Fatty Acid Prediction in Bovine Milk by Attenuated Total Reflection Infrared Spectroscopy after Solvent-Free Lipid Separation

Solvent-Free Lipid Separation and Attenuated Total Reflectance Infrared Spectroscopy for Fast and Green Fatty Acid Profiling of Human Milk

This study presents the first mid-infrared (IR)-based method capable of simultaneously predicting concentrations of individual fatty acids (FAs) and relevant sum parameters in human milk (HM). Representative fat fractions of 50 HM samples were obtained by rapid, two-step centrifugation and subsequently measured with attenuated total reflection IR spectroscopy. Partial least squares models were compiled for the acquired IR spectra with gas chromatography-mass spectrometry (GC-MS) reference data. External validation showed good results particularly for the most important FA sum parameters and the following individual FAs: C12:0 (R²_P = 0.96), C16:0 (R²_P = 0.88), C18:1cis (R²_P = 0.92), and C18:2cis (R²_P = 0.92). Based on the obtained results, the effect of different clinical parameters on the HM FA profile was investigated, indicating a change of certain sum parameters over the course of lactation. Finally, assessment of the method's greenness revealed clear superiority compared to GC-MS methods. The reported method thus represents a high-throughput, green alternative to resource-intensive established techniques.

Fatty Acid Determination in Human Milk Using Attenuated Total Reflection Infrared Spectroscopy and Solvent-Free Lipid Separation

This study introduces the first mid-infrared (IR)-based method for determining the fatty acid composition of human milk. A representative milk lipid fraction was obtained by applying a rapid and solvent-free two-step centrifugation method. Attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopy was applied to record absorbance spectra of pure milk fat. The obtained spectra were compared to whole human milk transmission spectra, revealing the significantly higher degree of fatty acid-related spectral features in ATR FT-IR spectra. Partial least squares (PLS)-based multivariate regression equations were established by relating ATR FT-IR spectra to fatty acid reference concentrations, obtained with gas chromatography-mass spectrometry (GC-MS). Good predictions were achieved for the most important fatty acid sum parameters: saturated fatty acids (SAT, R²_CV = 0.94), monounsaturated fatty acids (MONO, R²_CV = 0.85), polyunsaturated fatty acids (PUFA, R²_CV = 0.87), unsaturated fatty acids (UNSAT, R²_CV = 0.91), short-chain fatty acids (SCFA, R²_CV = 0.79), medium-chain fatty acids (MCFA, R²_CV = 0.97), and long-chain fatty acids (LCFA, R²_CV = 0.88). The PLS selectivity ratio (SR) was calculated in order to optimize and verify each individual calibration model. All mid-IR regions with high SR could be assigned to absorbances from fatty acids, indicating high validity of the obtained models.

Exploring Dry-Film FTIR Spectroscopy to Characterize Milk Composition and Subclinical Ketosis throughout a Cow's Lactation

The use of technologies for measurements of health parameters of individual cows may ensure early detection of diseases and maximization of individual cow and herd potential. In the present study, dry-film Fourier transform infrared spectroscopy (FTIR) was evaluated for the purpose of detecting and quantifying milk components during cows’ lactation. This was done in order to investigate if these systematic changes can be used to identify cows experiencing subclinical ketosis. The data included 2329 milk samples from 61 Norwegian Red dairy cows collected during the first 100 days in milk (DIM). The resulting FTIR spectra were used for explorative analyses of the milk composition. Principal component analysis (PCA) was used to search for systematic changes in the milk during the lactation. Partial least squares regression (PLSR) was used to predict the fatty acid (FA) composition of all milk samples and the models obtained were used to evaluate systematic changes in the predicted FA composition during the lactation. The results reveal that systematic changes related to both gross milk composition and fatty acid features can be seen throughout lactation. Differences in the predicted FA composition between cows with subclinical ketosis and normal cows, in particular C14:0 and C18:1cis9, showed that dietary energy deficits may be detected by deviations in distinct fatty acid features.