Determination of Main Categories of Components in Corn Steep Liquor by Near-Infrared Spectroscopy and Partial Least-Squares Regression

被引:22
|
作者
Xiao, Xue [1 ,2 ,3 ]
Hou, Yuanyuan [1 ,2 ]
Du, Jun [4 ,5 ]
Liu, Yang [1 ,2 ]
Liu, Yanjie [1 ,2 ,6 ]
Dong, Linyi [1 ,2 ]
Liang, Qionglin [3 ]
Wang, Yiming [3 ]
Bai, Gang [1 ,2 ]
Luo, Guoan [1 ,3 ]
机构
[1] Nankai Univ, Coll Pharm, Tianjin 300071, Peoples R China
[2] Nankai Univ, State Key Lab Med Chem Biol, Tianjin 300071, Peoples R China
[3] Tsinghua Univ, Dept Chem, Beijing 100084, Peoples R China
[4] Nankai Univ, Coll Life Sci, Tianjin 300071, Peoples R China
[5] China Biotech Fermentat Ind Assoc, Beijing 100833, Peoples R China
[6] Tianjin Univ Tradit Chinese Med, Coll Pharm, Tianjin 300193, Peoples R China
关键词
corn steep liquor; NIR; amino acid; PLSR; PCA; FT-NIR SPECTROSCOPY; PRODUCTS; QUALITY; WATER; WHEAT; ACIDS; GRAIN;
D O I
10.1021/jf3012823
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Corn steep liquor (CSL) is an important raw material that has a high nutritional value and serves as a nitrogen source. This study aimed to develop a fast, versatile, cheap, and environmentally safe analytical method of quantifying the total acidity (TA) of CSL as well as its contents of dry matter (DM), total sugars (TS), total reducing sugars (TRS), total free amino acids (TFAA), total nitrogen (TN), and total sulfite (TSu). The near-infrared (NIR) spectroscopy measurements of 66 samples (22 batches) of CSL were analyzed by partial least-squares regression using several spectral preprocessing methods. Multivariate models developed in the NIR area showed good predictive abilities for DM, TA, TS, TRS, TFAA, TN, and TSu determination. These results confirm the feasibility of the multivariate spectroscopic approach as a replacement for expensive and time-consuming conventional chemical methods. Thus, a convenient and feasible method for the quality control of fermentation raw materials for food additives and fine chemicals, especially in CSL, is established.
引用
收藏
页码:7830 / 7835
页数:6
相关论文
共 50 条
  • [31] Determination of glycated hemoglobin using near-infrared spectroscopy combined with equidistant combination partial least squares
    Han, Yun
    Chen, Jiemei
    Pan, Tao
    Liu, Guisong
    [J]. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2015, 145 : 84 - 92
  • [32] Genetic algorithm-based method for selecting wavelengths and model size for use with partial least-squares regression: Application to near-infrared spectroscopy
    Bangalore, AS
    Shaffer, RE
    Small, GW
    Arnold, MA
    [J]. ANALYTICAL CHEMISTRY, 1996, 68 (23) : 4200 - 4212
  • [33] Assessment of partial least-squares calibration and wavelength selection for complex near-infrared spectra
    McShane, MJ
    Cote, GL
    Spiegelman, CH
    [J]. APPLIED SPECTROSCOPY, 1998, 52 (06) : 878 - 884
  • [34] Partial least squares regression calibration for determining wax content in processed flax fiber by near-infrared spectroscopy
    Sohn, M
    Himmelsbach, DS
    Morrison, WH
    Akin, DE
    Barton, FE
    [J]. APPLIED SPECTROSCOPY, 2006, 60 (04) : 437 - 440
  • [35] Analysis of contaminants in lubricant oil by near infrared spectroscopy and interval partial least-squares
    Paschoal, J
    Barboza, FD
    Poppi, RJ
    [J]. JOURNAL OF NEAR INFRARED SPECTROSCOPY, 2003, 11 (03) : 211 - 218
  • [36] Optimisation of partial least squares regression calibration models in near-infrared spectroscopy: a novel algorithm for wavelength selection
    Smith, MR
    Jee, RD
    Moffat, AC
    Rees, DR
    Broad, NW
    [J]. ANALYST, 2003, 128 (11) : 1312 - 1319
  • [37] An improved partial least-squares regression method for Raman spectroscopy
    Monfared, Ali Momenpour Tehran
    Anis, Hanan
    [J]. SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2017, 185 : 98 - 103
  • [38] Comparison of the vibration mode of metals in HNO3 by a partial least-squares regression analysis of near-infrared spectra
    Sakudo, Akikazu
    Tsenkova, Roumiana
    Tei, Kyoko
    Onozuka, Taisuke
    Ikuta, Kazuyoshi
    Yoshimura, Etsuro
    Onodera, Takashi
    [J]. BIOSCIENCE BIOTECHNOLOGY AND BIOCHEMISTRY, 2006, 70 (07) : 1578 - 1583
  • [39] NIR spectroscopy and partial least-squares regression for determination of natural α-tocopherol in vegetable oils
    Szlyk, E
    Szydlowska-Czerniak, A
    Kowalczyk-Marzec, A
    [J]. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY, 2005, 53 (18) : 6980 - 6987
  • [40] Application of latent root regression for calibration in near-infrared spectroscopy. Comparison with principal component regression and partial least squares
    Vigneau, E
    Bertrand, D
    Qannari, EM
    [J]. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 1996, 35 (02) : 231 - 238