{"id":"https://openalex.org/W1904978179","doi":"https://doi.org/10.1109/icawst.2015.7314049","title":"Prediction of dry matter, protein, and acidity in corn steep liquor using near infrared spectroscopy","display_name":"Prediction of dry matter, protein, and acidity in corn steep liquor using near infrared spectroscopy","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W1904978179","doi":"https://doi.org/10.1109/icawst.2015.7314049","mag":"1904978179"},"language":"en","primary_location":{"id":"doi:10.1109/icawst.2015.7314049","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icawst.2015.7314049","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 7th International Conference on Awareness Science and Technology (iCAST)","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/A5057468200","display_name":"Zhonghai He","orcid":"https://orcid.org/0000-0001-8080-5383"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhonghai He","raw_affiliation_strings":["College of information science and engineering Northeastern university Shenyang, China","[College of Information Science & Engineering, Northeastern University, Shenyang, CHINA]"],"affiliations":[{"raw_affiliation_string":"College of information science and engineering Northeastern university Shenyang, China","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"[College of Information Science & Engineering, Northeastern University, Shenyang, CHINA]","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043652487","display_name":"Mengchao Li","orcid":"https://orcid.org/0009-0004-8707-3006"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengchao Li","raw_affiliation_strings":["College of information science and engineering Northeastern university Shenyang, China","[College of Information Science & Engineering, Northeastern University, Shenyang, CHINA]"],"affiliations":[{"raw_affiliation_string":"College of information science and engineering Northeastern university Shenyang, China","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"[College of Information Science & Engineering, Northeastern University, Shenyang, CHINA]","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066097867","display_name":"Zhenhe Ma","orcid":"https://orcid.org/0000-0003-4079-9550"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenhe Ma","raw_affiliation_strings":["College of information science and engineering Northeastern university Shenyang, China","[College of Information Science & Engineering, Northeastern University, Shenyang, CHINA]"],"affiliations":[{"raw_affiliation_string":"College of information science and engineering Northeastern university Shenyang, China","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"[College of Information Science & Engineering, Northeastern University, Shenyang, CHINA]","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5057468200"],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.03552014,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"212","last_page":"215"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9998999834060669,"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/T11324","display_name":"Spectroscopy Techniques in Biomedical and Chemical Research","score":0.9825999736785889,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10333","display_name":"Meat and Animal Product Quality","score":0.9783999919891357,"subfield":{"id":"https://openalex.org/subfields/1103","display_name":"Animal Science and Zoology"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/dry-matter","display_name":"Dry matter","score":0.7330744862556458},{"id":"https://openalex.org/keywords/partial-least-squares-regression","display_name":"Partial least squares regression","score":0.6428623795509338},{"id":"https://openalex.org/keywords/corn-steep-liquor","display_name":"Corn steep liquor","score":0.6036808490753174},{"id":"https://openalex.org/keywords/standard-error","display_name":"Standard error","score":0.598770022392273},{"id":"https://openalex.org/keywords/near-infrared-spectroscopy","display_name":"Near-infrared spectroscopy","score":0.584347128868103},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.5701733231544495},{"id":"https://openalex.org/keywords/coefficient-of-determination","display_name":"Coefficient of determination","score":0.5278116464614868},{"id":"https://openalex.org/keywords/analytical-chemistry","display_name":"Analytical Chemistry (journal)","score":0.5215327739715576},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.4878513813018799},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.4783291816711426},{"id":"https://openalex.org/keywords/spectroscopy","display_name":"Spectroscopy","score":0.4660220146179199},{"id":"https://openalex.org/keywords/cross-validation","display_name":"Cross-validation","score":0.45616278052330017},{"id":"https://openalex.org/keywords/standard-deviation","display_name":"Standard deviation","score":0.4488610327243805},{"id":"https://openalex.org/keywords/infrared-spectroscopy","display_name":"Infrared spectroscopy","score":0.44260096549987793},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.422030508518219},{"id":"https://openalex.org/keywords/derivative","display_name":"Derivative (finance)","score":0.4209819436073303},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.418012797832489},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3913348317146301},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.29279768466949463},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22218385338783264},{"id":"https://openalex.org/keywords/botany","display_name":"Botany","score":0.17386850714683533},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.13112637400627136},{"id":"https://openalex.org/keywords/fermentation","display_name":"Fermentation","score":0.10164082050323486},{"id":"https://openalex.org/keywords/food-science","display_name":"Food science","score":0.09662973880767822},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.07650372385978699}],"concepts":[{"id":"https://openalex.org/C2780138947","wikidata":"https://www.wikidata.org/wiki/Q393855","display_name":"Dry