{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T10:42:10Z","timestamp":1792233730794,"version":"4.4.0"},"reference-count":39,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2027,2,1]],"date-time":"2027-02-01T00:00:00Z","timestamp":1801440000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2027,2,1]],"date-time":"2027-02-01T00:00:00Z","timestamp":1801440000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2027,2,1]],"date-time":"2027-02-01T00:00:00Z","timestamp":1801440000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2027,2,1]],"date-time":"2027-02-01T00:00:00Z","timestamp":1801440000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2027,2,1]],"date-time":"2027-02-01T00:00:00Z","timestamp":1801440000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2027,2,1]],"date-time":"2027-02-01T00:00:00Z","timestamp":1801440000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2027,2,1]],"date-time":"2027-02-01T00:00:00Z","timestamp":1801440000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100005046","name":"Heilongjiang Province Natural Science Foundation","doi-asserted-by":"publisher","award":["LH2019C075"],"award-info":[{"award-number":["LH2019C075"]}],"id":[{"id":"10.13039\/501100005046","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy"],"published-print":{"date-parts":[[2027,2]]},"DOI":"10.1016\/j.saa.2026.128827","type":"journal-article","created":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T06:25:32Z","timestamp":1789971932000},"page":"128827","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Chemical fingerprinting of rapeseed varieties: A BiLSTM-based fusion strategy for near-infrared and fluorescence spectra"],"prefix":"10.1016","volume":"366","author":[{"given":"Wenlong","family":"Su","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Limin","family":"Suo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lili","family":"Qian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hailong","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liyuan","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.saa.2026.128827_bb0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.ncrops.2025.100078","article-title":"Identification, characteristics, and cytological analysis of three disomic alien addition lines of Brassica napus- Raphanus sativus","volume":"3","author":"Hu","year":"2026","journal-title":"New Crops"},{"key":"10.1016\/j.saa.2026.128827_bb0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.jksus.2024.103412","article-title":"An overview of the molecular and biochemical components of seed dormancy and germination in Brassica napus","volume":"36","author":"Pandian","year":"2024","journal-title":"J. King Saud Univ. - Sci."},{"key":"10.1016\/j.saa.2026.128827_bb0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.dib.2021.107392","article-title":"RNA sequencing data for responses to drought stress and\/or clubroot infection in developing seeds of brassica napus","volume":"38","author":"Bianchetti","year":"2021","journal-title":"Data Brief"},{"key":"10.1016\/j.saa.2026.128827_bb0020","article-title":"Seed yield, physiological and biochemical attributes in canola (Brassica napus L.) as influenced by tillage system and cropping season","volume":"14","author":"Sellami","year":"2023","journal-title":"J. Agric. Food Res."},{"key":"10.1016\/j.saa.2026.128827_bb0025","doi-asserted-by":"crossref","DOI":"10.1016\/j.foodchem.2023.138029","article-title":"Fingerprinting black tea: when spectroscopy meets machine learning a novel workflow for geographical origin identification","volume":"438","author":"Li","year":"2024","journal-title":"Food Chem."},{"key":"10.1016\/j.saa.2026.128827_bb0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.jfca.2021.103810","article-title":"Assessing black tea quality based on visible\u2013near infrared spectra and kernel-based methods","volume":"98","author":"Ren","year":"2021","journal-title":"J. Food Compos. Anal."},{"key":"10.1016\/j.saa.2026.128827_bb0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.jcs.2021.103322","article-title":"Rapid identification of the variety and geographical origin of wuyou no.4 rice by fourier transform near-infrared spectroscopy coupled with chemometrics","volume":"102","author":"Peijin","year":"2021","journal-title":"J. Cereal Sci."},{"key":"10.1016\/j.saa.2026.128827_bb0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.foodchem.2022.133425","article-title":"Determining the geographical origin and cultivation methods of Shanghai special rice using NIR and IRMS","volume":"394","author":"Liu","year":"2022","journal-title":"Food Chem."},{"key":"10.1016\/j.saa.2026.128827_bb0045","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1007\/s12161-020-01893-2","article-title":"Identification of edible gelatin origins by data fusion of NIRS, fluorescence spectroscopy, and LIBS","volume":"14","author":"Zhang","year":"2021","journal-title":"Food Anal. Methods"},{"key":"10.1016\/j.saa.2026.128827_bb0050","doi-asserted-by":"crossref","first-page":"3217","DOI":"10.1007\/s00217-023-04361-3","article-title":"The classification of leek seeds based on fluorescence spectroscopic data using machine learning","volume":"249","author":"Ropelewska","year":"2023","journal-title":"Eur. Food Res. Technol."