex.org/W2790973472","https://openalex.org/W2800451846","https://openalex.org/W2810045082","https://openalex.org/W2894129447","https://openalex.org/W2898543370","https://openalex.org/W2905983018","https://openalex.org/W2911964244","https://openalex.org/W2912411775","https://openalex.org/W2912622673","https://openalex.org/W2913971899","https://openalex.org/W2915536774","https://openalex.org/W2921360674","https://openalex.org/W2944794516","https://openalex.org/W2947309173","https://openalex.org/W2963852406","https://openalex.org/W2980893954","https://openalex.org/W2987822860","https://openalex.org/W2990480734","https://openalex.org/W2993028524","https://openalex.org/W2995678734","https://openalex.org/W2995946162","https://openalex.org/W2999658315","https://openalex.org/W2999884014","https://openalex.org/W3005029250","https://openalex.org/W3005096076","https://openalex.org/W3035502245","https://openalex.org/W3046135843","https://openalex.org/W3048727648","https://openalex.org/W3079760979","https://openalex.org/W3088305510","https://openalex.org/W3102148818","https://openalex.org/W3104887532","https://openalex.org/W3111700100","https://openalex.org/W3125542187","https://openalex.org/W3132602407","https://openalex.org/W3151770089","https://openalex.org/W3164809178","https://openalex.org/W3165319944","https://openalex.org/W3171916132","https://openalex.org/W3184850568","https://openalex.org/W3189330863","https://openalex.org/W4211049957","https://openalex.org/W4223642858","https://openalex.org/W4293077254","https://openalex.org/W6636950212","https://openalex.org/W6686616827","https://openalex.org/W6715652707","https://openalex.org/W6745313956","https://openalex.org/W6766726207","https://openalex.org/W6779303322"],"related_works":["https://openalex.org/W1968523686","https://openalex.org/W298893735","https://openalex.org/W2199291344","https://openalex.org/W1975632186","https://openalex.org/W2167342507","https://openalex.org/W4247222564","https://openalex.org/W4221140712","https://openalex.org/W2211316729","https://openalex.org/W3027745756","https://openalex.org/W3205213561"],"abstract_inverted_index":{"Timely":[0],"yield":[1,31,103,211,260],"prediction":[2,32,212,261],"is":[3,50],"crucial":[4],"for":[5,54,100,132],"the":[6,17,37,41,55,68,98,102,107,130,146,150,184,196,201,207,210,214,218,230,241,246,254,258,264,271],"agri-food":[7,18],"supply":[8],"chain":[9],"as":[10],"a":[11,30,93],"whole.":[12],"However,":[13],"different":[14,21],"stakeholders":[15],"in":[16,28,67,145,191,228,253],"sector":[19],"require":[20],"levels":[22],"of":[23,58,109,140,153,209,232,240,243,257],"accuracy":[24,177],"and":[25,75,89,92,119,148,158,166,182,213,251],"lead":[26],"times":[27],"which":[29,217],"should":[33],"be":[34],"available.":[35],"For":[36],"producers,":[38],"predictions":[39],"during":[40],"growing":[42],"season":[43,69,147],"are":[44,206,222],"essential":[45],"to":[46,70,96],"ensure":[47],"that":[48,200],"information":[49],"available":[51],"early":[52],"enough":[53],"timely":[56],"implementation":[57],"agronomic":[59],"decisions,":[60],"while":[61],"industries":[62],"can":[63],"wait":[64],"until":[65],"later":[66],"optimize":[71],"their":[72,77,175],"production":[73,78],"process":[74,126],"increase":[76],"traceability.":[79],"In":[80,105,161],"this":[81,235],"study,":[82],"we":[83],"used":[84],"machine":[85,219],"learning":[86,220],"algorithms,":[87],"dynamic":[88],"static":[90],"predictors,":[91],"phenology":[94],"approach":[95],"determine":[97],"time":[99],"issuing":[101],"prediction.":[104],"addition,":[106],"effect":[108],"data":[110],"reduction":[111,248],"was":[112,129,142,226,245],"evaluated":[113],"by":[114],"comparing":[115],"results":[116],"obtained":[117,143],"with":[118,149,178,216],"without":[120],"principal":[121],"component":[122],"analysis":[123],"(PCA).":[124],"Gaussian":[125],"regression":[127],"(GPR)":[128],"best":[131,137,176],"predicting":[133],"maize":[134,259],"yield.":[135],"Its":[136],"performance":[138,192,205,262],"(nRMSE":[139],"13.31%)":[141],"late":[144],"full":[151],"set":[152],"predictors":[154,215],"(vegetation":[155],"indices,":[156],"meteorological":[157],"soil":[159],"predictors).":[160],"contrast,":[162],"neural":[163],"network":[164],"(NNET)":[165],"support":[167],"vector":[168],"machines":[169],"linear":[170],"basis":[171],"function":[172],"(SVMl)":[173],"achieved":[174],"only":[179],"vegetation":[180],"indices":[181],"at":[183],"tasseling":[185],"phenological":[186],"stage.":[187,236],"Only":[188],"slight":[189],"differences":[190],"were":[193],"observed":[194],"between":[195,249],"algorithms":[197,221],"considered,":[198],"highlighting":[199],"main":[202],"factors":[203],"influencing":[204],"timing":[208],"fed.":[223],"Interestingly,":[224],"PCA":[225,244],"instrumental":[227],"increasing":[229],"performances":[231],"NNET":[233],"after":[234],"An":[237],"additional":[238],"benefit":[239],"application":[242],"overall":[247],"12":[250],"30.20%":[252],"standard":[255],"deviation":[256],"from":[263],"leave":[265],"one-year":[266],"outer-loop":[267],"cross-validation,":[268],"depending":[269],"on":[270],"feature":[272],"set.":[273]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":9}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2023-01-06T00:00:00"}
