Multivariate prediction of clarified butter composition using raman spectroscopy

Abstract

Raman spectroscopy has been used to predict the abundance of the FA in clarified butterfat that was obtained from dairy cows fed a range of levels of rapeseed oil in their diet. Partial least squares regression of the Raman spectra against FA compositions obtained by GC showed good prediction for the five major (abundance >5%) FA with R2 = 0.74-0.92 and a root mean SE of prediction (RMSEP) that was 5-7% of the mean. In general, the prediction accuracy fell with decreasing abundance in the sample, but the RMSEP was <10% for all but one of the 10 FA present at levels >1.25%. The Raman method has the best prediction ability for unsaturated FA (R2 = 0.85-0.92), and in particular trans unsaturated FA (best-predicted FA was 18:1 t delta9). This enhancement was attributed to the isolation of the unsaturated modes from the saturated modes and the significantly higher spectral response of unsaturated bonds compared with saturated bonds. Raman spectra of the melted butter samples could also be used to predict bulk parameters calculated from standard analyzes, such as iodine value (R2 = 0.80) and solid fat content at low temperature (R2 = 0.87). For solid fat contents determined at higher temperatures, the prediction ability was significantly reduced (R2 = 0.42), and this decrease in performance was attributed to the smaller range of values in solid fat content at the higher temperatures. Finally, although the prediction errors for the abundances of each of the FA in a given sample are much larger with Raman than with full GC analysis, the accuracy is acceptably high for quality control applications. This, combined with the fact that Raman spectra can be obtained with no sample preparation and with 60-s data collection times, means that high-throughput, on-line Raman analysis of butter samples should be possible.

Fast and Minimally Invasive Determination of the Unsaturation Index of White Fat Depots by Micro‐Raman Spectroscopy

“…the paramount component of WAT, as revealed by the NMR measurements, which also were not able to detect any appreciable component of free fatty acids in it [31]. By the way, it is worth to mention that the intensity of the peak at 1,745 cm -1 is is taken as the reference to evaluate the molar parameters of fatty acids methyl esthers (FAME) by some authors [20,[43][44][45]. On the other hand, the intensity of this peaks cannot be properly adopted as the reference for the assessment of the UI of free fatty acids, for which the situation is much more complex due to the spectral intermixing of C=C and C=O stretching modes.…”

Raman spectroscopy of advanced glycation end products (AGEs), possible markers for progressive retinal dysfunction

“…50 For example, two strong bands between 1060 and 1130 cm 1 come from trans/gauche C-C stretching modes, while the presence of unsaturated bonds is revealed by the very characteristic strong bands at 1270 and 1662 cm 1 . 45,51 The high intensity of the band around 1660 cm 1 strongly suggests that this lipid is highly unsaturated. The presence of carbonyl modes at 1740 and 925 cm 1 confirms that the fatty acid is present in an ester form.…”

Effect of signal intensity normalization on the multivariate analysis of spectral data in complex ‘real‐world’ datasets

“…3 PLS regression coefficients for the prediction of pentosidine level. 4 Standard error of prediction of pentosidine level. 5 Sample variance for the prediction of pentosidine level.…”

“…In some cases the nature of the changes being investigated within a dataset lends itself to an obvious choice for internal standard. For example, when studying the molecular structure of fatty ester lipids, the ester group of the fatty acid chain [3,4] occurs in fixed numbers per fatty acid chain, making spectral bands related to this group ideal candidates for studying molar quantities. However, the middle section of the fatty acid chain is composed of a variable number of CH x groups, which ultimately determines the mass of the fatty acid chain.…”