Water confined in the local field of ions

Review - Plant nutritional status analysis employing the visible and near-infrared spectroscopy spectral sensor

Experiments demonstrated that visible and near-infrared (Vis-NIR) spectroscopy is a highly reliable tool for determining the nutritional status of plants. Although numerous studies on various kinds of plants have been conducted, there are only a few summaries of the research findings regarding the absorbance bands in the visible and near-infrared region and how they relate to the nutritional status of plants. This article will discuss the application of Vis-NIR spectroscopy for monitoring the nutrient conditions of plants, with a particular emphasis on three major components required by plants, namely nitrogen (N), phosphorus (P), and potassium (K), or NPK. Each section discussed different topics, for instance, the essential nutrients needed by plants, the application of Vis-NIR spectroscopy in nutrient status analysis, chemometrics tools, and absorbance bands related to the nutrient status, respectively. Deduction made concluded that factors affecting the plant's structure are contributed by several circumstances like the age of leaves, concentration of pigments, and water content. These factors are intertwined, strongly correlated, and can be observed in the visible and near-infrared regions. While the visible region is commonly utilised for nutritional analysis in plants, the literature review performed in this paper shows that the near-infrared region as well contains valuable information about the plant's nutritional status. A few wavelengths related to the direct estimation of nutrients in this review explained that information on nutrients can be linked with chlorophyll and water absorption bands such that N and P are the components of chlorophyll and protein; on the other hand, K exists in the form of cationic carbohydrates which are sensitive to water region.

The Use of a Droplet Collar Accessory Attached to a Portable near Infrared Instrument to Identify Methanol Contamination in Whisky

The aim of this study was to evaluate the ability of a droplet collar accessory attached to a portable near-infrared (NIR) instrument to characterize the artificial contamination of methanol in commercial whisky samples. Unadulterated samples (n = 12) were purchased from local bottle shops where adulterated samples were created by adding methanol (99% pure methanol) at six levels (0.5%, 1%, 2%, 3%, 4% and 5% v/v) to the commercial whisky samples (controls). Samples were analyzed using a drop collar accessory attached to a MicroNIR Onsite instrument (900-1650 nm). Partial least squares (PLS) cross-validation statistics obtained for the prediction of all levels of methanol (from 0 to 5%) addition were considered adequate when the whole adulteration range was used, coefficient of determination in cross-validation (R2cv: 0.95) and standard error in cross of validation (SECV: 0.35% v/v). The cross-validation statistics were R2cv: 0.97, SECV: 0.28% v/v after the 0.5% and 1% v/v methanol addition was removed. These results showed the ability of using a new sample presentation attachment to a portable NIR instrument to analyze the adulteration of whisky with methanol. However, the low levels of methanol adulteration (0.5 and 1%) were not well predicted using the NIR method evaluated.

Fast-Training Deep Learning Algorithm for Multiplex Quantification of Mammalian Bioproduction Metabolites via Contactless Short-Wave Infrared Hyperspectral Sensing

Within the biopharmaceutical sector, there exists the need for a contactless multiplex sensor, which can accurately detect metabolite levels in real time for precise feedback control of a bioreactor environment. Reported spectral sensors in the literature only work when fully submerged in the bioreactor and are subject to probe fouling due to a cell debris buildup. The use of a short-wave infrared (SWIR) hyperspectral (HS) cam era allows for efficient, fully contactless collection of large spectral datasets for metabolite quantification. Here, we report the development of an interpretable deep learning system, a convolution metabolite regression (CMR) approach that detects glucose and lactate concentrations using label-free contactless HS images of cell-free spent media samples from Chinese hamster ovary (CHO) cell growth flasks. Using a dataset of <500 HS images, these CMR algorithms achieved a competitive test root-mean-square error (RMSE) performance of glucose quantification within 27 mg/dL and lactate quantification within 20 mg/dL. Conventional Raman spectroscopy probes report a validation performance of 26 and 18 mg/dL for glucose and lactate, respectively. The CMR system trains within 10 epochs and uses a convolution encoder with a sparse bottleneck regression layer to pick the best-performing filters learned by CMR. Each of these filters is combined with existing interpretable models to produce a metabolite sensing system that automatically removes spurious predictions. Collectively, this work will advance the safe and efficient adoption of contactless deep learning sensing systems for fine control of a variety of bioreactor environments.

