Why near infrared spectroscopy? Molecular structures have been investigated with vibrational infrared (Ir) and the respective vis-near infrared (nIr) overtone spectroscopy. Water is a strong absorber of Ir energy (figure 1) 16 and, as a result, this method is only suited to analysing small or very thin samples. therefore, it is difficult to use it for non-destructive real-time dynamic studies of

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.

Heat-induced denaturation of ovalbumin in aqueous solutions has been investigated by generalized two-dimensional (2D) Fourier transform near-infrared (FT-NIR) correlation spectroscopy. New insight has been gained into hydration and the unfolding process of secondary structures of ovalbumin by studying temperature-dependent correlation patterns in 2D synchronous and asynchronous spectra, which are constructed from concentration-perturbed NIR spectra at different temperatures. The correlation patterns have provided information about the correlation and phase relationships between different absorption bands of ovalbumin and water. The hydration of ovalbumin is almost unchanged from 45 to 67 °C, where ovalbumin molecules are in a natively folded state. A sudden change in the hydration is detected in a narrow temperature range of 67−69 °C, where the unfolding of the ordered secondary structures starts. The hydration, again, remains nearly unchanged upon further heating to 80 °C, even though the unfolding process develops progressively until the denatured state. The sudden change in the hydration around 68 °C seems to be caused by the stabilization of slightly unstable hydrogen bonds in the folded state. The change may make the intramolecular hydrophobic cores of ovalbumin less condensed and more accessible to the solvent molecules. On the other hand, the development of unfolding from 69 to 80 °C results in band shifts for combination bands involving free NH stretching−amide II (amide A/II), intramolecular hydrogen-bonded NH stretching−amide II (amide B/II) of ovalbumin. The present experiment demonstrates that the generalized 2D NIR correlation spectroscopy is powerful in detecting subtle but valuable structural information about the protein denaturation in the aqueous solution.

Aquaphotomics is a novel scientific discipline involving the study of water and aqueous systems. Using light-water interaction, it aims to extract information about the structure of water, composed of many different water molecular conformations using their absorbance bands. In aquaphotomics analysis, specific water structures (presented as water absorbance patterns) are related to their resulting functions in the aqueous systems studied, thereby building an aquaphotome—a database of water absorbance bands and patterns correlating specific water structures to their specific functions. Light-water interaction spectroscopic methods produce complex multidimensional spectral data, which require data processing and analysis to extract hidden information about the structure of water presented by its absorbance bands. The process of extracting information from water spectra in aquaphotomics requires a field–specific approach. It starts with an appropriate experimental design and execution to ensure high-quality spectral signals, followed by a multitude of spectral analysis, preprocessing and chemometrics methods to remove unwanted influences and extract water absorbance spectral pattern related to the perturbation of interest through the identification of activated water absorbance bands found among the common, consistently repeating and highly influential variables in all analytical models. The objective of this paper is to introduce the field of aquaphotomics and describe aquaphotomics multivariate analysis methodology developed during the last decade. Through a worked-out example of analysis of potassium chloride solutions supported by similar approaches from the existing aquaphotomics literature, the provided instruction should give enough information about aquaphotomics analysis i.e. to design and perform the experiment and data analysis as well as to represent water absorbance spectral pattern using various forms of aquagrams—specifically designed aquaphotomics graphs. The explained methodology is derived from analysis of near infrared spectral data of aqueous systems and will offer a useful and new tool for extracting data from informationally rich water spectra in any region. It is the hope of the authors that with this new tool at the disposal of scientists and chemometricians, pharmaceutical and biomedical spectroscopy will substantially progress beyond its state-of-the-art applications.

Aquaphotomics is a young scientific discipline based on innovative knowledge of water molecular network, which as an intrinsic part of every aqueous system is being shaped by all of its components and the properties of the environment. With a high capacity for hydrogen bonding, water molecules are extremely sensitive to any changes the system undergoes. In highly aqueous systems—especially biological—water is the most abundant molecule. Minute changes in system elements or surroundings affect multitude of water molecules, causing rearrangements of water molecular network. Using light of various frequencies as a probe, the specifics of water structure can be extracted from the water spectrum, indirectly providing information about all the internal and external elements influencing the system. The water spectral pattern hence becomes an integrative descriptor of the system state. Aquaphotomics and the new knowledge of water originated from the field of near infrared spectroscopy. This technique resulted in significant findings about water structure-function relationships in various systems contributing to a better understanding of basic life phenomena. From this foundation, aquaphotomics started integration with other disciplines into systematized science from which a variety of applications ensued. This review will present the basics of this emerging science and its technological potential.

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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 (NIRS) has been successfully used for non-invasive diagnosis of diseases and abnormalities where water spectral patterns are found to play an important role. The present study investigates water absorbance patterns indicative of estrus in the female giant panda. NIR spectra of urine samples were acquired from the same animal on a daily basis over three consecutive putative estrus periods. Characteristic water absorbance patterns based on 12 specific water absorbance bands were discovered, which displayed high urine spectral variation, suggesting that hydrogen-bonded water structures increase with estrus. Regression analysis of urine spectra and spectra of estrone-3-glucuronide standard concentrations at these water bands showed high correlation with estrogen levels. Cluster analysis of urine spectra grouped together estrus samples from different years. These results open a new avenue for using water structure as a molecular mirror for fast estrus detection.