{"id":"https://openalex.org/W4402218491","doi":"https://doi.org/10.1109/agro-geoinformatics262780.2024.10661011","title":"Estimation of leaf C/N in crops based on hyperspectral measurements and machine learning methods","display_name":"Estimation of leaf C/N in crops based on hyperspectral measurements and machine learning methods","publication_year":2024,"publication_date":"2024-07-15","ids":{"openalex":"https://openalex.org/W4402218491","doi":"https://doi.org/10.1109/agro-geoinformatics262780.2024.10661011"},"language":"en","primary_location":{"id":"doi:10.1109/agro-geoinformatics262780.2024.10661011","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/agro-geoinformatics262780.2024.10661011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 12th International Conference on Agro-Geoinformatics (Agro-Geoinformatics)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101459386","display_name":"Xingang Xu","orcid":"https://orcid.org/0000-0002-2692-5146"},"institutions":[{"id":"https://openalex.org/I4210156423","display_name":"National Engineering Research Center for Information Technology in Agriculture","ror":"https://ror.org/04c3j3t84","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210156423"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xingang Xu","raw_affiliation_strings":["Beijing Academy of Agriculture and Forestry Sciences,Information Technology Research Center,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing Academy of Agriculture and Forestry Sciences,Information Technology Research Center,Beijing,China","institution_ids":["https://openalex.org/I4210156423"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005698391","display_name":"Hao Yang","orcid":"https://orcid.org/0000-0001-8506-7295"},"institutions":[{"id":"https://openalex.org/I4210156423","display_name":"National Engineering Research Center for Information Technology in Agriculture","ror":"https://ror.org/04c3j3t84","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210156423"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Yang","raw_affiliation_strings":["Beijing Academy of Agriculture and Forestry Sciences,Information Technology Research Center,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing Academy of Agriculture and Forestry Sciences,Information Technology Research Center,Beijing,China","institution_ids":["https://openalex.org/I4210156423"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113255156","display_name":"Wenbiao Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210156423","display_name":"National Engineering Research Center for Information Technology in Agriculture","ror":"https://ror.org/04c3j3t84","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210156423"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbiao Wu","raw_affiliation_strings":["Beijing Academy of Agriculture and Forestry Sciences,Information Technology Research Center,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing Academy of Agriculture and Forestry Sciences,Information Technology Research Center,Beijing,China","institution_ids":["https://openalex.org/I4210156423"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020713851","display_name":"Guijun Yang","orcid":"https://orcid.org/0000-0002-6425-8321"},"institutions":[{"id":"https://openalex.org/I4210156423","display_name":"National Engineering Research Center for Information Technology in Agriculture","ror":"https://ror.org/04c3j3t84","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210156423"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guijun Yang","raw_affiliation_strings":["Beijing Academy of Agriculture and Forestry Sciences,Information Technology Research Center,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing Academy of Agriculture and Forestry Sciences,Information Technology Research Center,Beijing,China","institution_ids":["https://openalex.org/I4210156423"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000200794","display_name":"Xiaoyu Song","orcid":"https://orcid.org/0000-0003-0294-5705"},"institutions":[{"id":"https://openalex.org/I4210156423","display_name":"National Engineering Research Center for Information Technology in Agriculture","ror":"https://ror.org/04c3j3t84","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210156423"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyu Song","raw_affiliation_strings":["Beijing Academy of Agriculture and Forestry Sciences,Information Technology Research Center,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing Academy of Agriculture and Forestry Sciences,Information Technology Research Center,Beijing,China","institution_ids":["https://openalex.org/I4210156423"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041985951","display_name":"Xiaodong Yang","orcid":"https://orcid.org/0000-0002-3553-2125"},"institutions":[{"id":"https://openalex.org/I4210156423","display_name":"National Engineering Research Center for Information Technology in Agriculture","ror":"https://ror.org/04c3j3t84","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210156423"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodong Yang","raw_affiliation_strings":["Beijing Academy of Agriculture and Forestry Sciences,Information Technology Research Center,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing Academy of Agriculture and Forestry Sciences,Information Technology Research Center,Beijing,China","institution_ids":["https://openalex.org/I4210156423"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101620322","display_name":"Meng Yang","orcid":"https://orcid.org/0000-0002-2514-8015"},"institutions":[{"id":"https://openalex.org/I4210156423","display_name":"National Engineering Research Center for Information Technology in Agriculture","ror":"https://ror.org/04c3j3t84","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210156423"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Meng","raw_affiliation_strings":["Beijing Academy of Agriculture and Forestry Sciences,Information Technology Research Center,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing Academy of Agriculture and Forestry Sciences,Information Technology Research Center,Beijing,China","institution_ids":["https://openalex.org/I4210156423"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100599550","display_name":"Haikuan Feng","orcid":"https://orcid.org/0000-0003-3312-6200"},"institutions":[{"id":"https://openalex.org/I4210156423","display_name":"National Engineering Research Center for Information Technology in