Aquagrams of raw milk for oestrus detection in dairy cows.

The purpose of this research was to develop rapid and cost-effective method for oestrus detection in dairy cows by means of near infrared spectroscopy and aquaphotomics, using raw milk from individual cows. We found that aquaphotomics approach showed consistent specific water spectral pattern of milk at the oestrus periods of the investigated Holstein cows. Characteristic changes were detected especially in foremilk collected at morning milking. They were reflected in calculated aquagrams of milk spectra where distinctive spectral pattern of oestrus showed increased light absorbance of strongly hydrogen-bonded water. Results showed that monitoring of raw milk near infrared spectra provides an opportunity for analysing hormone levels indirectly, through the changes of water spectral pattern caused by complex physiological changes related to fertile periods.

On the feasibility of near infrared spectroscopy to detect contaminants in water using single salt solutions as model systems.

This research work evaluates the feasibility of NIRS to detect contaminants in water using single salt solutions as model systems. Previous research has indicated the potential of near infrared spectroscopy (NIRS) for detecting solutes in water; however, a comprehensive investigation of the limit of detection of this technique has not been carried out. Near infrared transmittance spectra of aqueous salt solutions in the concentration range 0.002-0.1 mol L(-1) (equivalent to 117-13,334 ppm or 0.0001-0.01% mass/mass) were investigated. The first overtone region of the near infrared spectrum (1300-1600 nm) was found to be the most effective wavelength range for prediction of salt concentration in aqueous solutions. Calibration models built using this wavelength range and employing the extended multiplicative scatter spectral pre-treatment resulted in root mean squared error of prediction values ranging from 0.004 to 0.01 mol L(-1). The limit of detection (LOD) was estimated to be of the order of 0.1% (mass/mass) or 1000 ppm. Within the framework of Aquaphotomics, it was possible to examine the effect of different salts on the NIR spectra of water in the first overtone range. Our results were confirmed through test experiments at various geographical locations employing dispersive and Fourier transform type NIRS instruments.

Characterisation of hydrogen bond perturbations in aqueous systems using aquaphotomics and multivariate curve resolution-alternating least squares.

Aquaphotomics is a new discipline that provides a framework for understanding changes in the structure of water caused by various perturbations, such as variations in temperature or the addition of solutes, using near infrared spectroscopy (NIRS). One of the main purposes of aquaphotomics is to identify water bands as main coordinates of future absorbance patterns to be used as biomarkers. These bands appear as consequence of perturbations in the NIR spectra. Curve resolution techniques may help to resolve and find new water bands or confirm already known bands. The aim of this study is to investigate the application of multivariate curve resolution-alternating least squares (MCR-ALS) to characterise the effects of various perturbations on the NIR spectra of water in terms of hydrogen bonding. For this purpose, the perturbations created by temperature change and the addition of four solutions of different ionic strength and Lewis acidity were studied (NaCl, KCl, MgCl(2) and AlCl(3), with concentrations ranging from 0.2 to 1 mol L(-1) in steps of 0.2 mol L(-1)). Transmission spectra of all salt solutions and pure water were obtained at temperatures ranging from 28 to 45°C. We have found that three distinct components with varying temperature dependence are present in water perturbed by temperature. The salt solutions studied exhibited similar trends with respect to the temperature perturbation, while the peak locations of their MCR-ALS pure components varied according to the ionic strength of the salt used.

Somatic cell count determination in cow's milk by near-infrared spectroscopy: a new diagnostic tool.

