{"id":"https://openalex.org/W4400202860","doi":"https://doi.org/10.3390/rs16132417","title":"Predicting China\u2019s Maize Yield Using Multi-Source Datasets and Machine Learning Algorithms","display_name":"Predicting China\u2019s Maize Yield Using Multi-Source Datasets and Machine Learning Algorithms","publication_year":2024,"publication_date":"2024-07-01","ids":{"openalex":"https://openalex.org/W4400202860","doi":"https://doi.org/10.3390/rs16132417"},"language":"en","primary_location":{"id":"doi:10.3390/rs16132417","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16132417","pdf_url":"https://www.mdpi.com/2072-4292/16/13/2417/pdf?version=1719829971","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/2072-4292/16/13/2417/pdf?version=1719829971","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023914008","display_name":"Lijuan Miao","orcid":"https://orcid.org/0000-0002-0332-8488"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lijuan Miao","raw_affiliation_strings":["School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China"],"affiliations":[{"raw_affiliation_string":"School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042779084","display_name":"Yangfeng Zou","orcid":"https://orcid.org/0009-0008-2079-3104"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yangfeng Zou","raw_affiliation_strings":["School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China"],"affiliations":[{"raw_affiliation_string":"School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101906224","display_name":"Xuefeng Cui","orcid":"https://orcid.org/0000-0002-9617-072X"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuefeng Cui","raw_affiliation_strings":["School of Systems Science, Beijing Normal University, Beijing 100875, China"],"affiliations":[{"raw_affiliation_string":"School of Systems Science, Beijing Normal University, Beijing 100875, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050834753","display_name":"Giri Kattel","orcid":"https://orcid.org/0000-0002-8348-6477"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]},{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["AU","CN"],"is_corresponding":false,"raw_author_name":"Giri Raj Kattel","raw_affiliation_strings":["Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China","Department of Infrastructure Engineering, University of Melbourne, Melbourne, VIC 3010, Australia","School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China"],"affiliations":[{"raw_affiliation_string":"Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Infrastructure Engineering, University of Melbourne, Melbourne, VIC 3010, Australia","institution_ids":["https://openalex.org/I165779595"]},{"raw_affiliation_string":"School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101661391","display_name":"Yi Shang","orcid":"https://orcid.org/0000-0001-5866-7543"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Shang","raw_affiliation_strings":["School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China"],"affiliations":[{"raw_affiliation_string":"School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101617173","display_name":"Jingwen Zhu","orcid":"https://orcid.org/0000-0002-7954-6449"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingwen Zhu","raw_affiliation_strings":["Changwang School of Honors, Nanjing University of Information Science & Technology, Nanjing 210044, China"],"affiliations":[{"raw_affiliation_string":"Changwang School of Honors, Nanjing University of Information Science & Technology, Nanjing 210044, China","institution_ids":["https://openalex.org/I200845125"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5042779084"],"corresponding_institution_ids":["https://openalex.org/I200845125"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":4.1192,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.93224605,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"16","issue":"13","first_page":"2417","last_page":"2417"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9883999824523926,"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":0.9883999824523926,"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":0.9764999747276306,"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/T11229","display_name":"Genetics and Plant Breeding","score":0.9641000032424927,"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/random-forest","display_name":"Random forest","score":0.6716432571411133},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.6519672870635986},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6400498747825623},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.6338488459587097},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5631524920463562},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5178694725036621},{"id":"https://openalex.org/keywords/yield","display_name":"Yield (engineering)","score":0.5078783631324768},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4709506928920746},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45264768600463867},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.4454458951950073},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.433788925409317},{"id":"https://openalex.org/keywords/food-security","display_name":"Food security","score":0.4257127046585083},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3966135084629059},{"id":"https://openalex.org/keywords/agriculture","display_name":"Agriculture","score":0.2551618218421936},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.134145587682724},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.08935892581939697}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6716432571411133},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.6519672870635986},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6400498747825623},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.6338488459587097},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5631524920463562},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5178694725036621},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.5078783631324768},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4709506928920746},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45264768600463867},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.4454458951950073},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.433788925409317},{"id":"https://openalex.org/C549605437","wikidata":"https://www.wikidata.org/wiki/Q1229911","display_name":"Food security","level":3,"score":0.4257127046585083},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3966135084629059},{"id":"https://openalex.org/C118518473","wikidata":"https://www.wikidata.org/wiki/Q11451","display_name":"Agriculture","level":2,"score":0.2551618218421936},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.134145587682724},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.08935892581939697},{"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/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs16132417","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16132417","pdf_url":"https://www.mdpi.com/2072-4292/16/13/2417/pdf?version=1719829971","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:caa9c19e6b854683922cef065e6e9ca7","is_oa":true,"landing_page_url":"https://doaj.org/article/caa9c19e6b854683922cef065e6e9ca7","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 16, Iss 13, p 2417 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs16132417","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16132417","pdf_url":"https://www.mdpi.com/2072-4292/16/13/2417/pdf?version=1719829971","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","score":0.46000000834465027,"id":"https://metadata.un.org/sdg/2"},{"display_name":"Climate action","score":0.44999998807907104,"id":"https://metadata.un.org/sdg/13"}],"awards":[{"id":"https://openalex.org/G2090132896","display_name":null,"funder_award_id":"KYCX23_1294","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2122411691","display_name":null,"funder_award_id":"BK20210657","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4043414106","display_name":null,"funder_award_id":"KYCX23_1294","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G4645094948","display_name":null,"funder_award_id":"42101295","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G582179273","display_name":null,"funder_award_id":"1511582101011","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G7129451869","display_name":null,"funder_award_id":"BK20210657","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G7252311245","display_name":null,"funder_award_id":"1511582101011","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8222868322","display_name":null,"funder_award_id":"42101295","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4400202860.pdf"},"referenced_works_count":88,"referenced_works":["https://openalex.org/W612661449","https://openalex.org/W784579088","https://openalex.org/W1602667577","https://openalex.org/W1875061881","https://openalex.org/W1981552604","https://openalex.org/W1987190824","https://openalex.org/W1990275677","https://openalex.org/W1991949513","https://openalex.org/W1994753308","https://openalex.org/W1997902957","https://openalex.org/W2008056655","https://openalex.org/W2010633042","https://openalex.org/W2012796776","https://openalex.org/W2015037454","https://openalex.org/W2045256553","https://openalex.org/W2064675550","https://openalex.org/W2075844317","https://openalex.org/W2084325791","https://openalex.org/W2086970160","https://openalex.org/W2108079011","https://openalex.org/W2117162642","https://openalex.org/W2123583857","https://openalex.org/W2130019576","https://openalex.org/W2135046866","https://openalex.org/W2144499799","https://openalex.org/W2144559754","https://openalex.org/W2148333466","https://openalex.org/W2161815745","https://openalex.org/W2188581537","https://