Agriculture","ror":"https://ror.org/04c3j3t84","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210156423"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haikuan Feng","raw_affiliation_strings":["Beijing Academy of Agriculture and Forestry Sciences,Information Technology Research Center,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing Academy of Agriculture and Forestry Sciences,Information Technology Research Center,Beijing,China","institution_ids":["https://openalex.org/I4210156423"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5101459386"],"corresponding_institution_ids":["https://openalex.org/I4210156423"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13582001,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"41","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9994999766349792,"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":0.9994999766349792,"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/T14365","display_name":"Leaf Properties and Growth Measurement","score":0.992900013923645,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9868000149726868,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.950387716293335},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5140668153762817},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.45500776171684265},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44982945919036865},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.39771682024002075},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39301392436027527},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33972322940826416},{"id":"https://openalex.org/keywords/agricultural-engineering","display_name":"Agricultural engineering","score":0.3332444429397583},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.18136045336723328},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1186622679233551}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.950387716293335},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5140668153762817},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45500776171684265},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44982945919036865},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.39771682024002075},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39301392436027527},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33972322940826416},{"id":"https://openalex.org/C88463610","wikidata":"https://www.wikidata.org/wiki/Q194118","display_name":"Agricultural engineering","level":1,"score":0.3332444429397583},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.18136045336723328},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1186622679233551},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/agro-geoinformatics262780.2024.10661011","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/agro-geoinformatics262780.2024.10661011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 12th International Conference on Agro-Geoinformatics (Agro-Geoinformatics)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","score":0.550000011920929,"display_name":"Zero hunger"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1480602009","https://openalex.org/W1963784463","https://openalex.org/W1969077079","https://openalex.org/W1973680308","https://openalex.org/W1974416151","https://openalex.org/W1988233512","https://openalex.org/W2019965926","https://openalex.org/W2084192167","https://openalex.org/W2084236720","https://openalex.org/W2087325533","https://openalex.org/W2095939249","https://openalex.org/W2109006150","https://openalex.org/W2111947859","https://openalex.org/W2118703810","https://openalex.org/W2128438912","https://openalex.org/W2137608957","https://openalex.org/W2159188796","https://openalex.org/W2163410149","https://openalex.org/W2371276046","https://openalex.org/W2382318143","https://openalex.org/W2906575954","https://openalex.org/W3135871359","https://openalex.org/W4250639944","https://openalex.org/W4387735795","https://openalex.org/W7046737012"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2070598848","https://openalex.org/W2385371209","https://openalex.org/W4250051149","https://openalex.org/W2083270190","https://openalex.org/W1991437568"],"abstract_inverted_index":{"Ratio":[0],"of":[1,13,31,46,52,71,112,117,157,195,211],"carbon":[2,16,32],"to":[3,18,58,93,123,182],"nitrogen":[4,21,76],"(C/N)":[5],"from":[6,107],"crop":[7,41,53],"leaves,":[8],"defined":[9],"as":[10,146],"the":[11,29,108,125,154,161,184,190,196,200],"ratio":[12],"LCC":[14],"(leaf":[15,20],"concentration)":[17],"LNC":[19],"concentration),":[22],"is":[23,45],"one":[24],"vital":[25],"index":[26],"for":[27,49,129,160,189],"evaluating":[28,130],"balance":[30],"and":[33,37,60,67,78,88,100,114,136,151,170,193,216],"nitrogen,":[34],"nutrient":[35],"status":[36,55],"growth":[38,54,110],"vigor":[39],"in":[40,56,98,119,134,214],"plants.":[42],"Therefore,":[43],"it":[44],"great":[47],"importance":[48],"efficient":[50],"assessment":[51],"field":[57],"monitor":[59],"estimate":[61,94],"leaf":[62,212],"$\\mathbf{C":[63,131,185],"/":[64,80,96,132,186],"N}$":[65,133,187],"quickly":[66],"accurately.":[68],"In":[69],"terms":[70],"close":[72],"relationships":[73],"between":[74],"chlorophyll,":[75],"(N)":[77],"$\\mathrm{C}":[79,95],"\\mathrm{N}$,":[81],"some":[82],"typical":[83],"indices":[84,128,144,181],"aimed":[85],"at":[86],"N":[87],"chlorophyll":[89],"estimation":[90],"were":[91,121,176],"tested":[92,143],"\\mathrm{N}$":[97],"radish":[99,118,135,215],"grape":[101,113,217],"leaves.":[102],"The":[103,138],"multi-temporal":[104],"hyperspectral":[105,220],"data":[106],"two":[109,142,162,191,197],"stages":[111,116],"four":[115],"2023":[120],"collected":[122],"extract":[124],"selected":[126],"spectral":[127,180],"grape.":[137],"results":[139,202],"showed":[140],"that":[141,209],"such":[145],"VI":[147],"$\\mathrm{I}_{\\text":[148],"{opt":[149],"}}$":[150],"RVI2":[152],"had":[153],"better":[155,201],"performance":[156],"estimating":[158],"C/N":[159,213],"crops.":[163],"Machine":[164],"Learning":[165],"(ML)":[166],"methods,":[167],"LASSO":[168],"regression":[169],"OWC":[171],"(Optimal":[172],"Weight":[173],"Combination)":[174],"algorithm":[175],"adopted":[177],"along":[178],"with":[179,203,223],"improve":[183],"estimates":[188],"crops,":[192],"both":[194],"methods":[198],"acquired":[199],"$R^{2}$":[204],"over":[205],"0.6.":[206],"It":[207],"indicates":[208],"monitoring":[210],"based":[218],"on":[219],"reflectance":[221],"measurements":[222],"ML":[224],"appears":[225],"very":[226],"potential.":[227]},"counts_by_year":[],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
