{"id":"https://openalex.org/W4415427418","doi":"https://doi.org/10.3233/faia251477","title":"Informed Learning for Estimating Drought Stress at Fine-Scale Resolution Enables Accurate Yield Prediction","display_name":"Informed Learning for Estimating Drought Stress at Fine-Scale Resolution Enables Accurate Yield Prediction","publication_year":2025,"publication_date":"2025-10-21","ids":{"openalex":"https://openalex.org/W4415427418","doi":"https://doi.org/10.3233/faia251477"},"language":null,"primary_location":{"id":"doi:10.3233/faia251477","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia251477","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.3233/faia251477","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019450085","display_name":"Miro Miranda","orcid":"https://orcid.org/0009-0002-8195-9776"},"institutions":[{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]},{"id":"https://openalex.org/I153267046","display_name":"University of Kaiserslautern","ror":"https://ror.org/04zrf7b53","country_code":"DE","type":"education","lineage":["https://openalex.org/I153267046"]},{"id":"https://openalex.org/I169381384","display_name":"University of Groningen","ror":"https://ror.org/012p63287","country_code":"NL","type":"education","lineage":["https://openalex.org/I169381384"]},{"id":"https://openalex.org/I2802076133","display_name":"University of Koblenz and Landau","ror":"https://ror.org/01j9f6752","country_code":"DE","type":"education","lineage":["https://openalex.org/I2802076133"]}],"countries":["DE","NL"],"is_corresponding":true,"raw_author_name":"Miro Miranda","raw_affiliation_strings":["Bernoulli Institute, University of Groningen, Groningen, Netherlands","Department of Computer Science, University of Kaiserslautern-Landau, Kaiserslautern, Germany","German Research Center for Artificial Intelligence, Kaiserslautern, Germany"],"affiliations":[{"raw_affiliation_string":"Bernoulli Institute, University of Groningen, Groningen, Netherlands","institution_ids":["https://openalex.org/I169381384"]},{"raw_affiliation_string":"Department of Computer Science, University of Kaiserslautern-Landau, Kaiserslautern, Germany","institution_ids":["https://openalex.org/I2802076133","https://openalex.org/I153267046"]},{"raw_affiliation_string":"German Research Center for Artificial Intelligence, Kaiserslautern, Germany","institution_ids":["https://openalex.org/I33256026"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008628120","display_name":"Marcela Charfuel\u00e0n","orcid":"https://orcid.org/0009-0005-6886-0415"},"institutions":[{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marcela Charfuelan","raw_affiliation_strings":["German Research Center for Artificial Intelligence, Kaiserslautern, Germany"],"affiliations":[{"raw_affiliation_string":"German Research Center for Artificial Intelligence, Kaiserslautern, Germany","institution_ids":["https://openalex.org/I33256026"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074132366","display_name":"Mar\u00eda Dolores del Toro","orcid":"https://orcid.org/0000-0002-4935-8754"},"institutions":[{"id":"https://openalex.org/I169381384","display_name":"University of Groningen","ror":"https://ror.org/012p63287","country_code":"NL","type":"education","lineage":["https://openalex.org/I169381384"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Matias Valdenegro Toro","raw_affiliation_strings":["Bernoulli Institute, University of Groningen, Groningen, Netherlands"],"affiliations":[{"raw_affiliation_string":"Bernoulli Institute, University of Groningen, Groningen, Netherlands","institution_ids":["https://openalex.org/I169381384"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101904182","display_name":"Andreas Dengel","orcid":"https://orcid.org/0000-0002-6100-8255"},"institutions":[{"id":"https://openalex.org/I153267046","display_name":"University of Kaiserslautern","ror":"https://ror.org/04zrf7b53","country_code":"DE","type":"education","lineage":["https://openalex.org/I153267046"]},{"id":"https://openalex.org/I2802076133","display_name":"University of Koblenz and Landau","ror":"https://ror.org/01j9f6752","country_code":"DE","type":"education","lineage":["https://openalex.org/I2802076133"]},{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Andreas Dengel","raw_affiliation_strings":["Department of Computer Science, University of Kaiserslautern-Landau, Kaiserslautern, Germany","German Research Center for Artificial Intelligence, Kaiserslautern, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Kaiserslautern-Landau, Kaiserslautern, Germany","institution_ids":["https://openalex.org/I2802076133","https://openalex.org/I153267046"]},{"raw_affiliation_string":"German Research Center for Artificial Intelligence, Kaiserslautern, Germany","institution_ids":["https://openalex.org/I33256026"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5019450085"],"corresponding_institution_ids":["https://openalex.org/I153267046","https://openalex.org/I169381384","https://openalex.org/I2802076133","https://openalex.org/I33256026"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.56457346,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T11404","display_name":"Irrigation Practices and Water Management","score":0.8324000239372253,"subfield":{"id":"https://openalex.org/subfields/1111","display_name":"Soil 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/T11404","display_name":"Irrigation Practices and Water Management","score":0.8324000239372253,"subfield":{"id":"https://openalex.org/subfields/1111","display_name":"Soil 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/T14406","display_name":"Multidisciplinary Science and Engineering Research","score":0.817799985408783,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12365","display_name":"Effects of Environmental Stressors on