Quantitative determination by temperature dependent near-infrared spectra: a further study

Water as a Probe for Standardization of Near-Infrared Spectra by Mutual-Individual Factor Analysis

The standardization of near-infrared (NIR) spectra is essential in practical applications, because various instruments are generally employed. However, standardization is challenging due to numerous perturbations, such as the instruments, testing environments, and sample compositions. In order to explain the spectral changes caused by the various perturbations, a two-step standardization technique was presented in this work called mutual–individual factor analysis (MIFA). Taking advantage of the sensitivity of a water probe to perturbations, the spectral information from a water spectral region was gradually divided into mutual and individual parts. With aquaphotomics expertise, it can be found that the mutual part described the overall spectral features among instruments, whereas the individual part depicted the difference of component structural changes in the sample caused by operation and the measurement conditions. Furthermore, the spectral difference was adjusted by the coefficients in both parts. The effectiveness of the method was assessed by using two NIR datasets of corn and wheat, respectively. The results showed that the standardized spectra can be successfully predicted by using the partial least squares (PLS) models developed with the spectra from the reference instrument. Consequently, the MIFA offers a viable solution to standardize the spectra obtained from several instruments when measurements are affected by multiple factors.

A novel aquaphotomics based approach for understanding salvianolic acid A conversion reaction with near infrared spectroscopy

As a fast and non-destructive detection method, near infrared spectroscopy, mainly containing overtones and combinations, can be used to quantify the components with a concentration of ≥ 1% in the analytical sample. Aquaphotomics uses the characteristic that the water structure changes with the addition of solute, which is reflected in the region of the water spectrum. Thus, it provides the possibility to unlock the information hidden in the spectrum. In our work, near infrared spectroscopy combined with aquaphotomics was used to quantify aqueous solution containing salvianolic acid B. It has shown that the aquaphotomics approach accurately quantifies the aqueous solution's salvianolic acid from 0.51 mg/mL to 25.86 mg/mL. The obtained RMSEP, R², RPD, and MRE of prediction were 0.52 mg/mL, 0.995, 14.88 and 4.74%, respectively. For the salvianolic acid A reaction solution, the predicted R² was 0.93, RMSEC was 0.85 mg/mL, and RMSEP was 0.82. The results of this study supported the concept of aquaphotomics, and the aquaphotomics approach was successfully applied in the reaction system of salvianolic acid A at 120 °C. This method was conducive to understanding the reaction and improving the accuracy of the quantitative model. It is a rapid and accurate alternative for analysis and measurement of transformation reactions at high temperature and high pressure, even for the substance with a concentration of less than 5 mg/mL.

Revealing the interactions of water with cryoprotectant and protein by near-infrared spectroscopy

Taking formamide (FA) as a model compound of protein, the water structure in the ternary mixtures of dimethyl sulfoxide (DMSO)-water-FA was studied by near-infrared (NIR) spectroscopy. The interaction of DMSO and water, and the effect of FA on the interaction, were analyzed with the help of chemometric methods. Continuous wavelet transform (CWT) was used to enhance the resolution of the spectra. A peak at 6437 cm^-1 depicting the interaction of DMSO and water through hydrogen bonding (SO…HO) was observed in the transformed spectra. When FA exists in the mixture, the intensity of the peak decreases with the increase of formamide content, showing that FA may replace the water to form the hydrogen bond of SO and HN. In addition, temperature-dependent NIR spectroscopy was used to analyze the effect of the three components on the spectral variation with temperature. Analyzing the spectral data by alternating trilinear decomposition (ATLD) and multiple linear regression, two varying spectral features were obtained that are related to water and DMSO, but no spectral feature was found that significantly varies with the content of FA. The result implies that DMSO is still the key component to prevent the water from icing, although FA may reduce slightly the anti-freezing effect.

Chemometrics: An Excavator in Temperature-Dependent Near-Infrared Spectroscopy

Temperature-dependent near-infrared (NIR) spectroscopy has been developed and taken as a powerful technique for analyzing the structure of water and the interactions in aqueous systems. Due to the overlapping of the peaks in NIR spectra, it is difficult to obtain the spectral features showing the structures and interactions. Chemometrics, therefore, is adopted to improve the spectral resolution and extract spectral information from the temperature-dependent NIR spectra for structural and quantitative analysis. In this review, works on chemometric studies for analyzing temperature-dependent NIR spectra were summarized. The temperature-induced spectral features of water structures can be extracted from the spectra with the help of chemometrics. Using the spectral variation of water with the temperature, the structural changes of small molecules, proteins, thermo-responsive polymers, and their interactions with water in aqueous solutions can be demonstrated. Furthermore, quantitative models between the spectra and the temperature or concentration can be established using the spectral variations of water and applied to determine the compositions in aqueous mixtures.

