{"id":"https://openalex.org/W3016095210","doi":"https://doi.org/10.3390/rs12071206","title":"Hyperspectral Estimation of Soil Organic Matter Content using Different Spectral Preprocessing Techniques and PLSR Method","display_name":"Hyperspectral Estimation of Soil Organic Matter Content using Different Spectral Preprocessing Techniques and PLSR Method","publication_year":2020,"publication_date":"2020-04-08","ids":{"openalex":"https://openalex.org/W3016095210","doi":"https://doi.org/10.3390/rs12071206","mag":"3016095210"},"language":"en","primary_location":{"id":"doi:10.3390/rs12071206","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12071206","pdf_url":"https://www.mdpi.com/2072-4292/12/7/1206/pdf?version=1586597732","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/2072-4292/12/7/1206/pdf?version=1586597732","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043454542","display_name":"Lanzhi Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I32574673","display_name":"Shantou University","ror":"https://ror.org/01a099706","country_code":"CN","type":"education","lineage":["https://openalex.org/I32574673"]},{"id":"https://openalex.org/I4210108914","display_name":"Institute of Agricultural Resources and Regional Planning","ror":"https://ror.org/01nrzdp21","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210108914","https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]},{"id":"https://openalex.org/I4210138501","display_name":"Chinese Academy of Agricultural Sciences","ror":"https://ror.org/0313jb750","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lanzhi Shen","raw_affiliation_strings":["Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China","Key Laboratory of Digital Signal and Image Processing of Guangdong Province, Shantou University, Shantou 515063, China"],"affiliations":[{"raw_affiliation_string":"Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China","institution_ids":["https://openalex.org/I4210108914","https://openalex.org/I4210138501"]},{"raw_affiliation_string":"Key Laboratory of Digital Signal and Image Processing of Guangdong Province, Shantou University, Shantou 515063, China","institution_ids":["https://openalex.org/I32574673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042781660","display_name":"Maofang Gao","orcid":"https://orcid.org/0000-0002-9674-6020"},"institutions":[{"id":"https://openalex.org/I4210108914","display_name":"Institute of Agricultural Resources and Regional Planning","ror":"https://ror.org/01nrzdp21","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210108914","https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]},{"id":"https://openalex.org/I4210138501","display_name":"Chinese Academy of Agricultural Sciences","ror":"https://ror.org/0313jb750","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Maofang Gao","raw_affiliation_strings":["Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"],"affiliations":[{"raw_affiliation_string":"Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China","institution_ids":["https://openalex.org/I4210108914","https://openalex.org/I4210138501"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081305410","display_name":"Jingwen Yan","orcid":"https://orcid.org/0000-0002-6153-3519"},"institutions":[{"id":"https://openalex.org/I32574673","display_name":"Shantou University","ror":"https://ror.org/01a099706","country_code":"CN","type":"education","lineage":["https://openalex.org/I32574673"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingwen Yan","raw_affiliation_strings":["Key Laboratory of Digital Signal and Image Processing of Guangdong Province, Shantou University, Shantou 515063, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Digital Signal and Image Processing of Guangdong Province, Shantou University, Shantou 515063, China","institution_ids":["https://openalex.org/I32574673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058040417","display_name":"Zhao-Liang Li","orcid":"https://orcid.org/0000-0001-9369-8548"},"institutions":[{"id":"https://openalex.org/I4210108914","display_name":"Institute of Agricultural Resources and Regional Planning","ror":"https://ror.org/01nrzdp21","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210108914","https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]},{"id":"https://openalex.org/I4210138501","display_name":"Chinese Academy of Agricultural Sciences","ror":"https://ror.org/0313jb750","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhao-Liang Li","raw_affiliation_strings":["Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"],"affiliations":[{"raw_affiliation_string":"Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China","institution_ids":["https://openalex.org/I4210108914","https://openalex.org/I4210138501"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112149554","display_name":"Pei Leng","orcid":"https://orcid.org/0000-0002-9130-5437"},"institutions":[{"id":"https://openalex.org/I4210108914","display_name":"Institute of Agricultural Resources and Regional Planning","ror":"https://ror.org/01nrzdp21","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210108914","https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]},{"id":"https://openalex.org/I4210138501","display_name":"Chinese Academy of Agricultural Sciences","ror":"https://ror.org/0313jb750","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pei Leng","raw_affiliation_strings":["Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"],"affiliations":[{"raw_affiliation_string":"Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China","institution_ids":["https://openalex.org/I4210108914","https://openalex.org/I4210138501"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100636286","display_name":"Qiang