Aquaphotomics Monitoring of Lettuce Freshness during Cold Storage

Fresh-cut leafy vegetables are one of the most perishable products because they readily deteriorate in quality even during cold storage and have a relatively short shelf life. Since these products are in high demand, methods for rigorous quality control and estimation of freshness that are rapid and non-destructive would be highly desirable. The objective of the present research was to develop a rapid, non-destructive near-infrared spectroscopy (NIRS)-based method for the evaluation of changes during cold storage of lettuce using an aquaphotomics approach to monitor the water molecular structure in lettuce leaves. The reference measurements showed that after 6 days of dark, cold storage, the weight and water activity of lettuce leaves decreased and β-carotene decreased, while chlorophylls slightly increased. Aquaphotomics characterization showed large differences in the lettuce leaves' spectra depending on their growth zone. Difference spectra, principal component analysis (PCA) and linear discriminant analysis (LDA) confirmed the differences in the inner and outer leaves and revealed that spectra change as a function of storage time. Partial least squares regression (PLSR) allowed the prediction of the time spent in storage with a coefficient of determination of R² = 0.80 and standard error of RMSE = 0.77 days for inner, and R² = 0.86 and RMSE = 0.66 days for outer leaves, respectively. The following water absorbance bands were found to provide the most information in the spectra: 1348, 1360, 1373, 1385, 1391, 1410, 1416, 1422, 1441, 1447, 1453, 1466, 1472, 1490, 1503, 1515, 1521, 1534 and 1571 nm. They were further used as water matrix coordinates (WAMACs) to define the water spectral patterns (WASPs) of lettuce leaves. The WASPs of leaves served to succinctly describe the state of lettuces during storage. The changes in WASPs during storage reveled moisture loss, damage to cell walls and expulsion of intracellular water, as well as loss of free and weakly hydrogen-bonded water, all leading to a loss of juiciness. The WASPs also showed that damage stimulated the defense mechanisms and production of vitamin C. The leaves at the end of the storage period were characterized by water strongly bound to collapsed structural elements of leaf tissues, mainly cellulose, leading to a loss of firmness that was more pronounced in the outer leaves. All of this information was reflected in the changes of absorbance in the identified WAMACs, showing that the water molecular structure of lettuce leaves accurately reflects the state of the lettuce during storage and that WASPs can be used as a multidimensional biomarker to monitor changes during storage.

Aquaphotomics monitoring of strawberry fruit during cold storage - A comparison of two cooling systems

The objective of this study was to use aquaphotomics and near-infrared (NIR) spectroscopy to follow the changes in strawberries during cold storage in the refrigerator with an electric field generator (supercooling fridge, SCF) and without it (control fridge, CF). The NIR spectra of strawberries stored in these refrigerators were collected over the course of 15 days using a portable mini spectrometer and their weight was measured daily. The spectral data in the region of the first overtone of water (1,300-1,600 nm) were analyzed using aquaphotomics multivariate analysis. The results showed a decrease in weight loss of strawberries, but the loss of weight was significantly lower in SCF, compared to the CF. The reduction of weight loss due to exposure to an electric field was comparable to the use of coatings. The aquaphotomics analysis showed that the NIR spectra adequately captured changes in the fruit over the storage period, and that it is possible to predict how long the fruit spent in storage, regardless of the storage type. During aquaphotomics analysis, 19 water absorbance bands were found to be consistently repeating and to have importance for the description of changes in strawberries during cold storage. These bands defined the water spectral pattern (WASP), multidimensional biomarker that was used for the description of the state and dynamics of water in strawberries during time spent in storage. Comparison of WASPs of strawberries in CF and SCF showed that exposure to an electric field leads to a delay in ripening by around 3 days. This was evidenced by the increased amount of structural, strongly bound water and vapor-like trapped water in the strawberries stored in SCF. This particular state of water in strawberries stored in SCF was related to the hardening of the strawberry skin and prevention of moisture loss, in agreement with the results of significantly decreased weight loss.

