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.

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.

Haberlea rhodopensisis a resurrection plant with an extremely high desiccation tolerance. Even after long periods of almost full desiccation, its physiological functions are recovered shortly upon re-watering. In order to identify physiological strategies which contribute to its remarkable drought stress tolerance we used near infrared spectroscopy to investigate the state of water in the leaves of this plant and compared it to its relative, non-resurrection plant speciesDeinostigma eberhardtii. Here we show, using a novel aquaphotomics spectral analysis, thatH.rhodopensisperforms a dynamic regulation of water molecular structure during dehydration directed at drastic decrease of free water molecules, increase of water molecules with 4 hydrogen bonds, and a massive accumulation of water dimers in the full desiccation stage. Our findings suggest that changes in water structure mirror the changes in major metabolites and antioxidants which together constitute a robust defense system underlying the desiccation tolerance of the resurrection plant, while the water dimer may hold special importance for the “drying without dying” ability.

Food quality and safety, as well as bacteria identification, have become very important issues. Establishing fast and non-destructive methods for control is of a great importance. The performance and safety of processed milk and milk products are influenced by the quality of the raw milk used and animal health. Cell count in udder quarter milk has been established as the main criteria by which milk abnormality is evaluated and, in addition to electrical conductivity and pathogen identification, it is also a principle means for the diagnosis of the inflammatory udder disease known as mastitis. Near infrared (NIR) spectroscopy has proved to be a fast non-destructive method for the analysis of food and agricultural products, including non-homogenised milk. In this study, we have analysed NIR spectra of udder quarter milk samples collected continuously from individual cows, at various farms, at different times of the year. We report that NIR spectra of cows' udder quarter milk, when subjected to multivariate data analysis, provides information about milk abnormality and health disorders in cows. We have developed spectroscopic models for the simultaneous measurement of somatic cell count and electrical conductivity, as well as for identification of the main mastitis-causing bacterial pathogens in cow's udder quarter milk. These findings present NIR spectroscopy as a powerful technology for in vivo health monitoring, disease diagnosis at molecular level and bacteria identification.