{"id":"https://openalex.org/W3042701400","doi":"https://doi.org/10.3390/rs12142230","title":"Using Artificial Neural Networks and Remotely Sensed Data to Evaluate the Relative Importance of Variables for Prediction of Within-Field Corn and Soybean Yields","display_name":"Using Artificial Neural Networks and Remotely Sensed Data to Evaluate the Relative Importance of Variables for Prediction of Within-Field Corn and Soybean Yields","publication_year":2020,"publication_date":"2020-07-11","ids":{"openalex":"https://openalex.org/W3042701400","doi":"https://doi.org/10.3390/rs12142230","mag":"3042701400"},"language":"en","primary_location":{"id":"doi:10.3390/rs12142230","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12142230","pdf_url":"https://www.mdpi.com/2072-4292/12/14/2230/pdf?version=1594778788","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/2072-4292/12/14/2230/pdf?version=1594778788","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088397180","display_name":"Angela Kross","orcid":"https://orcid.org/0000-0003-4646-951X"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Angela Kross","raw_affiliation_strings":["Department of Geography, Planning and Environment, Concordia University, Montreal, QC H3G 1M8, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geography, Planning and Environment, Concordia University, Montreal, QC H3G 1M8, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053028332","display_name":"Evelyn Znoj","orcid":null},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Evelyn Znoj","raw_affiliation_strings":["Department of Geography, Planning and Environment, Concordia University, Montreal, QC H3G 1M8, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geography, Planning and Environment, Concordia University, Montreal, QC H3G 1M8, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030374004","display_name":"Daihany Moraes Callegari","orcid":"https://orcid.org/0000-0001-5545-2678"},"institutions":[{"id":"https://openalex.org/I3130823459","display_name":"Universidade Federal Rural da Amaz\u00f4nia","ror":"https://ror.org/02j71c790","country_code":"BR","type":"education","lineage":["https://openalex.org/I3130823459"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Daihany Callegari","raw_affiliation_strings":["Department of Agronomy, Federal Rural University of Amazon, Paragominas, PA 68627-451, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Agronomy, Federal Rural University of Amazon, Paragominas, PA 68627-451, Brazil","institution_ids":["https://openalex.org/I3130823459"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027571327","display_name":"Gurpreet Kaur","orcid":"https://orcid.org/0000-0002-2611-5143"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Gurpreet Kaur","raw_affiliation_strings":["Department of Geography, Planning and Environment, Concordia University, Montreal, QC H3G 1M8, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geography, Planning and Environment, Concordia University, Montreal, QC H3G 1M8, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109000785","display_name":"Mark Sunohara","orcid":null},"institutions":[{"id":"https://openalex.org/I1331897569","display_name":"Agriculture and Agri-Food Canada","ror":"https://ror.org/051dzs374","country_code":"CA","type":"government","lineage":["https://openalex.org/I1331897569","https://openalex.org/I2802286613"]},{"id":"https://openalex.org/I4390039273","display_name":"Ottawa Research and Development Centre","ror":"https://ror.org/03fx3ra47","country_code":null,"type":"facility","lineage":["https://openalex.org/I1331897569","https://openalex.org/I2802286613","https://openalex.org/I4390039273"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mark Sunohara","raw_affiliation_strings":["Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada","institution_ids":["https://openalex.org/I1331897569","https://openalex.org/I4390039273"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110547802","display_name":"David R. Lapen","orcid":null},"institutions":[{"id":"https://openalex.org/I1331897569","display_name":"Agriculture and Agri-Food Canada","ror":"https://ror.org/051dzs374","country_code":"CA","type":"government","lineage":["https://openalex.org/I1331897569","https://openalex.org/I2802286613"]},{"id":"https://openalex.org/I4390039273","display_name":"Ottawa Research and Development Centre","ror":"https://ror.org/03fx3ra47","country_code":null,"type":"facility","lineage":["https://openalex.org/I1331897569","https://openalex.org/I2802286613","https://openalex.org/I4390039273"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"David R. Lapen","raw_affiliation_strings":["Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada","institution_ids":["https://openalex.org/I1331897569","https://openalex.org/I4390039273"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040448854","display_name":"Heather McNairn","orcid":"https://orcid.org/0000-0003-1006-0018"},"institutions":[{"id":"https://openalex.org/I1331897569","display_name":"Agriculture and Agri-Food Canada","ror":"https://ror.org/051dzs374","country_code":"CA","type":"government","lineage":["https://openalex.org/I1331897569","https://openalex.org/I2802286613"]},{"id":"https://openalex.org/I4390039273","display_name":"Ottawa