TY - JOUR

T1 - On‐line real‐time monitoring of a rapid enzymatic oil degumming process

T2 - A feasibility study using free‐run near‐infrared spectroscopy

AU - Forsberg, Jakob

AU - Nielsen, Per Munk

AU - Engelsen, Søren Balling

AU - Sørensen, Klavs Martin

N1 - This article belongs to the Special Issue Advances in NIR Spectroscopy Analytical Technology in Food Industries.

PY - 2021

Y1 - 2021

N2 - 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 online 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.

AB - 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 online 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.

KW - Chemometrics

KW - Near‐Infrared spectroscopy

KW - Oil refinement

KW - Process analytical technology (PAT)

KW - Process control

KW - Processing technology

KW - Variable selection

KW - Vegetable oil

U2 - 10.3390/foods10102368

DO - 10.3390/foods10102368

M3 - Journal article

C2 - 34681417

AN - SCOPUS:85117243244

VL - 10

JO - Foods

JF - Foods

SN - 2304-8158

IS - 10

M1 - 2368

ER -