matter","level":2,"score":0.7330744862556458},{"id":"https://openalex.org/C22354355","wikidata":"https://www.wikidata.org/wiki/Q422009","display_name":"Partial least squares regression","level":2,"score":0.6428623795509338},{"id":"https://openalex.org/C2779078344","wikidata":"https://www.wikidata.org/wiki/Q5171066","display_name":"Corn steep liquor","level":3,"score":0.6036808490753174},{"id":"https://openalex.org/C18747219","wikidata":"https://www.wikidata.org/wiki/Q620994","display_name":"Standard error","level":2,"score":0.598770022392273},{"id":"https://openalex.org/C43571822","wikidata":"https://www.wikidata.org/wiki/Q599037","display_name":"Near-infrared spectroscopy","level":2,"score":0.584347128868103},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.5701733231544495},{"id":"https://openalex.org/C128990827","wikidata":"https://www.wikidata.org/wiki/Q192830","display_name":"Coefficient of determination","level":2,"score":0.5278116464614868},{"id":"https://openalex.org/C113196181","wikidata":"https://www.wikidata.org/wiki/Q485223","display_name":"Analytical Chemistry (journal)","level":2,"score":0.5215327739715576},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4878513813018799},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.4783291816711426},{"id":"https://openalex.org/C32891209","wikidata":"https://www.wikidata.org/wiki/Q483666","display_name":"Spectroscopy","level":2,"score":0.4660220146179199},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.45616278052330017},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.4488610327243805},{"id":"https://openalex.org/C153642686","wikidata":"https://www.wikidata.org/wiki/Q70906","display_name":"Infrared spectroscopy","level":2,"score":0.44260096549987793},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.422030508518219},{"id":"https://openalex.org/C111771559","wikidata":"https://www.wikidata.org/wiki/Q66295","display_name":"Derivative (finance)","level":2,"score":0.4209819436073303},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.418012797832489},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3913348317146301},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.29279768466949463},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22218385338783264},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.17386850714683533},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.13112637400627136},{"id":"https://openalex.org/C100544194","wikidata":"https://www.wikidata.org/wiki/Q41760","display_name":"Fermentation","level":2,"score":0.10164082050323486},{"id":"https://openalex.org/C31903555","wikidata":"https://www.wikidata.org/wiki/Q1637030","display_name":"Food science","level":1,"score":0.09662973880767822},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.07650372385978699},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icawst.2015.7314049","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icawst.2015.7314049","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 7th International Conference on Awareness Science and Technology (iCAST)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.44999998807907104,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W158447550","https://openalex.org/W1977442857","https://openalex.org/W2003008699","https://openalex.org/W2003425251","https://openalex.org/W2004236650","https://openalex.org/W2033565429","https://openalex.org/W2039360113","https://openalex.org/W2041573151","https://openalex.org/W2043336734","https://openalex.org/W2050273443","https://openalex.org/W2051098649","https://openalex.org/W2061485898","https://openalex.org/W2063877835","https://openalex.org/W2076357383","https://openalex.org/W2085191402","https://openalex.org/W2109606373","https://openalex.org/W2143391632","https://openalex.org/W2150823344","https://openalex.org/W2154823440"],"related_works":["https://openalex.org/W2005343960","https://openalex.org/W2389676600","https://openalex.org/W3038549854","https://openalex.org/W2356611498","https://openalex.org/W2313233562","https://openalex.org/W1994467437","https://openalex.org/W2036068629","https://openalex.org/W3190418201","https://openalex.org/W2606632967","https://openalex.org/W2762592329"],"abstract_inverted_index":{"The":[0,19,42,61,72,130],"near":[1,134],"infrared":[2,135],"spectroscopy":[3,136],"methods":[4],"for":[5,29,113,120,127,141],"determining":[6],"the":[7,51,69,83,92,104],"dry":[8,114,143],"matter,":[9,115],"protein,":[10,121],"and":[11,25,36,50,91,111,118,122,125,145,152],"acidity":[12],"in":[13,55,68],"corn":[14,148],"steep":[15,149],"liquid":[16,150],"were":[17,21,66,108],"investigated.":[18],"samples":[20],"divided":[22],"into":[23],"calibration":[24],"validation":[26,77],"subsets":[27],"randomly":[28],"multivariate":[30],"modeling.":[31],"Outlier":[32],"was":[33,45],"eliminated":[34],"carefully":[35],"cross":[37],"validated":[38,139],"by":[39,47],"different":[40,48],"method.":[41],"preprocessing":[43],"method":[44,54],"tested":[46],"combination":[49],"most":[52],"effective":[53],"practical":[56],"(1st":[57],"derivative+SNV)":[58],"is":[59,137],"selected.":[60],"partial":[62],"least":[63],"squares":[64],"(PLS)":[65],"applied":[67],"modeling":[70],"process.":[71],"coefficient":[73],"of":[74,76,88,94,97,103,147],"determination":[75],"R":[78],"<sup":[79],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[80],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[81],",":[82],"root":[84],"mean":[85],"square":[86],"error":[87,96],"prediction":[89,98],"(RMSEP)":[90],"ratio":[93],"standard":[95,100],"to":[99],"deviation":[101],"(RPD)":[102],"obtained":[105],"optimum":[106],"models":[107],"0.94,":[109],"5.02":[110],"4.26":[112],"0.93,":[116],"2.41":[117],"3.92":[119],"0.67,":[123],"0.48":[124],"1.75":[126],"acidity,":[128],"respectively.":[129],"results":[131],"indicated":[132],"that":[133],"a":[138],"approach":[140],"predicting":[142],"matter":[144],"protein":[146],"rapidly":[151],"accurately.":[153]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}