Yang","orcid":"https://orcid.org/0000-0001-5059-8360"},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Yang","raw_affiliation_strings":["College of Engineering, Nanjing Forestry University, Nanjing 210037, China"],"affiliations":[{"raw_affiliation_string":"College of Engineering, Nanjing Forestry University, Nanjing 210037, China","institution_ids":["https://openalex.org/I167027274"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055755007","display_name":"Si\u2010Bo Duan","orcid":"https://orcid.org/0000-0002-4390-2421"},"institutions":[{"id":"https://openalex.org/I4210108914","display_name":"Institute of Agricultural Resources and Regional Planning","ror":"https://ror.org/01nrzdp21","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210108914","https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]},{"id":"https://openalex.org/I4210138501","display_name":"Chinese Academy of Agricultural Sciences","ror":"https://ror.org/0313jb750","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Si-Bo Duan","raw_affiliation_strings":["Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"],"affiliations":[{"raw_affiliation_string":"Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China","institution_ids":["https://openalex.org/I4210108914","https://openalex.org/I4210138501"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5042781660"],"corresponding_institution_ids":["https://openalex.org/I4210108914","https://openalex.org/I4210138501"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":5.1551,"has_fulltext":true,"cited_by_count":132,"citation_normalized_percentile":{"value":0.96228448,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"12","issue":"7","first_page":"1206","last_page":"1206"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10770","display_name":"Soil Geostatistics and Mapping","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10770","display_name":"Soil Geostatistics and Mapping","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9965000152587891,"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"}},{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7938154935836792},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5962405204772949},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5525587797164917},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5461001992225647},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5190813541412354},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4626193344593048},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4478519558906555},{"id":"https://openalex.org/keywords/partial-least-squares-regression","display_name":"Partial least squares regression","score":0.43409743905067444},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.417110800743103},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3623526692390442},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3250362277030945},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18162637948989868}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7938154935836792},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5962405204772949},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5525587797164917},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5461001992225647},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5190813541412354},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4626193344593048},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4478519558906555},{"id":"https://openalex.org/C22354355","wikidata":"https://www.wikidata.org/wiki/Q422009","display_name":"Partial least squares regression","level":2,"score":0.43409743905067444},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.417110800743103},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3623526692390442},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3250362277030945},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18162637948989868},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs12071206","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12071206","pdf_url":"https://www.mdpi.com/2072-4292/12/7/1206/pdf?version=1586597732","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:c97f37fa506f4e10bb7a687fbb01b568","is_oa":true,"landing_page_url":"https://doaj.org/article/c97f37fa506f4e10bb7a687fbb01b568","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-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 7, p 1206 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/12/7/1206/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs12071206","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 7; Pages: 1206","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs12071206","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12071206","pdf_url":"https://www.mdpi.com/2072-4292/12/7/1206/pdf?version=1586597732","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":0.6600000262260437,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2514888371","display_name":null,"funder_award_id":"41921001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3975256927","display_name":null,"funder_award_id":"41921001, 41871282","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5848258319","display_name":null,"funder_award_id":"0 and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7163760694","display_name":null,"funder_award_id":"41871282","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8208342437","display_name":null,"funder_award_id":"1 and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322174","display_name":"People's Government of Jilin Province","ror":"https://ror.org/02fzqav45"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3016095210.pdf","grobid_xml":"https://content.openalex.org/works/W3016095210.