openalex.org/W2295598076","https://openalex.org/W2305485144","https://openalex.org/W2523192248","https://openalex.org/W2556344292","https://openalex.org/W2586821267","https://openalex.org/W2591121333","https://openalex.org/W2591944408","https://openalex.org/W2612890152","https://openalex.org/W2625548966","https://openalex.org/W2742109465","https://openalex.org/W2751549785","https://openalex.org/W2784327149","https://openalex.org/W2791592925","https://openalex.org/W2808964638","https://openalex.org/W2884280053","https://openalex.org/W2885693608","https://openalex.org/W2886775386","https://openalex.org/W2891765392","https://openalex.org/W2895348292","https://openalex.org/W2904659464","https://openalex.org/W2910729503","https://openalex.org/W2911964244","https://openalex.org/W2912587018","https://openalex.org/W2914693075","https://openalex.org/W2920549115","https://openalex.org/W2940718352","https://openalex.org/W2943472941","https://openalex.org/W2943654052","https://openalex.org/W2944794516","https://openalex.org/W2946483004","https://openalex.org/W2997068971","https://openalex.org/W3004377517","https://openalex.org/W3004408348","https://openalex.org/W3014134514","https://openalex.org/W3017487449","https://openalex.org/W3048689597","https://openalex.org/W3086171315","https://openalex.org/W3104887532","https://openalex.org/W3112881537","https://openalex.org/W3119853342","https://openalex.org/W3133001403","https://openalex.org/W3186111258","https://openalex.org/W3201452552","https://openalex.org/W3215039669","https://openalex.org/W3216762698","https://openalex.org/W4200127837","https://openalex.org/W4200331542","https://openalex.org/W4213044558","https://openalex.org/W4238077362","https://openalex.org/W4242361954","https://openalex.org/W4252208101","https://openalex.org/W4281632229","https://openalex.org/W4292640043","https://openalex.org/W4306362631","https://openalex.org/W4386884380","https://openalex.org/W6676379363","https://openalex.org/W6731388614","https://openalex.org/W6747913231","https://openalex.org/W6838628961"],"related_works":["https://openalex.org/W2967733078","https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W2885778889","https://openalex.org/W4310224730","https://openalex.org/W2766514146","https://openalex.org/W4386690025","https://openalex.org/W4289703016","https://openalex.org/W2885516856"],"abstract_inverted_index":{"A":[0],"timely":[1],"and":[2,10,40,57,62,80,127,179,208],"accurately":[3],"predicted":[4],"grain":[5],"yield":[6,37,101,138,215,229],"can":[7],"ensure":[8],"regional":[9],"global":[11],"food":[12],"security.":[13],"The":[14,90,153],"scientific":[15],"community":[16],"is":[17,43],"gradually":[18],"advancing":[19],"the":[20,27,34,96,105,111,118,132,159,165,171,176,180,203,219],"prediction":[21,139,160,230],"of":[22,29,92,99,161,205,231],"regional-scale":[23,35,213],"maize":[24,36,88,100,137,162,172,184,214],"yield.":[25,89],"However,":[26,175],"combination":[28],"various":[30],"datasets":[31,52,94,207],"while":[32,121,164],"predicting":[33,97],"using":[38],"simple":[39],"accurate":[41],"methods":[42,65,114,135],"still":[44],"relatively":[45],"rare.":[46],"Here,":[47],"we":[48,221],"have":[49,222],"used":[50],"multi-source":[51,206],"(climate":[53],"dataset,":[54,56],"satellite":[55,166],"soil":[58],"dataset),":[59],"lasso":[60,119],"algorithm,":[61,120],"machine":[63,112,130,209],"learning":[64,113,210],"(random":[66],"forest,":[67,123],"support":[68,128],"vector,":[69],"extreme":[70,124],"gradient":[71,125],"boosting,":[72,126],"BP":[73],"neural":[74],"network,":[75,79],"long":[76],"short-term":[77],"memory":[78],"K-nearest":[81],"neighbor":[82],"regression)":[83],"to":[84,104,117,158,169,201],"predict":[85],"China\u2019s":[86],"county-level":[87],"use":[91],"multi-sourced":[93],"advanced":[95],"accuracy":[98],"significantly":[102],"compared":[103],"single-sourced":[106],"dataset.":[107],"We":[108],"found":[109],"that":[110],"were":[115],"superior":[116],"random":[122],"vector":[129],"represented":[131],"most":[133],"preferable":[134],"for":[136,212,227],"in":[140],"China":[141],"(R2":[142],"\u2265":[143],"0.75,":[144],"RMSE":[145],"=":[146,150],"824\u2013875":[147],"kg/ha,":[148],"MAE":[149],"626\u2013651":[151],"kg/ha).":[152],"climate":[154],"dataset":[155,167],"contributed":[156,168],"more":[157],"yield,":[163],"tracking":[170],"growth":[173,185],"process.":[174],"methods\u2019":[177],"accuracies":[178],"dominant":[181],"variables":[182],"affecting":[183],"varied":[186],"with":[187],"agricultural":[188],"regions":[189],"across":[190],"different":[191,232],"geographic":[192],"locations.":[193],"Our":[194],"research":[195],"serves":[196],"as":[197],"an":[198],"important":[199],"effort":[200],"examine":[202],"feasibility":[204],"techniques":[211],"prediction.":[216],"In":[217],"addition,":[218],"methodology":[220],"proposed":[223],"here":[224],"provides":[225],"guidance":[226],"reliable":[228],"crops.":[233]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