},{"key":"10.1016\/j.saa.2026.128827_bb0055","doi-asserted-by":"crossref","DOI":"10.1016\/j.saa.2025.126463","article-title":"Discrimination of normal and wooden breast chicken fillets using NIR, fluorescence and raman spectroscopy","volume":"343","author":"Mu\u00f1oz-Lapeira","year":"2025","journal-title":"Spectrochim. Acta A"},{"key":"10.1016\/j.saa.2026.128827_bb0060","doi-asserted-by":"crossref","DOI":"10.1016\/j.microc.2025.113384","article-title":"Rapid origin traceability and quality evaluation of artemisia argyi folium empowered by excitation-emission fluorescence spectroscopy and machine learning","volume":"212","author":"Nie","year":"2025","journal-title":"Microchem. J."},{"key":"10.1016\/j.saa.2026.128827_bb0065","doi-asserted-by":"crossref","DOI":"10.1016\/j.chemolab.2025.105468","article-title":"Wine variety traceability by data fusion of near-infrared(NIR) spectroscopy and mid-infrared (MIR) spectroscopy combined with GAF and ResNet","volume":"264","author":"Xie","year":"2025","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"10.1016\/j.saa.2026.128827_bb0070","doi-asserted-by":"crossref","DOI":"10.1016\/j.fochx.2025.103137","article-title":"MSI-FusionNet: a multi-modal spectral-image fusion network for sorghum variety identification","volume":"31","author":"Hu","year":"2025","journal-title":"Food Chem. X"},{"key":"10.1016\/j.saa.2026.128827_bb0075","doi-asserted-by":"crossref","DOI":"10.1016\/j.saa.2025.127210","article-title":"Intelligent species identification of Fritillaria spp. based on multispectral feature fusion","volume":"348","author":"Tang","year":"2026","journal-title":"Spectrochim. Acta A"},{"key":"10.1016\/j.saa.2026.128827_bb0080","doi-asserted-by":"crossref","DOI":"10.1016\/j.heliyon.2024.e35512","article-title":"Novel authentication of African geographical coffee types (bean, roasted, powdered) by handheld NIR spectroscopic method","volume":"10","author":"Boadu","year":"2024","journal-title":"Heliyon"},{"key":"10.1016\/j.saa.2026.128827_bb0085","doi-asserted-by":"crossref","DOI":"10.1016\/j.saa.2025.126306","article-title":"Combining Vis-NIR and NIR hyperspectral imaging techniques with a data fusion strategy for rapid and nondestructive determination of multiple nutritional qualities in flaxseed","volume":"340","author":"Zhu","year":"2025","journal-title":"Spectrochim. Acta A"},{"key":"10.1016\/j.saa.2026.128827_bb0090","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.aca.2014.12.033","article-title":"A consensus successive projections algorithm \u2013 multiple linear regression method for analyzing near infrared spectra","volume":"858","author":"Liu","year":"2015","journal-title":"Anal. Chim. Acta"},{"key":"10.1016\/j.saa.2026.128827_bb0095","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.126833","article-title":"ODTE\u2014an ensemble of multi-class SVM-based oblique decision trees","volume":"273","author":"Monta\u00f1ana","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.saa.2026.128827_bb0100","doi-asserted-by":"crossref","DOI":"10.1016\/j.lwt.2023.114701","article-title":"Edibility and species discrimination of wild bolete mushrooms using FT-NIR spectroscopy combined with DD-SIMCA and RF models","volume":"180","author":"Chen","year":"2023","journal-title":"LWT"},{"key":"10.1016\/j.saa.2026.128827_bb0105","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2024.127323","article-title":"Hierarchical text classification with multi-label contrastive learning and KNN","volume":"577","author":"Zhang","year":"2024","journal-title":"Neurocomputing"},{"key":"10.1016\/j.saa.2026.128827_bb0110","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1016\/j.procs.2025.07.074","article-title":"BiLSTM-based approach for music genre classification","volume":"263","author":"Lin","year":"2025","journal-title":"Procedia Comput. Sci."},{"key":"10.1016\/j.saa.2026.128827_bb0115","doi-asserted-by":"crossref","first-page":"14286","DOI":"10.1038\/s41598-023-40863-6","article-title":"Identification of growth years for puerariae thomsonii radix based on hyperspectral imaging technology and deep learning algorithm","volume":"13","author":"Zhang","year":"2023","journal-title":"Sci. Rep."},{"key":"10.1016\/j.saa.2026.128827_bb0120","series-title":"Practical guide to interpretive near-infrared spectroscopy","author":"Workman","year":"2007"},{"key":"10.1016\/j.saa.2026.128827_bb0125","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1255\/jnirs.786","article-title":"Incorporating chemical band-assignment in near infrared spectroscopy regression models","volume":"16","author":"Westad","year":"2008","journal-title":"J. Near Infrared Spectrosc."