Aquaphotomic Study of Effects of Different Mixing Waters on the Properties of Cement Mortar

The mixing water used for cement concrete has a significant effect on the physical properties of the material after hardening; however, other than the upper limit for the mixed impurities, not enough consideration has been given to the functions and characteristics of water at the molecular level. In this study, we investigated the effect of four different types of water (two spring-, mineral waters, tap water and distilled water) on the drying shrinkage of the hardened cement by comparing the material properties of the concrete specimens and analyzing the molecular structure of the water and cement mortar using aquaphotomics. The near infrared (NIR) spectra of waters used for mixing were acquired in the transmittance mode using a high-precision, high-accuracy benchtop spectrometer in the range of 400-2500 nm, with the 0.5 nm step. The NIR spectra of cement paste and mortar were measured in 6.2 nm increments in the wavelength range of 950 nm to 1650 nm using a portable spectrometer. The measurements of cement paste and mortar were performed on Day 0 (immediately after mixing, cement paste), 1 day, 3 days, 7 days, and 28 days after mixing (cement mortar). The spectral data were analyzed according to the aquaphotomics' multivariate analysis protocol, which involved exploration of raw and preprocessed spectra, exploratory analysis, discriminating analysis and aquagrams. The results of the aquaphotomics' analysis were interpreted together with the results of thermal and drying shrinkage measurements. Together, the findings clearly demonstrated that the thermal and drying shrinkage properties of the hardened cement material differed depending on the water used. Better mechanical properties were found to be a result of using mineral waters for cement mixing despite minute differences in the chemical content. In addition, the aquaphotomic characterization of the molecular structure of waters and cement mortar during the initial hydration reaction demonstrated the possibility to predict the characteristics of hardened cement at a very early stage. This provided the rationale to propose a novel evaluation method based on aquaphotomics for non-invasive evaluation and monitoring of cement mortar.

Aquaphotomics for monitoring of groundwater using short-wavelength near-infrared spectroscopy

Water spectrum of any aqueous system contains information about OH covalent and hydrogen bonds that are highly influenced by the environment and the rest of the molecules in the system. When aquaphotomics is used to analyze the water near infrared (NIR) spectra, the information about the water molecular structure can be obtained as a function of internal and external factors. The objective of this research is to apply aquaphotomics analysis to evaluate different groundwaters by using their NIR unique spectral pattern, robust to external influences of temperature and humidity, that can potentially be used for water type identification and screening practice. Two groundwaters obtained at different depths and their mixture, differing in mineral content and molecular structure were monitored on a daily basis using portable visible/NIR (vis/NIR) spectrometer during three consecutive years. The spectra were pre-processed by smoothing and multiplicative scatter correction (MSC) to remove noise and baseline effects. Results showed that NIR spectral patterns of groundwater samples were affected by changes in environmental factors - temperature, humidity, time and others. The water absorbance bands which are highly influenced by humidity and temperature in short wavelength NIR region were identified. Their avoidance resulted in obtaining consistent spectral patterns during the entire monitoring period, unique for each groundwater, that can be used as its fingerprint and monitored over time. Consistency and uniqueness of the spectral pattern for each groundwater provide a potential to use the deviation of spectral pattern as an indicator of changes in the water. These results confirm that vis/NIR spectral pattern can be used as an integrative marker of water status, stable over time, providing the basis for an efficient cost-effective method for monitoring of water functionality.

Pilot Aquaphotomic Study of the Effects of Audible Sound on Water Molecular Structure

Sound affects the medium it propagates through and studies on biological systems have shown various properties arising from this phenomenon. As a compressible media and a “collective mirror”, water is influenced by all internal and external influences, changing its molecular structure accordingly. The water molecular structure and its changes can be observed as a whole by measuring its electromagnetic (EMG) spectrum. Using near-infrared spectroscopy and aquaphotomics, this pilot study aimed to better describe and understand the sound-water interaction. Results on purified and mineral waters reported similar effects from the applied 432 Hz and 440 Hz frequency sound, where significant reduction in spectral variations and increased stability in water were shown after the sound perturbation. In general, the sound rearranged the initial water molecular conformations, changing the samples’ properties by increasing strongly bound, ice-like water and decreasing small water clusters and solvation shells. Even though there was only 8 Hz difference in applied sound frequencies, the change of absorbance at water absorbance bands was specific for each frequency and also water-type-dependent. This also means that sound could be effectively used as a perturbation tool together with spectroscopy to identify the type of bio, or aqueous, samples being tested, as well as to identify and even change water functionality.

