Use of Fourier transform infrared (FTIR) spectroscopy to determine the health-promoting index (HPI) of cow's milk

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Thomas, Wendy
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Donald C. Beitz
Albert E. Freeman
Earl G. Hammond
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Biochemistry, Biophysics and Molecular Biology

The Department of Biochemistry, Biophysics, and Molecular Biology was founded to give students an understanding of life principles through the understanding of chemical and physical principles. Among these principles are frontiers of biotechnology such as metabolic networking, the structure of hormones and proteins, genomics, and the like.

The Department of Biochemistry and Biophysics was founded in 1959, and was administered by the College of Sciences and Humanities (later, College of Liberal Arts & Sciences). In 1979 it became co-administered by the Department of Agriculture (later, College of Agriculture and Life Sciences). In 1998 its name changed to the Department of Biochemistry, Biophysics, and Molecular Biology.

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  • Department of Biochemistry and Biophysics (1959–1998)

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Fourier transform infrared (FTIR) spectroscopy steadily has been gaining popularity for the analysis of milk components including total fat, protein, lactose, and ketones. To date, there have been few descriptions of the use of FTIR spectroscopy for the determination of milk fatty acid composition.;The first objective of this thesis was to develop a method utilizing FTIR spectroscopy for prediction of the health-promoting index (HPI) of milk. The HPI is known to affect the relative softness of butter (Bobe et al., 2003); so, this model could be used to predict which cows' milk could be designated for generation of niche products. To accomplish this objective, milk was collected from 281 cows for analysis. One set of samples was esterified into butyl esters for analysis via gas chromatography (GC), and the lipid was extracted from another set to analyze via FTIR spectroscopy. The GC-derived values and FTIR spectra were used to make predictive models by using the partial least squares (PLS) procedure of SAS. The models subsequently were used to generate predictions of milk composition by using FTIR spectra from three additional sets of 135 cows. The predictive model generated for HPI did not generate values for data not included in the predictive model satisfactorily (mean = 0266, root mean-squared error of prediction (RMSEP) = 0.122); so, predictive models were created for additional milk fatty acid combinations. The predictive models generated estimates for several milk composition parameters relatively well. For example, the model generated to determine the ratio of unsaturated to saturated fatty acids is able to predict with a mean = 0.347 and RMSEP = 0.096. With further development, the use of FTIR spectroscopy to determine milk fatty acid composition could become an essential part of milk analysis protocols.;The second objective of this study was to develop a method utilizing FTIR spectroscopy to determine fatty acid composition of milk that could be commercially marketed. At this time, this objective has not been achieved because the O-H stretching vibrations of water absorb nearly all of the photons present in the wavelengths at which the C-H and alkene bonds of fatty acids absorb energy. To counteract the interference of the O-H stretching vibrations at these wavelengths, it was necessary to remove water from raw milk samples before analysis. Several potential methods to eliminate water were investigated and a modification of the Folch method (Folch and Stanley, 1957) was chosen. The Folch method produces accurate and reproducible results (Avalli and Contarini, 2005, Zhang et al., 2008), but takes several hours per sample to complete as well as requiring the use of chloroform, which has multiple potential negative human health effects. Further investigation is needed to develop a method that will eliminate water from samples quickly and in a manner that does not pose risk to human health.;Key words: dairy cow, fatty acid composition, Fourier transform infrared spectroscopy, partial least squares analysis, health-promoting index

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Tue Jan 01 00:00:00 UTC 2008