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W1977886272","https://openalex.org/W1990167351","https://openalex.org/W1990547462","https://openalex.org/W1998053851","https://openalex.org/W1998171787","https://openalex.org/W2007440415","https://openalex.org/W2010212234","https://openalex.org/W2016090370","https://openalex.org/W2023586251","https://openalex.org/W2032077688","https://openalex.org/W2035121399","https://openalex.org/W2038599307","https://openalex.org/W2052903566","https://openalex.org/W2057474369","https://openalex.org/W2057687252","https://openalex.org/W2067558695","https://openalex.org/W2068670606","https://openalex.org/W2070467687","https://openalex.org/W2083041300","https://openalex.org/W2109606373","https://openalex.org/W2165993842","https://openalex.org/W2196579671","https://openalex.org/W2200752703","https://openalex.org/W2294798173","https://openalex.org/W2347217942","https://openalex.org/W2360323265","https://openalex.org/W2586813976","https://openalex.org/W2594581855","https://openalex.org/W2755091472","https://openalex.org/W2766359225","https://openalex.org/W2769747912","https://openalex.org/W2780625821","https://openalex.org/W2883891091","https://openalex.org/W2893188571","https://openalex.org/W2904796016","https://openalex.org/W2917539806","https://openalex.org/W2920332010","https://openalex.org/W2944731604","https://openalex.org/W3146257408","https://openalex.org/W6647766378","https://openalex.org/W6687584342"],"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/W2404757046","https://openalex.org/W2292979300","https://openalex.org/W1881188068","https://openalex.org/W3115502235","https://openalex.org/W3129124584"],"abstract_inverted_index":{"Soil":[0],"organic":[1],"matter":[2],"(SOM)":[3],"is":[4,25,53],"the":[5,15,28,34,46,171,180,192,201,204,213,219,222,229,237,240,253,259,262,285,292,295],"main":[6,175],"source":[7],"of":[8,19,27,32,60,83,133,239,252,264,284,294],"soil":[9,62,75],"nutrients,":[10],"which":[11],"are":[12],"essential":[13],"for":[14,169,270],"growth":[16],"and":[17,40,90,106,130,151,185,225,233,291,313],"development":[18],"agricultural":[20],"crops.":[21],"Hyperspectral":[22],"remote":[23],"sensing":[24],"one":[26],"most":[29],"efficient":[30],"ways":[31],"estimating":[33],"SOM":[35,172,193,241,296],"content.":[36,173,194],"Visible,":[37],"near":[38],"infrared,":[39],"mid-infrared":[41],"reflectance":[42],"spectroscopy,":[43],"combined":[44],"with":[45,191,221],"partial":[47],"least":[48],"squares":[49],"regression":[50],"(PLSR)":[51],"method":[52,232],"considered":[54],"to":[55,73,165],"be":[56,289,301],"an":[57],"effective":[58,276],"way":[59],"determining":[61],"properties.":[63],"In":[64],"this":[65,316],"study,":[66],"we":[67],"used":[68],"54":[69,214],"different":[70],"spectral":[71,76,79,117,234,286],"pretreatments":[72,80,215],"preprocess":[74],"data.":[77],"These":[78],"were":[81,162,177],"composed":[82],"three":[84,91,96,137],"denoising":[85,97,101,104,109,183,231],"methods,":[86],"six":[87,112],"data":[88,113,187,279,287],"transformations,":[89],"dimensionality":[92,138,143,148,156],"reduction":[93,139,144,149,157,274],"methods.":[94],"The":[95,111,136,159,174,282],"methods":[98,140,197,309],"included":[99,115,141],"no":[100,142],"(ND),":[102],"Savitzky\u2013Golay":[103],"(SGD),":[105],"wavelet":[107,181],"packet":[108,182],"(WPD).":[110],"transformations":[114],"original":[116],"data,":[118,236],"R;":[119],"reciprocal,":[120,134],"1/R;":[121],"logarithmic,":[122,125],"log(R);":[123],"reciprocal":[124],"log(1/R);":[126],"first":[127,131],"derivative,":[128],"R\u2019;":[129],"derivative":[132],"(1/R)\u2019.":[135],"(NDR),":[145],"sensitive":[146],"waveband":[147],"(SWDR),":[150],"principal":[152],"component":[153],"analysis":[154],"(PCA)":[155],"(PCADR).":[158],"processed":[160],"spectra":[161],"then":[163],"employed":[164],"construct":[166],"PLSR":[167],"models":[168],"predicting":[170],"results":[176],"as":[178],"follows\u2014(1)":[179],"(WPD)-R\u2019":[184],"WPD-(1/R)\u2019":[186],"showed":[188],"stronger":[189],"correlations":[190],"Furthermore,":[195,258],"these":[196],"could":[198,288,300],"effectively":[199],"limit":[200],"correlation":[202],"between":[203],"adjacent":[205],"bands":[206],"and,":[207],"thus,":[208],"prevent":[209],"\u201coverfitting\u201d.":[210],"(2)":[211],"Of":[212],"investigated,":[216],"WPD-(1/R)\u2019-PCADR":[217],"yielded":[218],"model":[220,244,254,299],"highest":[223],"accuracy":[224,238,260,293],"stability.":[226],"(3)":[227],"For":[228],"same":[230],"transformation":[235],"content":[242,297],"estimation":[243,298],"based":[245,255],"on":[246,256],"SWDR":[247],"was":[248,266,275],"higher":[249,267],"than":[250,268],"that":[251,269],"NDR.":[257],"in":[261,277,315],"case":[263],"PCADR":[265,314],"SWDR.":[271],"(4)":[272],"Dimensionality":[273],"preventing":[278],"overfitting.":[280],"(5)":[281],"quality":[283],"improved":[290],"enhanced":[302],"effectively,":[303],"by":[304],"using":[305],"some":[306],"appropriate":[307],"preprocessing":[308],"(one":[310],"combining":[311],"WPD":[312],"study).":[317]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":31},{"year":2024,"cited_by_count":38},{"year":2023,"cited_by_count":24},{"year":2022,"cited_by_count":16},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":4}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2020-04-17T00:00:00"}