Aquaphotomics Research of Cold Stress in Soybean Cultivars with Different Stress Tolerance Ability: Early Detection of Cold Stress Response

The development of non-destructive methods for early detection of cold stress of plants and the identification of cold-tolerant cultivars is highly needed in crop breeding programs. Current methods are either destructive, time-consuming or imprecise. In this study, soybean leaves' spectra were acquired in the near infrared (NIR) range (588-1025 nm) from five cultivars genetically engineered to have different levels of cold stress tolerance. The spectra were acquired at the optimal growing temperature 27 °C and when the temperature was decreased to 22 °C. In this paper, we report the results of the aquaphotomics analysis performed with the objective of understanding the role of the water molecular system in the early cold stress response of all cultivars. The raw spectra and the results of Principal Component Analysis, Soft Independent Modeling of Class Analogies and aquagrams showed consistent evidence of huge differences in the NIR spectral profiles of all cultivars under normal and mild cold stress conditions. The SIMCA discrimination between the plants before and after stress was achieved with 100% accuracy. The interpretation of spectral patterns before and after cold stress revealed major changes in the water molecular structure of the soybean leaves, altered carbohydrate and oxidative metabolism. Specific water molecular structures in the leaves of soybean cultivars were found to be highly sensitive to the temperature, showing their crucial role in the cold stress response. The results also indicated the existence of differences in the cold stress response of different cultivars, which will be a topic of further research.

Analysing the water spectral pattern by near-infrared spectroscopy and chemometrics as a dynamic multidimensional biomarker in preservation: rice germ storage monitoring

Water activity is an important phenomenon not yet explained in terms of water molecular structure. This paper aims to find the relationship between the water activity and water molecular structure of the rice germ, based on its spectral pattern which can be measured using non-destructive technology. Aquaphotomics near-infrared spectroscopy was used to study rice germ stored at different levels of water activity and atmosphere. The findings show that state of the rice germ is governed by the water activity upon storage, which is defined by the structure of water within germ matrix. The structure of water can be described solely by the absorbance spectral pattern at the following absorbance bands: proton hydrates, hydration shells and water vapor (1364, 1375 and 1382 nm), trapped water (1392 nm), free water (1410 nm), hydration water (1425 nm), adsorbed water (1455 nm), non-bonded hydroxyl (1436 nm) and bound water (1520 nm).

Aquaphotomics Reveals Subtle Differences between Natural Mineral, Processed and Aged Water Using Temperature Perturbation Near-Infrared Spectroscopy

Current approaches to the quality control of water are unsatisfying due to either a high cost or the inability to capture all of the relevant information. In this study, near-infrared spectroscopy (NIRS) with aquaphotomics as a novel approach was assessed for the discrimination of natural, processed and aged water samples. Temperature perturbation of water samples was employed to probe the aqueous systems and reveal the hidden information. A radar chart named an aquagram was used to visualize and compare the absorbance spectral patterns of waters at different temperatures. For the spectra acquired at a constant temperature of 30 °C, the discrimination analysis of different water samples failed to produce satisfying results. However, under perturbation by increasing the temperature from 35 to 60 °C, the absorbance spectral pattern of different waters displayed in aquagrams revealed different, water-specific dynamics. Moreover, it was found that aged processed water changed with the temperature, whereas the same processed water, when freshly prepared, had hydrogen bonded structures unperturbed by temperature. In summary, the aquaphotomics approach to the NIRS analysis showed that the water absorbance spectral pattern can be used to describe the character and monitor dynamics of each water sample as a complex molecular system, whose behavior under temperature perturbation can reveal even subtle changes, such as aging and the loss of certain qualities during storage.