Research and Development Centre","ror":"https://ror.org/03fx3ra47","country_code":null,"type":"facility","lineage":["https://openalex.org/I1331897569","https://openalex.org/I2802286613","https://openalex.org/I4390039273"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Heather McNairn","raw_affiliation_strings":["Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada"],"raw_orcid":"https://orcid.org/0000-0003-1006-0018","affiliations":[{"raw_affiliation_string":"Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada","institution_ids":["https://openalex.org/I1331897569","https://openalex.org/I4390039273"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5088397180"],"corresponding_institution_ids":["https://openalex.org/I60158472"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":4.8234,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.95411015,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"12","issue":"14","first_page":"2230","last_page":"2230"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9987000226974487,"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"}},"topics":[{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9987000226974487,"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/T10226","display_name":"Land Use and Ecosystem Services","score":0.9818999767303467,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T10770","display_name":"Soil Geostatistics and Mapping","score":0.9745000004768372,"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":0.6869168877601624},{"id":"https://openalex.org/keywords/crop","display_name":"Crop","score":0.5575634837150574},{"id":"https://openalex.org/keywords/yield","display_name":"Yield (engineering)","score":0.5466660857200623},{"id":"https://openalex.org/keywords/growing-season","display_name":"Growing season","score":0.5189154148101807},{"id":"https://openalex.org/keywords/crop-yield","display_name":"Crop yield","score":0.5182130932807922},{"id":"https://openalex.org/keywords/vegetation","display_name":"Vegetation (pathology)","score":0.4571296274662018},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.43243739008903503},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42912235856056213},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.41521790623664856},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3664659559726715},{"id":"https://openalex.org/keywords/agricultural-engineering","display_name":"Agricultural engineering","score":0.33853209018707275},{"id":"https://openalex.org/keywords/agronomy","display_name":"Agronomy","score":0.2944907248020172},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.18914344906806946},{"id":"https://openalex.org/keywords/leaf-area-index","display_name":"Leaf area index","score":0.16513487696647644},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.15936389565467834},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.07055005431175232}],"concepts":[{"id":"https://openalex.org/C1549246","wikidata":"https://www.wikidata.org/wiki/Q718775","display_name":"Normalized Difference Vegetation Index","level":3,"score":0.6869168877601624},{"id":"https://openalex.org/C137580998","wikidata":"https://www.wikidata.org/wiki/Q235352","display_name":"Crop","level":2,"score":0.5575634837150574},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.5466660857200623},{"id":"https://openalex.org/C137660486","wikidata":"https://www.wikidata.org/wiki/Q732240","display_name":"Growing season","level":2,"score":0.5189154148101807},{"id":"https://openalex.org/C126343540","wikidata":"https://www.wikidata.org/wiki/Q889514","display_name":"Crop yield","level":2,"score":0.5182130932807922},{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.4571296274662018},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.43243739008903503},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42912235856056213},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.41521790623664856},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3664659559726715},{"id":"https://openalex.org/C88463610","wikidata":"https://www.wikidata.org/wiki/Q194118","display_name":"Agricultural engineering","level":1,"score":0.33853209018707275},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.2944907248020172},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.18914344906806946},{"id":"https://openalex.org/C25989453","wikidata":"https://www.wikidata.org/wiki/Q446746","display_name":"Leaf area index","level":2,"score":0.16513487696647644},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.15936389565467834},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.07055005431175232},{"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/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0},{"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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs12142230","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12142230","pdf_url":"https://www.mdpi.com/2072-4292/12/14/2230/pdf?version=1594778788","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:73ff1fdc164e4a0295907a2c13c4ba87","is_oa":true,"landing_page_url":"https://doaj.org/article/73ff1fdc164e4a0295907a2c13c4ba87","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":"Remote