Multilevel LASSO-based NIR temperature-correction modeling for viscosity measurement of bisphenol-A

Temperature variation will affect the prediction accuracy when using the near-infrared (NIR) analytical model to measure the viscosity of bisphenol-A. In order to correct the effect of temperature on the prediction performance of NIR model, a multilevel least-absolute shrinkage and selection operator (LASSO) is proposed in this paper. The multilevel LASSO algorithm combines LASSO with the multilevel simultaneous component analysis (MLSCA) to enhance the robustness of the model under temperature changes and external disturbances. MLSCA is applied to decompose the molecular spectral data into two parts. One part denotes the property caused by temperature, the other means the changes of concentration. LASSO, a sparse regression model, is used to select the variables and perform the regularization to further enhance the robustness and interpretability of the model. Experimental results demonstrate the effectiveness of the proposed model in measuring bisphenol-A viscosity, which provides a more stable prediction result compared with the existing ones without temperature corrections.

Three-level simultaneous component analysis for analyzing the near-infrared spectra of aqueous solutions under multiple perturbations

Quantitative analysis under various perturbations is a difficult problem because the analytical signal changes with different factors. In this work, three-level simultaneous component analysis (3-MSCA) was used for analyzing the near-infrared (NIR) spectra of aqueous solutions under different perturbations. The spectral data of aqueous proline solutions at different pH, concentration and temperature were measured, and a three-level model was built to describe the effects of the three perturbations on the spectra, respectively. The first level model describes the change of the spectra with pH, from which significant aggregation of proline was observed around the isoelectric point. The second and third level model show the spectral change with concentration and temperature, respectively, and the spectral feature has a very good linear relationship with the corresponding influencing factors. Therefore, the pH and concentration scores can be used as the calibration curve for quantitative analysis of the pH and the content of proline, and the temperature scores can be used to predict the temperature of the solutions. In addition, the structural change of water molecules under different conditions is obtained from the loadings. A decline of the bulk water was found with the increase of concentration, implying an ascending trend of the bonded water due to the interaction of proline and water. The dissociation of water clusters with the increase of temperature is also displayed.

Aquaphotomics-From Innovative Knowledge to Integrative Platform in Science and Technology

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.

Understanding the role of water in the aggregation of poly(N,N-dimethylaminoethyl methacrylate) in aqueous solution using temperature-dependent near-infrared spectroscopy

For understanding the role of water in the aggregation of polymers, the variation of water structures with the structural change of polymers in the process of aggregation was studied by temperature-dependent near-infrared (NIR) spectroscopy. The NIR spectra of the aqueous poly(N,N-dimethylaminoethyl methacrylate) (PDMAEMA) solutions of different concentrations were measured at different temperatures. The spectral changes of the polymer and water with temperature were analyzed by N-way principal component analysis (NPCA). It was found that, at low concentration, the chains of the polymer tend to form a loose hydrophobic structure below 36 °C and then aggregate into a micelle at a lower critical solution temperature (LCST) of around 39 °C. In the process of the aggregation, the water species with two hydrogen bonds (S2) increases gradually before 36 °C and then a sudden decrease occurs after that temperature. The results clearly indicate that water species S2 plays an important role in the formation of the intermediate, i.e., the loose hydrophobic structure of the polymer chains linked by the two hydrogen bonds of S2 water. When the temperature increases, the dissociation of the hydrogen bonds enables the intermediate to be destroyed to form a micelle structure. For the high concentration solution, however, the spectral information of S2 was not found in the aggregation, suggesting direct formation of the micelle from the dehydrated chains.

