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182 related items for PubMed ID: 35056650

  • 1. Rapid Measurement of Cellulose, Hemicellulose, and Lignin Content in Sargassum horneri by Near-Infrared Spectroscopy and Characteristic Variables Selection Methods.
    Ai N, Jiang Y, Omar S, Wang J, Xia L, Ren J.
    Molecules; 2022 Jan 06; 27(2):. PubMed ID: 35056650
    [Abstract] [Full Text] [Related]

  • 2. Rapid detection of cellulose and hemicellulose contents of corn stover based on near-infrared spectroscopy combined with chemometrics.
    Wang N, Li L, Liu J, Shi J, Lu Y, Zhang B, Sun Y, Li W.
    Appl Opt; 2021 May 20; 60(15):4282-4290. PubMed ID: 34143114
    [Abstract] [Full Text] [Related]

  • 3. Prediction of Lignin Content in Different Parts of Sugarcane Using Near-Infrared Spectroscopy (NIR), Ordered Predictors Selection (OPS), and Partial Least Squares (PLS).
    Assis C, Ramos RS, Silva LA, Kist V, Barbosa MHP, Teófilo RF.
    Appl Spectrosc; 2017 Aug 20; 71(8):2001-2012. PubMed ID: 28452227
    [Abstract] [Full Text] [Related]

  • 4. Feasibility of an NIR spectral calibration transfer algorithm based on optimized feature variables to predict tobacco samples in different states.
    Geng Y, Ni H, Shen H, Wang H, Wu J, Pan K, Wu Y, Chen Y, Luo Y, Xu T, Liu X.
    Anal Methods; 2023 Feb 09; 15(6):719-728. PubMed ID: 36722963
    [Abstract] [Full Text] [Related]

  • 5. Rapid Determination of Cellulose and Hemicellulose Contents in Corn Stover Using Near-Infrared Spectroscopy Combined with Wavelength Selection.
    Wang N, Feng J, Li L, Liu J, Sun Y.
    Molecules; 2022 May 24; 27(11):. PubMed ID: 35684314
    [Abstract] [Full Text] [Related]

  • 6. Determination of hemicellulose, cellulose and lignin content using visible and near infrared spectroscopy in Miscanthus sinensis.
    Jin X, Chen X, Shi C, Li M, Guan Y, Yu CY, Yamada T, Sacks EJ, Peng J.
    Bioresour Technol; 2017 Oct 24; 241():603-609. PubMed ID: 28601778
    [Abstract] [Full Text] [Related]

  • 7. Determination of Hemicellulose, Cellulose and Lignin in Moso Bamboo by Near Infrared Spectroscopy.
    Li X, Sun C, Zhou B, He Y.
    Sci Rep; 2015 Nov 25; 5():17210. PubMed ID: 26601657
    [Abstract] [Full Text] [Related]

  • 8. Determination of metmyoglobin in cooked tan mutton using Vis/NIR hyperspectral imaging system.
    Yuan R, Liu G, He J, Ma C, Cheng L, Fan N, Ban J, Li Y, Sun Y.
    J Food Sci; 2020 May 25; 85(5):1403-1410. PubMed ID: 32304238
    [Abstract] [Full Text] [Related]

  • 9. [Prediction of Cellulose, Hemicellulose, Lignin and Ash Content of Four Miscanthus Bio-Energy Crops Using Near-Infrared Spectroscopy].
    Li XN, Fan XF, Wu JY, Zhang GF, Liu SY, Wu MJ, Cheng YB, Zhang N.
    Guang Pu Xue Yu Guang Pu Fen Xi; 2016 Jan 25; 36(1):64-9. PubMed ID: 27228742
    [Abstract] [Full Text] [Related]

  • 10. Determination of hemicellulose, cellulose, holocellulose and lignin content using FTIR in Calycophyllum spruceanum (Benth.) K. Schum. and Guazuma crinita Lam.
    Javier-Astete R, Jimenez-Davalos J, Zolla G.
    PLoS One; 2021 Jan 25; 16(10):e0256559. PubMed ID: 34705842
    [Abstract] [Full Text] [Related]

  • 11. Measurement of non-sugar solids content in Chinese rice wine using near infrared spectroscopy combined with an efficient characteristic variables selection algorithm.
    Ouyang Q, Zhao J, Chen Q.
    Spectrochim Acta A Mol Biomol Spectrosc; 2015 Jan 25; 151():280-5. PubMed ID: 26143319
    [Abstract] [Full Text] [Related]

  • 12. Fine root lignin content is well predictable with near-infrared spectroscopy.
    Elle O, Richter R, Vohland M, Weigelt A.
    Sci Rep; 2019 Apr 23; 9(1):6396. PubMed ID: 31015553
    [Abstract] [Full Text] [Related]

  • 13. [Rapid determination of active components in Ginkgo biloba leaves by near infrared spectroscopy combined with genetic algorithm joint extreme learning machine].
    Ni HF, Si LT, Huang JP, Zan Q, Chen Y, Luan LJ, Wu YJ, Liu XS.
    Zhongguo Zhong Yao Za Zhi; 2021 Jan 23; 46(1):110-117. PubMed ID: 33645059
    [Abstract] [Full Text] [Related]

  • 14. Measurement of total flavone content in snow lotus (Saussurea involucrate) using near infrared spectroscopy combined with interval PLS and genetic algorithm.
    Chen Q, Jiang P, Zhao J.
    Spectrochim Acta A Mol Biomol Spectrosc; 2010 Jun 23; 76(1):50-5. PubMed ID: 20338806
    [Abstract] [Full Text] [Related]

  • 15. [Determination of holocellulose and lignin content in Chinese fir by near infrared spectroscopy].
    Huang AM, Jiang ZH, Li GY.
    Guang Pu Xue Yu Guang Pu Fen Xi; 2007 Jul 23; 27(7):1328-31. PubMed ID: 17944406
    [Abstract] [Full Text] [Related]

  • 16. Effects of variable selection and processing of NIR and ATR-IR spectra on the prediction of extractive content in Eucalyptus bosistoana heartwood.
    Li Y, Altaner CM.
    Spectrochim Acta A Mol Biomol Spectrosc; 2019 Apr 15; 213():111-117. PubMed ID: 30684879
    [Abstract] [Full Text] [Related]

  • 17. Using an optimal CC-PLSR-RBFNN model and NIR spectroscopy for the starch content determination in corn.
    Jiang H, Lu J.
    Spectrochim Acta A Mol Biomol Spectrosc; 2018 May 05; 196():131-140. PubMed ID: 29444495
    [Abstract] [Full Text] [Related]

  • 18. Prediction of hot-water-soluble extractive, pentosan and cellulose content of various wood species using FT-NIR spectroscopy.
    He W, Hu H.
    Bioresour Technol; 2013 Jul 05; 140():299-305. PubMed ID: 23711938
    [Abstract] [Full Text] [Related]

  • 19. Prediction of tea theanine content using near-infrared spectroscopy and flower pollination algorithm.
    Ong P, Chen S, Tsai CY, Chuang YK.
    Spectrochim Acta A Mol Biomol Spectrosc; 2021 Jul 05; 255():119657. PubMed ID: 33744842
    [Abstract] [Full Text] [Related]

  • 20. Highly identification of keemun black tea rank based on cognitive spectroscopy: Near infrared spectroscopy combined with feature variable selection.
    Ren G, Wang Y, Ning J, Zhang Z.
    Spectrochim Acta A Mol Biomol Spectrosc; 2020 Apr 05; 230():118079. PubMed ID: 31982655
    [Abstract] [Full Text] [Related]

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