Genetic correlations of milk fatty acid contents predicted from milk mid-infrared spectra in New Zealand dairy cattle.

The objective of this study was to estimate genetic correlations among milk fatty acid (FA) concentrations in New Zealand dairy cattle. Concentrations of each of the most common FA, expressed as a percentage of the total FA, were determined by gas chromatography on a specific cohort of animals. Using this data set, prediction equations were derived using mid-infrared (MIR) spectroscopy data collected from the same samples. These prediction equations were applied to a large data set of MIR measurements in 34,141 milk samples from 3,445 Holstein-Friesian, 2,935 Jersey, and 3,609 crossbred Holstein-Friesian × Jersey cows, sampled an average of 3.42 times during the 2007-2008 season. Data were analyzed using univariate and bivariate repeatability animal models. Heritability of predicted FA concentration in milk fat ranged from 0.21 to 0.42, indicating that genetic selection could be used to change the FA composition of milk. The de novo synthesized FA (C6:0, C8:0, C10:0, C12:0, and C14:0) showed strong positive genetic correlations with each other, ranging from 0.24 to 0.99. Saturated FA were negatively correlated with unsaturated (-0.93) and polyunsaturated (-0.84) FA. The saturated FA were positively correlated with milk fat yield and fat percentage, whereas the unsaturated FA were negatively associated with fat yield and fat percentage. Our results indicate that bovine milk FA composition can be changed through genetic selection using MIR as a phenotypic proxy.

Rapid, sensitive, and reproducible screening of liquid milk for adulterants using a portable Raman spectrometer and a simple, optimized sample well.

We have developed a powerful general spectroscopic method for rapidly screening liquid milk for adulterants by combining reflective focusing wells simply fabricated in aluminum with a small, portable Raman spectrometer with a focusing fiber optic probe. Hemispherical aluminum sample wells were specially designed to optimize internal reflection and sampling volume by matching the focal length of the mirror to the depth of focus of the laser probe. The technique was tested on milk adulterated with 4 different nitrogen-rich compounds (melamine, urea, dicyandiamide, and ammonium sulfate) and sucrose. No sample preparation of the milk was needed, and the total analysis time was 4min. Reliable sample presentation enabled average reproducibility of 8% residual standard deviation. The limit of detection interval measured from partial least squares calibrations ranged between 140 and 520mg/L for the 4 N-rich compounds and between 7,000 and 36,000mg/L (0.7-3.6%) for sucrose. The portability of the system and the reliability and reproducibility of this technique open opportunities for general, reagentless screening of milk for adulterants at the point of collection.

Raman spectroscopy as an effective screening method for detecting adulteration of milk with small nitrogen-rich molecules and sucrose.

Adulteration of milk for commercial gain is acknowledged as a serious issue facing the dairy industry. Several analytical techniques can be used to detect adulteration but they often require time-consuming sample preparation, expensive laboratory equipment, and highly skilled personnel. Here we show that Raman spectroscopy provides a simple, selective, and sensitive method for screening milk, specifically for small nitrogen-rich compounds, such as melamine, urea, ammonium sulfate, dicyandiamide, and for sucrose. Univariate and multivariate statistical methods were used to determine limits of detection and quantification from Raman spectra of milk spiked with 50 to 1,000 mg/L of the N-rich compounds and 0.25 to 4% sucrose. Partial least squares (PLS) calibration provided limit of detection minimum thresholds <200mg/L (0.02%) for the 4 N-rich compounds and <0.8% for sucrose, without the need for surface-enhanced Raman spectroscopy. The results show high reproducibility (7% residual standard deviation) and 100% efficiency for screening of milk for these adulterants.

Raman spectroscopic quantification of milk powder constituents.

Raman spectroscopy has significant potential for the quantification of food products. Milk powder is an important foodstuff and ingredient that is produced on large scale (over 20 million tonnes per annum). Raman spectroscopy, unlike near- and mid-infrared spectroscopies, has not been used extensively to quantify milk powder constituents. The effect of sample presentation on spectroscopic calibrations of protein and fat for 136 New Zealand milk powders was assessed using Raman spectroscopy. Prediction models were produced to quantify a protein concentration range of 32.19-37.65% w/w for skim milk powder, and a protein concentration range of 23.34-25.02% w/w and a fat concentration range of 26.26-29.68% w/w for whole milk powder (where ratios of prediction to deviation exceeded 2.6 with one exception). The resultant calibrations were not influenced by sample orientation; the sample temperature during data collection did affect the calibrations. Calcium fortification in the form of calcium carbonate was identified within a sub-set of samples, reinforcing the efficacy of Raman spectroscopy for identifying both crystalline and non-crystalline constituents within milk powder.

Raman spectroscopic prediction of the solid fat content of New Zealand anhydrous milk fat.

The functionality of anhydrous milk fat (AMF) is determined from solid fat content (SFC) and triacylglycerol (TG) profiles, parameters traditionally measured using nuclear magnetic resonance and high pressure liquid chromatography respectively. Raman spectroscopy coupled with partial least squares (PLS) analysis has been assessed as an alternative method for SFC and TG class quantification. Sample temperature at which the Raman spectra were collected, method of spectral preprocessing and type of PLS analysis were all investigated and found to significantly affect the resulting calibrations (as parameterized by root mean square error of cross validation). Physically heterogeneous AMF samples held at 20 °C were shown to allow reliable SFC predictions on the basis of collected Raman spectra. In contrast to SFC calibrations, physically homogenous samples in a liquid form were ideal for TG class concentration predictions, however, not all TG classes could be reliably predicted.