Research on the Structure of Peanut Allergen Protein Ara h1 Based on Aquaphotomics

Peanut allergy is becoming a life-threatening disease that could induce severe allergic reactions in modern society, especially for children. The most promising method applied for deallergization is heating pretreatment. However, the mechanism from the view of spectroscopy has not been illustrated. In this study, near-infrared spectroscopy (NIRS) combined with aquaphotomics was introduced to help us understand the detailed structural changes information during the heating process. First, near-infrared (NIR) spectra of Ara h1 were acquired from 25 to 80°C. Then, aquaphotomics processing tools including principal component analysis (PCA), continuous wavelet transform (CWT), and two-dimensional correlation spectroscopy (2D-COS) were utilized for better understanding the thermodynamic changes, secondary structure, and the hydrogen bond network of Ara h1. The results indicated that about 55°C could be a key temperature, which was the structural change point. During the heating process, the hydrogen bond network was destroyed, free water was increased, and the content of protein secondary structure was changed. Moreover, it could reveal the interaction between the water structure and Ara h1 from the perspective of water molecules, and explain the effect of temperature on the Ara h1 structure and hydrogen-bonding system. Thus, this study described a new way to explore the thermodynamic properties of Ara h1 from the perspective of spectroscopy and laid a theoretical foundation for the application of temperature-desensitized protein products.

Relating Near-Infrared Light Path-Length Modifications to the Water Content of Scattering Media in Near-Infrared Spectroscopy: Toward a New Bouguer-Beer-Lambert Law

In near-infrared spectroscopy (NIRS), the linear relationship between absorbance and an absorbing compound concentration has been strictly defined by the Bouguer-Beer-Lambert law only for the case of transmission measurements of nonscattering media. However, various quantitative calibrations have been successfully built both on reflectance measurements and for scattering media. Although the lack of linearity for scattering media has been observed experimentally, the sound multivariate statistics and signal processing involved in chemometrics have allowed us to overcome this problem in most cases. However, in the case of samples with varying water content, important modifications of scattering levels still make calibrations difficult to build due to nonlinearities. Moreover, even when calibration procedures are successfully developed, many preprocessing methods used do not guarantee correct spectroscopic assignments (in the sense of a pure chemical absorbance). In particular, this may prevent correct modeling and interpretation of the structure of water. In this study, dynamic near-infrared spectra acquired during a drying process allow the study of the physical effects of water content variations, with a focus on the first overtone OH absorbance region. A model sample consisting of aluminum pellets mixed with water allowed us to study this specifically, without any other absorbing interaction terms related to the dry mass-absorbing constituents. A new formulation of the Bouguer-Beer-Lambert law is proposed, by expressing path length as a power function of water content. Through this new formulation, it is shown that a better and simpler prediction model of water content may be developed, with more precise and accurate identification of water absorbance bands.

Near-Infrared Spectroscopy and Aquaphotomics for Monitoring Mung Bean (Vigna radiata) Sprout Growth and Validation of Ascorbic Acid Content

Mung bean is a leguminous crop with specific trait in its diet, namely in the form of anti-nutrient components. The sprouting process is commonly done for better nutritional acceptance of mung bean as it presents better nutritional benefits. Sprouted mung bean serves as a cheap source of protein and ascorbic acid, which are dependent on the sprouting process, hence the importance of following the biological process. In larger production scale, there has not been a definite standard for mung bean sprouting, raising the need for quick and effective mung bean sprout quality checks. In this regard, near-infrared spectroscopy (NIRS) has been recognized as a highly sensitive technique for quality control that seems suitable for this study. The aim of this paper was to describe quality parameters (water content, pH, conductivity, and ascorbic acid by titration) during sprouting using conventional analytical methods and advanced NIRS techniques as correlative methods for modelling sprouted mung beans’ quality and ascorbic acid content. Mung beans were sprouted in 6 h intervals up to 120 h and analyzed using conventional methods and a NIR instrument. The results of the standard analytical methods were analyzed with univariate statistics (analysis of variance (ANOVA)), and the NIRS spectral data was assessed with the chemometrics approach (principal component analysis (PCA), discriminant analysis (DA), and partial least squares regression (PLSR)). Water content showed a monotonous increase during the 120 h of sprouting. The change in pH and conductivity did not describe a clear pattern during the sprouting, confirming the complexity of the biological process. Spectral data-based discriminant analysis was able to distinctly classify the bean sprouts with 100% prediction accuracy. A NIRS-based model for ascorbic acid determination was made using standard ascorbic acid to quantify the components in the bean extract. A rapid detection technique within sub-percent level was developed for mung bean ascorbic acid content with R² above 0.90. The NIR-based prediction offers reliable estimation of mung bean sprout quality