Sensing, Vol 12, Iss 14, p 2230 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/12/14/2230/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs12142230","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 12; Issue 14; Pages: 2230","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs12142230","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12142230","pdf_url":"https://www.mdpi.com/2072-4292/12/14/2230/pdf?version=1594778788","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":[{"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.4099999964237213}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334595","display_name":"Agriculture and Agri-Food Canada","ror":"https://ror.org/051dzs374"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W633320881","https://openalex.org/W1833005471","https://openalex.org/W2042966177","https://openalex.org/W2043230890","https://openalex.org/W2043791654","https://openalex.org/W2050009461","https://openalex.org/W2080010866","https://openalex.org/W2081539341","https://openalex.org/W2116905012","https://openalex.org/W2143933571","https://openalex.org/W2202019762","https://openalex.org/W2246132822","https://openalex.org/W2308333096","https://openalex.org/W2418118740","https://openalex.org/W2502187592","https://openalex.org/W2564103795","https://openalex.org/W2567262610","https://openalex.org/W2805142011","https://openalex.org/W2905983018","https://openalex.org/W2921277556","https://openalex.org/W2946413603","https://openalex.org/W2953686964","https://openalex.org/W2955928210","https://openalex.org/W2983376237","https://openalex.org/W2995678734","https://openalex.org/W6638646117","https://openalex.org/W6730922110"],"related_works":["https://openalex.org/W2360471910","https://openalex.org/W2996115036","https://openalex.org/W3080397319","https://openalex.org/W3096013024","https://openalex.org/W2415170322","https://openalex.org/W2161881124","https://openalex.org/W2969072466","https://openalex.org/W2391543016","https://openalex.org/W2046550984","https://openalex.org/W2088267788"],"abstract_inverted_index":{"Crop":[0],"yield":[1,22,72,97,132,267,284],"prediction":[2,65],"prior":[3],"to":[4,55,75,92,191,209],"harvest":[5],"is":[6,23],"important":[7,158,178],"for":[8,15,63,89,161,184,206,237],"crop":[9,21,33,131,142,163,187,194],"income":[10],"and":[11,14,35,69,73,95,117,120,143,152,168,189,264],"insurance":[12],"projections,":[13],"evaluating":[16],"food":[17],"security.":[18],"Yet,":[19],"modeling":[20],"challenging":[24],"because":[25],"of":[26,29,60,66,79,175,212,223,242,253],"the":[27,30,40,57,64,77,80,102,137,149,153,156,176,185,213,224,243,254,270],"complexity":[28],"relationships":[31],"between":[32],"growth":[34],"predictor":[36,61,133,159],"variables,":[37,134],"especially":[38],"at":[39,101,269],"field":[41],"scale.":[42],"In":[43,239],"this":[44],"study,":[45],"an":[46],"artificial":[47],"neural":[48],"network":[49],"(ANN)":[50],"method":[51],"was":[52],"used:":[53],"(1)":[54],"evaluate":[56,76],"relative":[58,199],"importance":[59],"variables":[62,123,139,160],"within-field":[67,103],"corn":[68,94,207,215],"soybean":[70,96],"end-of-season":[71],"(2)":[74],"performance":[78],"ANN":[81],"models":[82],"with":[83],"a":[84],"minimal":[85],"optimized":[86],"variable":[87,236],"dataset":[88],"their":[90,192],"capacity":[91],"predict":[93],"over":[98],"multiple":[99],"years":[100,170],"level.":[104],"Several":[105],"satellite":[106],"derived":[107,122],"vegetation":[108,112],"indices":[109],"(normalized":[110],"difference":[111],"index\u2014NDVI,":[113],"red":[114],"edge":[115],"NDVI":[116],"simple":[118],"ratio\u2014SR)":[119],"elevation":[121],"(slope,":[124],"flow":[125],"accumulation,":[126],"aspect)":[127],"were":[128,182,203,234],"used":[129],"as":[130,155],"hypothesizing":[135],"that":[136],"different":[138,141,183],"reflect":[140],"site":[144],"conditions.":[145],"The":[146,173,198,232,260],"study":[147,216],"identified":[148],"SR":[150,179],"index":[151],"slope":[154],"most":[157,177],"both":[162],"types":[164,188],"during":[165],"two":[166,186],"training":[167],"testing":[169],"(2011,":[171],"2012).":[172],"dates":[174],"images,":[180],"however,":[181],"corresponded":[190],"critical":[193],"developmental":[195],"stages":[196],"(phenology).":[197],"mean":[200],"absolute":[201],"errors":[202,219,227,233,246,257],"overall":[204],"smaller":[205],"compared":[208],"soybean:":[210],"all":[211],"2011":[214],"fields":[217,225,244,255],"had":[218,226,245,256],"below":[220,228,247,258],"10%;":[221],"75%":[222],"10%":[229],"in":[230,250,277],"2012.":[231],"more":[235],"soybean.":[238],"2011,":[240],"37%":[241],"10%,":[248],"while":[249],"2012,":[251],"100%":[252],"20%.":[259],"results":[261],"are":[262],"promising":[263],"can":[265],"provide":[266],"estimates":[268],"farm":[271],"level,":[272],"which":[273],"could":[274],"be":[275],"useful":[276],"refining":[278],"broader":[279],"scale":[280],"(e.g.,":[281],"county,":[282],"region)":[283],"projections.":[285]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":7}],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-10-10T00:00:00"}