TY - GEN
T1 - Towards in-flow monitoring of fat content and fluid composition of dairy milk using microfluidic confocal Raman spectroscopy
AU - Canyelles Pericàs, P.
AU - Sundararajan, A.
AU - Wiegerink, R.
AU - Lötters, J.C.
N1 - Funding Information:
This publication is part of the Perspectief program Synoptic Optics 2018 TTW with project number P17-24 project 6 which is (partly) financed by the Dutch Research Council (NWO). We thank Hanna de Wolf and Dr. Nienke Bosschaart from the Biomedical Photonic Imaging group at the University of Twente for valuable discussions and advice. We acknowledge Dr. Ine Segers-Nolten, laboratory manager for the University of Twente BioNanoLab, for technical support.
Publisher Copyright:
Copyright © 2022 SPIE.
PY - 2022
Y1 - 2022
N2 - Dairy milk composition analysis is critical for quality control and pricing purposes. Particularly, fat content in dairy milk determines its market value, and free fatty acids can be used as a proxy for milk quality. Milk with high fat contents (4% and above) is progressively skimmed to obtain a chain of products (butter, cheese, milk, powder milk, etc.), increasing the profitability in a traditionally low-margin industry. Besides total fat percentage, the composition of fatty acids is also relevant, as C14, C16 and C18 free fatty acids can be used to monitor cattle food intake. Established chemical separation techniques to measure fat content, such as the Gerber method, are off-line, manual, labor intensive, cannot distinguish fats and have a high error margin. We present a monitoring system concept, free of labelling and sample processing, for fat milk content using Raman spectroscopy in flowing microfluidic channels. The technique has been tested using several microfluidic flow rates (20 μl/min to 1000 μl/min) with Raman measurements of 5 seconds of exposure time and with a single accumulation. We show that Raman spectra remain the same even after continuously refreshing the fluid during measurements at increasing flow rates. Proof of concept Raman measurements at the region of interest for undiluted whole (3.5% of fat), semi-skimmed (1.5%) and buttermilk (0.5%) are presented under different microfluidic flows, showing the potential of the technique. The technique can also be used to identify different fats, proteins, and minerals.
AB - Dairy milk composition analysis is critical for quality control and pricing purposes. Particularly, fat content in dairy milk determines its market value, and free fatty acids can be used as a proxy for milk quality. Milk with high fat contents (4% and above) is progressively skimmed to obtain a chain of products (butter, cheese, milk, powder milk, etc.), increasing the profitability in a traditionally low-margin industry. Besides total fat percentage, the composition of fatty acids is also relevant, as C14, C16 and C18 free fatty acids can be used to monitor cattle food intake. Established chemical separation techniques to measure fat content, such as the Gerber method, are off-line, manual, labor intensive, cannot distinguish fats and have a high error margin. We present a monitoring system concept, free of labelling and sample processing, for fat milk content using Raman spectroscopy in flowing microfluidic channels. The technique has been tested using several microfluidic flow rates (20 μl/min to 1000 μl/min) with Raman measurements of 5 seconds of exposure time and with a single accumulation. We show that Raman spectra remain the same even after continuously refreshing the fluid during measurements at increasing flow rates. Proof of concept Raman measurements at the region of interest for undiluted whole (3.5% of fat), semi-skimmed (1.5%) and buttermilk (0.5%) are presented under different microfluidic flows, showing the potential of the technique. The technique can also be used to identify different fats, proteins, and minerals.
KW - Fluid composition
KW - In-flow measurements
KW - Microfluidic sensing
KW - Milk
KW - Raman spectroscopy
KW - 2023 OA procedure
UR - http://www.scopus.com/inward/record.url?scp=85129138318&partnerID=8YFLogxK
U2 - 10.1117/12.2610154
DO - 10.1117/12.2610154
M3 - Conference contribution
AN - SCOPUS:85129138318
SN - 9781510647817
T3 - Proceedings of SPIE
BT - Microfluidics, BioMEMS, and Medical Microsystems XX
A2 - Gray, Bonnie L.
A2 - Becker, Holger
PB - SPIE Press
CY - Bellingham, WA
T2 - Microfluidics, BioMEMS, and Medical Microsystems XX 2022
Y2 - 20 February 2022 through 24 February 2022
ER -