Water as a probe to understand the traditional Chinese medicine extraction process with near infrared spectroscopy: A case of Danshen (Salvia miltiorrhiza Bge) extraction process

Extraction process is not only a critical manufacturing unit but also the initial process of various extracts and preparations. Taking the most extensive Chinese herbal medicine Danshen (Salvia miltziorrhiza Bge) as an example, salvianolic acid B (Sal B) is its main active pharmaceutical ingredient but lacks accurate characterization of the extraction process. As one of process analytical technologies, near-infrared spectroscopy (NIRS) technology has been widely applied for monitoring pharmaceutical extraction process. In most past studies, water spectral information is often eliminated due to its high absorption. However, this study proposed a method of using water spectrum to understand the whole extraction process and to quickly determine the content of Sal B. Principal component analysis (PCA) was first utilized to investigate the whole extraction process, then the reconstructed spectrum based on PCA was established and analyzed by Aquaphotomics, and finally the partial least squares regression (PLSR) quantitative model of Sal B was established. PCA and Aquaphotomics results showed the whole extraction process could be considered as a dynamic change from structure breaker to structure maker, and the dominance of highly H-bonded water structures increases with the extraction time. Also, the Sal B quantitative model with water spectrum showed higher accuracy and stability than other methods, which parameters (RMSEC, RMSECV, RMSEP, R²c, R²cv, R²p, RPD) were 0.2408 mg/mL, 0.2939 mg/mL, 0.2584 mg/mL, 0.9536, 0.9300, 0.9494, 4.6298, respectively, and the paired t-test showed that Sal B content measured by NIR and HPLC methods had no significant differences (p > 0.05). In conclusion, all result indicated that water can be used as a probe to understand the traditional Chinese medicine extraction process with NIRS.

Understanding hyaluronic acid induced variation of water structure by near-infrared spectroscopy

In order to understand the hydration effect of hyaluronic acid (HA) in aqueous solution, near-infrared (NIR) spectroscopy was used to investigate the HA aqueous solutions at different concentrations and temperature. As HA concentration was raised, there was a nonlinear change in absorption value in the first overtone region of OH, indicating the changes of hydration water. A reconstructed spectrum based on principal component analysis (PCA) was established and analyzed with the concept of aquaphotomics. The results showed that HA acted as a structure maker to make water molecules arranged in order. Water species with two hydrogen bonds (S2) and three hydrogen bonds (S3) showed the decrease at low concentration range of 0-40 mg/mL, but increased at higher concentration, indicating the difference in water species at different HA concentration. Meanwhile, HA had the ability to improve the thermal stability of water structure, suggesting a potential bio-protective function. This study provides a unique perspective on the molecular interactions between HA and water molecules, which is helpful for understanding the role of HA in life process and may serve as the basis for HA applications.

Nano-/Micro-confined Water in Graphene Hydrogel as Superadsorbents for Water Purification

Confined water has been proven to be of great importance due to its pervasiveness and contribution to life and many fields of scientific research. However, the control and characterization of confined water are a challenge. Herein, a confined space is constructed by flexibly changing the pH of a graphene oxide dispersion under the self-assembly process of a graphene hydrogel (GH), and the confined space is adjusted with variation from 10.04 to 3.52 nm. Confined water content in GH increases when the pore diameter of the confined space decreases; the corresponding adsorption capacity increases from 243.04 to 442.91 mg g^-1. Moreover, attenuated total reflectance Fourier transform infrared spectroscopy and Raman spectroscopy are utilized to analyze the hydrogen bonding structure qualitatively and quantitatively, and correlation analysis reveals that the improvement in the adsorption capacity is caused by incomplete hydrogen bonding in the confined water. Further, confined water is assembled into four typical porous commercial adsorbents, and a remarkable enhancement of the adsorption capacity is achieved. This research demonstrates the application potential for the extraordinary properties of confined water and has implications for the development of highly effective confined water-modified adsorbents.