Understanding the Interaction Between Oligopeptide and Water in Aqueous Solution Using Temperature-Dependent Near-Infrared Spectroscopy

Investigating the interaction between oligopeptide and water is essential for understanding the structure, dynamics and function of proteins. Temperature-dependent near-infrared (NIR) spectroscopy and independent component analysis (ICA) were employed to study the interaction between oligopeptide and water in aqueous solution. The NIR spectra of two homo-oligopeptides, penta-aspartic acid (D₅) and penta-lysine (K₅), in aqueous solution of different concentration were measured at different temperature (30-90 ℃). Independent component analysis was performed to extract the spectral information that changes with temperature. The independent components (ICs) representing the spectral information of NH and CH₂ groups were obtained. Compared with D₅, the two groups in K₅ change significantly at higher temperature. The result may suggest that K₅ has stronger interaction with water than D₅. Moreover, three ICs that contain the spectral information of the water species with no (S₀), one (S₁), and two (S₂) hydrogen-bonds were obtained. It was shown that the spectral intensity of S₀ and S₁ increases while that of S₂ decreases with the temperature, and the changes of oligopeptide solutions are weaker than those of pure water. The results indicate that water structure is sensitive to temperature and the oligopeptide in aqueous solution improves the thermal stability of the water species. When oligopeptide is added, the spectral intensity of S₀ and S₂ decreases and that of S₁ increases for D₅ solution, but the intensity of all the three species decreases for K₅ solution. Furthermore, the concentration effect of K₅ was found to be stronger than D₅. The result may reveal that D₅ combines with water molecule through forming one hydrogen bond but K₅ interacts with water through a different way.

Essentials of Aquaphotomics and Its Chemometrics Approaches

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.

Understanding the function of water during the gelation of globular proteins by temperature-dependent near infrared spectroscopy

Water plays an indispensable role in the gelation of proteins, but its function still remains unclear. In this work, the variation of water species with the structural changes of globular proteins was investigated using temperature-dependent near infrared (NIR) spectroscopy. Ovalbumin (OVA) was used as a model protein, which forms a gel-like structure as the temperature increases through three phases, i.e., phase I (native), phase II (molten globule state), and phase III (gel state). The structural change and the content variation of different water species in the three phases of gelation were analyzed by two-dimensional correlation NIR spectroscopy and Gaussian fitting. A decrease in the water species with two hydrogen bonds (S2) was found and the change follows the same phases as OVA. In the first two phases, the change occurs after those of other water species but in the third phase, the change is faster than that of free water species. The result indicates that in the native and molten globule states, S2 is located in the hydration shell of OVA to maintain the stability of the protein structure, and then in the gel state, high temperature weakens the hydrogen bonding of S2 and leads to the destruction of the hydration shell, making OVA clusters form a gel structure.

Mutual factor analysis for quantitative analysis by temperature dependent near infrared spectra

Temperature dependent near infrared (NIR) spectroscopy has been developed for analyzing multi-component mixtures and understanding the molecular interactions in solutions. In this work, a chemometric method named as mutual factor analysis (MFA) was proposed for the analysis of temperature dependent NIR spectra. The method extracts the common spectral feature contained in the spectra of different temperature or different concentration. The relative quantity of the extracted spectral feature is proportional to the temperature or concentration. From the spectra of water-glucose mixtures, both the spectral variations induced by temperature and concentration are obtained and the variations are correlated with the inducements, respectively, in a very good linearity. Serum samples were used for validation of the method. An acceptable calibration model with a good correlation coefficient (R² = 0.8639) was obtained for glucose measurement. The relative deviations of the measured concentrations from the calibration model are in the range of -18.7-8.52%, which are in a reasonable level for clinical uses. More importantly, the calculations are based on the spectral information of water that has interactions with the analyte. This provides a new way for quantitative analyses of bio-systems.

Quantitative determination based on the differences between spectra-temperature relationships

In the Near-infrared (NIR) spectral measurement it is not always possible to keep the experimental conditions constant. The fluctuations in external variables, such as temperature, will result in a nonlinear shift and a broadening of the spectral bands. In this study, the temperature-induced spectral variation coefficient (TSVC) was obtained by using loading space standardization (LSS). The relationship between TSVC and normalized squared temperature was quantitatively analyzed and applied to the quantitative determination of the compositions in mixtures. NIR spectra of peanut-soy-corn oil mixtures measured at seven temperatures were analyzed. It was found that, the relationship between TSVC and normalized squared temperature can be established by using LSS. Furthermore, the quantitative determination of the compositions in a mixture can be achieved by using the difference between the relationships, i.e., the slope of the relationship. The calibration curves between slope and composition volume are found to be reliable with the correlation coefficients (R(2)) as high as 0.9992. Quantitative determination by the calibration curves were also validated. Therefore, the method can be an effective tool for investigating the effect of temperature and quantitatively analysis.

Glucose induced variation of water structure from temperature dependent near infrared spectra

The different effects of glucose on water species provide evidence to explain the bioprotective function of carbohydrates in aqueous solutions.