Spectroscopy of Food

Fourier Transform Infrared Spectroscopy (FTIR) has been shown to be a powerful tool for the food quality control and safety. One of the areas where FTIR is used is characterization of the chemical composition of milk in the dairy industry. Routine FTIR milk analyzers are used in milk production facilities all over the world to predict bulk parameters such as fat, lactose, protein, urea, pH, etc. Members of our group have been among the first researchers establishing calibration models for fatty acid composition. By these models in collaboration with IHA lipid profiles of millions of cows were obtained and used in breeding programs and for genetic improvement of milk quality: fat content and fat composition of milk. Since both characteristics are highly heritable traits they can be effectively improved by breeding.

In collaboration with ProMed at NMBU we have showed that FTIR spectra can not only provide the information of milk composition but also monitor cow’s health predicting health traits like energy balance (EB), dry matter intake (DMI) and efficient energy intake (EEI)) in lactating dairy cows as well as cows with subclinical ketosis.

Food safety is another area where FTIR spectroscopy is used as a powerful method. Our group is involved in research of new photonic devices that can be used along production chain. We are coordinating an EU project called PHOTONFOOD. The objective of the research project is to design a portable and flexible device to identify microbial and chemical contamination in the food production chain and in finished food products. The aim of developing, testing and demonstrating a compact, portable, adaptable and multifunctional technology solution is to significantly cut the costs of testing for fungi, mycotoxins, pesticides and antibiotics in all parts of the food chain.

Togeter with partners in Digital Food Quality (DigiFoods) we will be involved in the development of smart sensors for food quality assessment directly in the processing lines. The obtained information will be used for optimization of processes and value chains and make the food industry more efficient and sustainable.



PHOTONFOOD - Flexible Mid-Infrared Photonic Solution for Rapid Farm-to-Fork Sensing of Food Contaminants
European Commision (H2020-ICT-2020-2, Project Nº 101016444)

DigiFoods - Digital Food Quality
Research Council of Norway SFI project Nº. 309259)

Genome-based improvement of bovine milk fat composition
Research Council of Norway, Project Nº 225173

AMS - New approaches for management and breeding of dairy cows, in automatic milking systems
Research Council of Norway, Project Nº 244231




Knutsen T.M., Olsen H.G., Ketto I.A., Sundsaasen K.K, Kohler A., Tafintseva V., Svendsen M., Kent M.P., Lien S. 
Genetic variants associated with two major bovine milk fatty acids offer opportunities to breed for altered milk fat composition.
Genetics Selection Evolution 54 (2022) 35

Rachah A., Reksen O., Afseth N., Tafintseva V., Ferneborg S., Martin A., Kohler A., Prestløkken E. 
Fourier transform infrared spectral data as a tool to predict energy balance, energy- and dry matter intake in lactating dairy cows
Journal of dairy research (2020) 1-8

Knutsen T.M., Olsen H.G., Tafintseva V., Svendsen M., Kohler A., Kent M.P., Lien S.
Unravelling genetic variation underlying de novo-synthesis of bovine milk fatty acids.
Scientific reports 8 (2018) 2179.

Nørstebø H., Rachah A., Dalen G., Rønningen O., Whist A.C., Reksen O. 
Milk-flow data collected routinely in an automatic milking system: an alternative to milking-time testing in the management of teat-end condition?
Acta Veterinaria Scandinavica 60:2 (2018) doi: 10.1186/s13028-018-0356-x.

Dalen G., Rachah A., Nørstebø H., Schukken Y.H., Gröhn Y.T., Barlow J.W., Reksen O. 
Transmission dynamics of intramammary infections caused by Corynebacterium species.
Journal of Dairy Science 101 (2018) 472.

Rachah A., Dalen G., Reksen O., Nørstebø H., Barlow J.W. 
Modelling and dynamics of intramammary infections caused by Corynebacterium species.
IEEE Xplore, 2017. doi:10.1109/ICMSAO.2017.7934858

Olsen H.G., Knutsen T.M., Kohler A., Svendsen M., Gidskehaug L., Grove H., Nome T., Sodeland M., Sundsaasen K.K., Kent M.P., Martens H., Lien S.
Genome-wide association mapping for milk fat composition and fine mapping of a QTL for de novo synthesis of milk fatty acids on bovine chromosome 13.
Genetics Selection Evolution, 49:20 (2017) doi:10.1186/s12711-017-0294-5

Martin A.D., Afseth N.K., Kohler A., Randby Å., Eknæs M., Waldmann A., Dørum G., Måge I., Reksen O. 
The relationship between fatty acid profiles in milk identified by Fourier transform infrared spectroscopy and onset of luteal activity in Norwegian dairy cattle.
Journal of Dairy Science 98 (2015) 1.

Afseth N.K., Martens H., Giskehaug L., Narum B., Jørgensen K., Lien S., Haug A., Kohler A. 
Predicting fatty acid composition of milk - A comparison of two FTIR sampling techniques.
Applied Spectroscopy 64 (2010) 700.

Martens H., Kohler A., Afseth N.K., Wold J.P., Hersleth M., Berget I., Ådnøy T., Skaugen M., Isaksson T., Vegarud G., Criscione A., Frøst M.B., Randby Å., Prestløkken E., Berg P., Kent M., Lien S., Omholt S.W. 
High-throughput measurements for functional genomics of milk.
Journal of Animal and Feed Sciences 16 (2007) 172.


Published 23. May 2016 - 15:13 - Updated 4. October 2022 - 16:06