},{"key":"10.1016\/j.saa.2026.128827_bb0130","doi-asserted-by":"crossref","DOI":"10.1016\/j.fufo.2023.100241","article-title":"Prediction of potato dry matter content by FT-NIR spectroscopy: impact of tuber tissue on model performance","volume":"8","author":"Bedini","year":"2023","journal-title":"Future Foods"},{"key":"10.1016\/j.saa.2026.128827_bb0135","doi-asserted-by":"crossref","DOI":"10.1016\/j.heliyon.2023.e23000","article-title":"Assessing the differences of two vineyards soils\u2019 by NIR spectroscopy and chemometrics","volume":"9","author":"Machado","year":"2023","journal-title":"Heliyon"},{"key":"10.1016\/j.saa.2026.128827_bb0140","article-title":"Geographic origin discrimination and quantification of phenolic compounds and moisture in Artemisia argyi folium using NIRS and chemometrics","volume":"23","author":"Hu","year":"2025","journal-title":"J. Agric. Food Res."},{"key":"10.1016\/j.saa.2026.128827_bb0145","doi-asserted-by":"crossref","first-page":"759","DOI":"10.1021\/jf048742p","article-title":"Fluorescence of vegetable oils: olive oils","volume":"53","author":"Zandomeneghi","year":"2005","journal-title":"J. Agric. Food Chem."},{"key":"10.1016\/j.saa.2026.128827_bb0150","doi-asserted-by":"crossref","DOI":"10.1016\/j.talo.2024.100334","article-title":"Non-destructive fluorescence spectroscopy for quality evaluation of almond oils extracted from roasted kernel","volume":"9","author":"Mart\u00edn-Tornero","year":"2024","journal-title":"Talanta Open"},{"key":"10.1016\/j.saa.2026.128827_bb0155","doi-asserted-by":"crossref","DOI":"10.1016\/j.foodchem.2023.137931","article-title":"Rapid quality evaluation and geographical origin recognition of ginger powder by portable NIRS in tandem with chemometrics","volume":"438","author":"Chen","year":"2024","journal-title":"Food Chem."},{"key":"10.1016\/j.saa.2026.128827_bb0160","first-page":"4257","article-title":"SVM and KNN based CNN architectures for plant classification","volume":"71","author":"Ghosh","year":"2022","journal-title":"Comput. Mater. Contin."},{"key":"10.1016\/j.saa.2026.128827_bb0165","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109122","article-title":"Variety classification and identification of jujube based on near-infrared spectroscopy and 1D-CNN","volume":"223","author":"Li","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.saa.2026.128827_bb0170","doi-asserted-by":"crossref","DOI":"10.1016\/j.jksuci.2024.102126","article-title":"A novel deep CNN model with entropy coded sine cosine for corn disease classification","volume":"36","author":"Malik","year":"2024","journal-title":"J. King Saud Univ. Comput. Inf. Sci."},{"key":"10.1016\/j.saa.2026.128827_bb0175","doi-asserted-by":"crossref","DOI":"10.1016\/j.foodcont.2024.110740","article-title":"Salmon origin traceability based on hyperspectral imaging data fusion strategy and improved deep learning method","volume":"166","author":"Zou","year":"2024","journal-title":"Food Control"},{"key":"10.1016\/j.saa.2026.128827_bb0180","doi-asserted-by":"crossref","DOI":"10.1016\/j.jfca.2024.106259","article-title":"Hyperspectral imaging combined with spectral-imagery feature fusion convolutional neural network to discriminate different geographical origins of wolfberries","volume":"132","author":"Jiang","year":"2024","journal-title":"J. Food Compos. Anal."},{"key":"10.1016\/j.saa.2026.128827_bb0185","doi-asserted-by":"crossref","DOI":"10.1016\/j.foodchem.2025.143698","article-title":"Geographical origin authentication of instant coffee from southern bahia using MIR and NIR spectroscopy coupled with DD-SIMCA","volume":"479","author":"Candeias","year":"2025","journal-title":"Food Chem."},{"key":"10.1016\/j.saa.2026.128827_bb0190","doi-asserted-by":"crossref","DOI":"10.1016\/j.microc.2025.115294","article-title":"Non-destructive quantification of tobacco blend components using FT-NIR spectroscopy coupled with multivariate machine learning","volume":"218","author":"Xiao","year":"2025","journal-title":"Microchem. J."},{"key":"10.1016\/j.saa.2026.128827_bb0195","doi-asserted-by":"crossref","DOI":"10.1016\/j.lwt.2026.119237","article-title":"Feature-optimized ResNet\u2013BiLSTM model with hyperspectral imaging for non-destructive quality prediction of salted kimchi cabbage processed by various salting methods","volume":"246","author":"Choi","year":"2026","journal-title":"LWT"}],"container-title":["Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1386142526013983?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1386142526013983?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T09:51:53Z","timestamp":1792230713000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1386142526013983"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2027,2]]},"references-count":39,"alternative-id":["S1386142526013983"],"URL":"https:\/\/doi.org\/10.1016\/j.saa.2026.128827","relation":{},"ISSN":["1386-1425"],"issn-type":[{"value":"1386-1425","type":"print"}],"subject":[],"published":{"date-parts":[[2027,2]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Chemical fingerprinting of rapeseed varieties: A BiLSTM-based fusion strategy for near-infrared and fluorescence spectra","name":"articletitle","label":"Article Title"},{"value":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.saa.2026.128827","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"128827"}}