The potential of near-infrared spectroscopy (NIR) in the region from 1,100 to 2,500 nm to measure somatic cell count (SCC) content of cow's milk was investigated. A total of 196 milk samples from seven Holstein cows were collected for 28, consecutive days, starting from 7th d after calving, and analyzed for fat, protein, lactose, and SCC. Three of the cows were healthy, and the remainder had periods of mastitis during the experiment. Near-infrared transflectance milk spectra were obtained using an InfraAlyzer 500 spectrophotometer. The calibration for logSCC was performed using partial least square (PLS) regression and different spectral data pretreatment. The best accuracy of determination was found for an equation that was obtained using smoothed absorbance data and 10 PLS factors. The standard error of calibration was 0.361, the calibration coefficient of multiple correlation was 0.868, the standard error of prediction for independent validation set of samples was 0.382, the correlation coefficient was 0.854, and the coefficient of variation was 7.63%. The accuracy of logSCC determination by NIR spectroscopy would allow health screening of cows and differentiation between healthy and mastitic milk samples. It has been found that SCC determination by NIR milk spectra is based on the related changes in milk composition. The most significant factors that simultaneously influenced milk spectra with the elevation of SCC were alteration of milk proteins and changes in ionic concentration of milk.

Near infrared spectroscopy for biomonitoring: cow milk composition measurement in a spectral region from 1,100 to 2,400 nanometers.

The potential of near infrared spectroscopy (NIRS; 1,100 to 2,400 nm) to measure fat, total protein, and lactose content of nonhomogenized milk during milking and the influence of individual characteristics of each cow's milk on the accuracy of determination were studied. Milk fractions were taken during milking, twice per month, for 6 mo. Samples were taken every 2nd and 4th wk at the morning and the evening milkings. Teatcups were removed at each 3 L of milk yield as determined with a fractional sampling milk meter. A total of 260 milk samples were collected and analyzed with an NIRSystem 6500 spectrophotometer with 1-mm sample thickness. Partial least squares (PLS) regression was used to develop calibration models for the examined milk components. The comparison with the reference method was based on standard error of cross validation (SECV). The obtained SECV varied from .107 to .138% for fat content, from .092 to .125% for total protein, and from .066 to .096% for lactose content, and the accuracy of the reference method (AOAC, 1990, method No 972.16) was .05% for all measured milk components. The obtained models had lower SECV when an individual cow's spectral data were used for calibration. The reduction of SECV for each cow's individual calibration, when compared with SECV for the set of all samples, differed with the different constituents. For fat content determination, the reduction reached 22.46%, for protein 26.40%, and for lactose 31.25%. This phenomena was investigated and explained by principle component analysis (PCA) and by comparing loading of PLS factors that account for the most spectral variations for each cow and the measured milk components, respectively. The results of this study indicated that NIRS (1,100 to 2,500 nm, 1-mm sample thickness) was satisfactory for nonhomogenized milk compositional analysis of milk fractions taken in the process of milking.

Near-infrared spectroscopy for dairy management: measurement of unhomogenized milk composition.

The potential of near-infrared spectroscopy to measure fat, total protein, and lactose contents of unhomogenized milk was studied for use in dairy management, as a new tool for on-line milk analysis in the process of milking. Influence of the spectral region, sample thickness, and spectral data treatment on the accuracy of determination was investigated. Transmittance spectra of 258 milk samples, collected at different stages of the milking process, were obtained with a spectrophotometer (NIRSystems 6500; FOSS-NIRSystems, Silver Spring, MD) in the wavelength range from 400 to 2500 nm with sample thicknesses of 1 mm, 4 mm, and 10 mm. The spectral region and sample thickness were found to be significant factors for milk fat and total protein determination but not the lactose determination. The best accuracy was obtained with the 1100 to 2400 nm region, 1-mm sample thickness, and the first derivative data transformation. For the spectral region from 700 to 1100 nm, close accuracy was obtained for fat with a 10-mm sample and for total protein with a 1-mm sample thickness. The sample thickness did not change significantly the accuracy of lactose determination. Different treatments of spectral data did not improve the calibrations for fat and protein. For the region from 700 to 1100 nm, where inexpensive on-line sensors could be used, the highest positive coefficients for fat were at 930, 968, 990, 1026, 1076, and 1092 nm; for lactose were at 734, 750, 786, 812, 908, 974, 982, and 1064 nm; and for total protein were at 776, 880, 902, 952, and 1034 nm.