On-Line Real-Time Monitoring of a Rapid Enzymatic Oil Degumming Process: A Feasibility Study Using Free-Run Near-Infrared Spectroscopy

被引:3
|
作者
Forsberg, Jakob [1 ]
Nielsen, Per Munk [2 ]
Engelsen, Soren Balling [1 ]
Sorensen, Klavs Martin [1 ]
机构
[1] Univ Copenhagen, Dept Food Sci, Food Analyt & Biotechnol, Rolighedsvej 26, DK-1958 Frederiksberg C, Denmark
[2] Novozymes, Oils & Fats Applicat Res, Biologiens Vej 2, DK-2800 Lyngby, Denmark
关键词
Near-infrared spectroscopy; process analytical technology (PAT); process control; processing technology; chemometrics; vegetable oil; oil refinement; variable selection; RAMAN-SPECTROSCOPY; TRANSESTERIFICATION; NIR;
D O I
10.3390/foods10102368
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
Enzymatic degumming is a well established process in vegetable oil refinement, resulting in higher oil yield and a more stable downstream processing compared to traditional degumming methods using acid and water. During the reaction, phospholipids in the oil are hydrolyzed to free fatty acids and lyso-phospholipids. The process is typically monitored by off-line laboratory measurements of the free fatty acid content in the oil, and there is a demand for an automated on-line monitoring strategy to increase both yield and understanding of the process dynamics. This paper investigates the option of using Near-Infrared spectroscopy (NIRS) to monitor the enzymatic degumming reaction. A new method for balancing spectral noise and keeping the chemical information in the spectra obtained from a rapid changing chemical process is suggested. The effect of a varying measurement averaging window width (0 to 300 s), preprocessing method and variable selection algorithm is evaluated, aiming to obtain the most accurate and robust calibration model for prediction of the free fatty acid content (% (w/w)). The optimal Partial Least Squares (PLS) model includes eight wavelength variables, as found by rPLS (recursive PLS) calibration, and yields an RMSECV (Root Mean Square Error of Cross Validation) of 0.05% (w/w) free fatty acid using five latent variables.</p>
引用
收藏
页数:15
相关论文
共 50 条
  • [1] On-Line Monitoring of Enzymatic Degumming of Soybean Oil Using Near-Infrared Spectroscopy
    Tonolini, Margherita
    Wawrzynczyk, Joanna
    Nielsen, Per Munk
    Engelsen, Soren Balling
    APPLIED SPECTROSCOPY, 2023, 77 (12) : 1333 - 1343
  • [2] On-line monitoring of starch enzymatic hydrolysis by near-infrared spectroscopy
    Blanco, M
    Coello, J
    Iturriaga, H
    Maspoch, S
    Banó, RG
    ANALYST, 2000, 125 (04) : 749 - 752
  • [3] Sensor Fusion: Comprehensive Real-Time, On-Line Monitoring for Process Control via Visible, Near-Infrared, and Raman Spectroscopy
    Lines, Amanda M.
    Hall, Gabriel B.
    Asmussen, Susan
    Allred, Jarrod
    Sinkov, Sergey
    Heller, Forrest
    Gallagher, Neal
    Lumetta, Gregg J.
    Bryan, Samuel A.
    ACS SENSORS, 2020, 5 (08) : 2467 - 2475
  • [4] FEASIBILITY OF REAL-TIME NEAR-INFRARED SPECTROSCOPY MONITORING DURING TRACHEAL INTUBATION
    Al-Subu, Awni
    Hagen, Scott
    Hsieh, Ting-Chang
    Lasarev, Michael
    CRITICAL CARE MEDICINE, 2024, 52
  • [5] Real-time monitoring of distillations by near-infrared spectroscopy
    Pasquini, C
    Scafi, SHF
    ANALYTICAL CHEMISTRY, 2003, 75 (10) : 2270 - 2275
  • [6] REAL-TIME MONITORING OF POLYURETHANE PRODUCTION USING NEAR-INFRARED SPECTROSCOPY
    DETHOMAS, FA
    HALL, JW
    MONFRE, SL
    TALANTA, 1994, 41 (03) : 425 - 431
  • [7] Real-Time Monitoring of Yogurt Fermentation Process by Aquaphotomics Near-Infrared Spectroscopy
    Muncan, Jelena
    Tei, Kyoko
    Tsenkova, Roumiana
    SENSORS, 2021, 21 (01) : 1 - 18
  • [8] Near-infrared spectroscopy for on-line monitoring of lube base oil processes
    Chung, H
    Ku, MS
    APPLIED SPECTROSCOPY, 2003, 57 (05) : 545 - 550
  • [9] On-line monitoring of the distillates of a solvent switch process by near-infrared spectroscopy
    Ge, ZH
    Buchanan, B
    Timmermans, J
    De Tora, D
    Ellison, D
    Wyvratt, J
    PROCESS CONTROL AND QUALITY, 1999, 11 (04): : 277 - 287
  • [10] Real-time monitoring of a coffee roasting process with near infrared spectroscopy using multivariate statistical analysis: A feasibility study
    Catelani, Tiago A.
    Santos, Joao Rodrigo
    Pascoa, Ricardo N. M. J.
    Pezza, Leonardo
    Pezza, Helena R.
    Lopes, Joao A.
    TALANTA, 2018, 179 : 292 - 299