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Potential of Mid-Infrared Spectrometry for
Prediction of Fatty Acid Contents in Cow Milk
H. Soyeurt1,7, F. Dehareng2, P. Dardenne2, D.
Veselko3, G. Lognay4, C. Bertozzi5, P.
Mayeres1,5, V. Baeten2 N. Gengler1,6 1
Gembloux Agricultural University, Animal Science
Unit, B-5030 Gembloux, Belgium 2 Walloon
Agricultural Research Center, Quality Department,
B-5030 Gembloux, Belgium 3 Milk Committee, B-4651
Battice, Belgium 4 Gembloux Agricultural
University, Analytical Chemistry Unit, B-5030
Gembloux, Belgium 5 Walloon Breeders Association,
B-5530 Ciney, Belgium 6 National Fund for
Scientific Research, B-1000 Brussels, Belgium 7
F.R.I.A., B-1000 Brussels, Belgium

1. Aim and Objectives
3. Results and discussion
Since many years, gas chromatography is the most
widely used method to determine the fatty acids
profile. Even if this method is efficient, it
involves a time consuming procedure, some
expensive and pollutant reagents and qualified
staff. Mid-Infrared (MIR) Spectrometry
should be considered as a good alternative to
assess fatty acids contents in milk. The aim of
this study was to explore the possibilities
offered by MIR Spectrometry for the calibration
of the fatty acid concentrations in milk.
Table 1 Estimated statistical parameters for
each calibration equation that characterize
concentrations of fatty acid in milk (g/dl of
milk)
1 SD Standard deviation 2 SEC Standard
error of calibration 3 R²C Calibration
coefficient of determination 4 SECV Standard
error of cross-validation 5 R²CV
Cross-validation coefficient of determination 6
RPD Ratio of standard error of cross validation
to standard deviation 7 SAT Saturated fatty
acids 8 UNSAT Unsaturated fatty acids 9
MONO Monounsaturated fatty acids 10 POLY
Polyunsaturated fatty acids
2. Material and methods
The estimated concentrations of fatty acids
obtained with PLS were more reliable for milk
than for milk fat. In order to have good results
of prediction, we need to have a good
repeatability of the reference values and the
statistic of the equations (coefficient of
determination and RPD) must be as high as
possible. The correlations between reference GC
fatty acids and the percentage of milk fat were
lower than the correlations between the fatty
acids and the predicted values from the spectrum.
This is the prove that the MIR spectra contain
information for the different fatty acids
independently and not only for the total fat
content.
Sampling and recording spectra files Between
April to June 2005 in Wallonia, 600 milk samples
were taken from 275 cows among 6 breeds in 7
reference herds chosen using different criteria
(e.g. the percentage of milk fat or the type and
number of breeds). Then the milk samples were
analyzed by a MIR Spectrometer (FOSS MilkoScanTM
FT6000) and the spectra files were recorded in a
database. Figure 1
Example of milk spectra Reference values Among
the 600 spectra, 49 samples covering the whole
variability in the space determined by a
Principal Component Analysis (PCA) were selected.
Then, the milk fat was extracted according to ISO
141562001 and analyzed by gas chromatography
based on a methodology derived from Collomb et
al. (2000). Calibration equations Using
chromatographic and spectral data, multivariate
calibration equations were built by using Partial
Least Squares regression method (PLS).
Chromatographic data were expressed in two ways
fatty acid concentrations in milk (g/dl) and
fatty acid concentrations in milk fat (g/100g of
fat).
Figure 2 Relation between total saturated fatty
acids predicted and measured
4. Conclusion
This experiment showed that the MIR spectrometry
technique associated to the multivariate
calibration methods is a promisingly combination
for quantifying C120, C140, C160, C161 9-cis,
C181, C182 9-cis,12-cis, total saturated and
monounsaturated fatty acids in milk. All these
components represent a majority (gt70) of fatty
acids present in milk. This combination could be
used in many fields, such as, nutrition and
dietetics, genetic and animal selection, animal
feeding,
References Collomb, M. and T. Bühler. 2000.
Analyse de la composition en acides gras de la
graisse de lait. Mitt. Lebensm. Hyg. 91306-332
Soyeurt, H., Dardenne, P.,
Dehareng, F., Lognay, G., Veselko, D., Marlier,
M., Bertozzi, C., Mayeres, P. and Gengler, N.
2006. Estimating Fatty Acid Content in Cow Milk
Using Mid-Infrared Spectrometry. J. Dairy Sci.
2006 89 3690-3695. Acknowledgement Hélène
Soyeurt acknowledges the support of the FRIA
through a grant scholarschip, Danny Trisman for
his laboratory work, the Walloon Breeding
Association (AWE), the Walloon Milk Committee,
Walloon Agricultural Research centre and the
Walloon Regional
Ministry of Agriculture for his partial
financial support.
Walloon Agricultural Research Center, Quality
Department Chaussée de Namur, 24 5030
GEMBLOUX - Tél  [phone] - Fax 
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