Livestock","score":0.8108000159263611,"subfield":{"id":"https://openalex.org/subfields/1103","display_name":"Animal Science and Zoology"},"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-yield","display_name":"Crop yield","score":0.6373000144958496},{"id":"https://openalex.org/keywords/water-scarcity","display_name":"Water scarcity","score":0.6292999982833862},{"id":"https://openalex.org/keywords/yield","display_name":"Yield (engineering)","score":0.4738999903202057},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.4510999917984009},{"id":"https://openalex.org/keywords/crop-simulation-model","display_name":"Crop simulation model","score":0.44940000772476196},{"id":"https://openalex.org/keywords/agriculture","display_name":"Agriculture","score":0.4481000006198883}],"concepts":[{"id":"https://openalex.org/C126343540","wikidata":"https://www.wikidata.org/wiki/Q889514","display_name":"Crop yield","level":2,"score":0.6373000144958496},{"id":"https://openalex.org/C51193700","wikidata":"https://www.wikidata.org/wiki/Q5376358","display_name":"Water scarcity","level":3,"score":0.6292999982833862},{"id":"https://openalex.org/C88463610","wikidata":"https://www.wikidata.org/wiki/Q194118","display_name":"Agricultural engineering","level":1,"score":0.5582000017166138},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.4738999903202057},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.4510999917984009},{"id":"https://openalex.org/C2777106113","wikidata":"https://www.wikidata.org/wiki/Q18349347","display_name":"Crop simulation model","level":3,"score":0.44940000772476196},{"id":"https://openalex.org/C118518473","wikidata":"https://www.wikidata.org/wiki/Q11451","display_name":"Agriculture","level":2,"score":0.4481000006198883},{"id":"https://openalex.org/C2777399377","wikidata":"https://www.wikidata.org/wiki/Q17073957","display_name":"DSSAT","level":3,"score":0.4438999891281128},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.41179999709129333},{"id":"https://openalex.org/C2778361644","wikidata":"https://www.wikidata.org/wiki/Q8053545","display_name":"Yield gap","level":3,"score":0.3928999900817871},{"id":"https://openalex.org/C120217122","wikidata":"https://www.wikidata.org/wiki/Q740083","display_name":"Precision agriculture","level":3,"score":0.3163999915122986},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.311599999666214},{"id":"https://openalex.org/C128383755","wikidata":"https://www.wikidata.org/wiki/Q3816336","display_name":"Agricultural productivity","level":3,"score":0.2937999963760376},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.28209999203681946},{"id":"https://openalex.org/C149207113","wikidata":"https://www.wikidata.org/wiki/Q26534","display_name":"Water use","level":2,"score":0.257999986410141}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia251477","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia251477","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/faia251477","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia251477","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"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":{"Water":[0],"is":[1,13,88,144,224],"essential":[2],"for":[3,19,45,160,205],"agricultural":[4,21],"productivity.":[5],"Assessing":[6],"water":[7,93,105,118,130],"shortages":[8],"and":[9,23,51,60,107,114,153,180,208],"reduced":[10],"yield":[11,47,87,99,127,133,155,184],"potential":[12],"a":[14,101,139,169,187,212],"critical":[15],"factor":[16],"in":[17,182,210,216],"decision-making":[18],"ensuring":[20],"productivity":[22],"food":[24],"security.":[25],"Crop":[26],"simulation":[27],"models,":[28],"which":[29],"align":[30],"with":[31,186],"physical":[32,65,137],"processes,":[33],"offer":[34],"intrinsic":[35],"explainability":[36],"but":[37],"often":[38],"perform":[39],"poorly.":[40],"Conversely,":[41],"machine":[42],"learning":[43],"models":[44,177],"crop":[46,68,86,98,111,126,183],"modeling":[48,124],"are":[49],"powerful":[50],"scalable,":[52],"yet":[53],"they":[54],"commonly":[55],"operate":[56],"as":[57,100],"black":[58],"boxes":[59],"lack":[61],"adherence":[62],"to":[63,117,129,158,194],"the":[64,77,85,92,110,115,125,161,164],"principles":[66],"of":[67,79,103,189,192,218],"growth.":[69],"This":[70,200],"study":[71],"bridges":[72],"this":[73],"gap":[74],"by":[75,91],"coupling":[76],"advantages":[78],"both":[80,109],"worlds.":[81],"We":[82,146],"postulate":[83],"that":[84],"inherently":[89],"defined":[90],"availability.":[94],"Therefore,":[95],"we":[96,166],"formulate":[97],"function":[102,143],"temporal":[104],"scarcity":[106,119],"predict":[108],"drought":[112],"stress":[113],"sensitivity":[116],"at":[120,227],"fine-scale":[121,154],"resolution.":[122],"Sequentially":[123],"response":[128],"enables":[131],"accurate":[132],"prediction.":[134],"To":[135],"enforce":[136],"consistency,":[138],"novel":[140],"physics-informed":[141],"loss":[142],"proposed.":[145],"leverage":[147],"multispectral":[148],"satellite":[149],"imagery,":[150],"meteorological":[151],"data,":[152],"data.":[156],"Further,":[157],"account":[159],"uncertainty":[162],"within":[163],"model,":[165],"build":[167],"upon":[168],"deep":[170],"ensemble":[171],"approach.":[172],"Our":[173],"method":[174,201],"surpasses":[175],"state-of-the-art":[176],"like":[178],"LSTM":[179],"Transformers":[181],"prediction":[185],"coefficient":[188],"determination":[190],"(R2-score)":[191],"up":[193],"0.82":[195],"while":[196],"offering":[197],"high":[198],"explainability.":[199],"offers":[202],"decision":[203],"support":[204],"industry,":[206],"policymakers,":[207],"farmers":[209],"building":[211],"more":[213],"resilient":[214],"agriculture":[215],"times":[217],"changing":[219],"climate":[220],"conditions.":[221],"The":[222],"code":[223],"publicly":[225],"available":[226],"https://github.com/mmiranda-l/Yield-Loss.":[228]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-24T00:00:00"}