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.

Application of near-infrared spectroscopy for frozen-thawed characterization of cuttlefish (Sepia officinalis)

Few works to date have reported the application of near-infrared spectroscopy (NIRS) for the characterization and authentication of cephalopods. This study investigated the feasibility of a portable NIRS instrument for the non-destructive freshness evaluation of fresh (F) and frozen-thawed (FT) cuttlefish (Sepia officinalis). Samples were examined by chemical, microbiological and sensorial analyses, during 13 days of conservation at 3 °C. The spectral data were collected on lateral mantle of cuttlefish, and different partial least squares discriminant analyses (PLS-DA) were applied for classification purposes. The interpretation of spectra was also investigated by applying the specific water coordinates, using aquaphotomics. Few significant differences in the wet chemistry and microbiological data were detected between F and FT during storage. The quality index method and microbiological analyses suggested similar behavior between F and FT samples until to near 9 days of shelf life. PLS-DA models with the spectral range 900-1650 nm achieved a classification precision of 0.91 between F and FT, while the performances for the prediction of storage days were less effective. The results of aquaphotomics plotted in aquagrams were suitable for the interpretation of the main physicochemical changes of cuttlefish throughout the shelf life. The water coordinates suggested a different molecular conformation of water species in the FT than F samples, with more free water molecules and a lower amount of bound species and the water solvation shell, respectively.

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.

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.

Effects of temperature, concentration, and isomer on the hydration structure in monosaccharide solutions

Water-monosaccharide coupled interactions are essential for the function, stability, and dynamics of all glycans. Using molecular dynamics simulations, we investigated the effects of temperature, concentration, and monosaccharide isomer on the hydration structure and water dynamics in the hydration shell of monosaccharides in solution. We found that perturbations of the hydrogen-bond (H-bond) network in the first hydration shell around each monosaccharide molecule can be separated into two regions: one rich in water molecules with donor H-bonds (in the 2.4-2.8 Å region) and the other rich in water molecules with abundant acceptor H-bonds (in the 2.8-3.3 Å region). Moreover, we investigated the dependencies of clustering and conversion of the conformers of the monosaccharides on temperature and concentration. Increasing the concentration enhances monosaccharide clustering in all the monosaccharide solutions, while cluster formation does not depend on temperature. In the clusters, some water molecules in the hydration shell are replaced with monosaccharide oxygen atoms, which contributes to the shrinkage of the hydration shell with increasing monosaccharide concentration. The monosaccharides basically adopt one of two conformers, the stable chair or the unstable boat conformer. We revealed that the hydration structures of the boat and chair conformers were dramatically different. As the temperature increases, the content of the chair conformer decreases. Thus, the conversion of conformers strongly affects the hydration structure around the monosaccharide. These results are critical to understand the important roles of the hydration structure in glycan solutions.

Detection of UV-induced cyclobutane pyrimidine dimers by near-infrared spectroscopy and aquaphotomics

Ultraviolet (UV) radiation causes cellular DNA damage, among which cyclobutane pyrimidine dimers (CPDs) are responsible for a variety of genetic mutations. Although several approaches have been developed for detection of CPDs, conventional methods require time-consuming steps. Aquaphotomics, a new approach based on near-infrared spectroscopy (NIRS) and multivariate analysis that determines interactions between water and other components of the solution, has become an effective method for qualitative and quantitative parameters measurement in the solutions. NIR spectral patterns of UVC-irradiated and nonirradiated DNA solutions were evaluated using aquaphotomics for detection of UV-induced CPDs. Groups of UV-irradiated and nonirradiated DNA samples were classified (87.5% accuracy) by soft independent modeling of class analogy (SIMCA). A precise regression model calculated from NIR water spectral patterns based on UVC doses (r Val = 0.9457) and the concentration of cis-syn cyclobutane thymine dimers (cis-syn T<>Ts; r Val = 0.9993) was developed using partial least squares regression (PLSR), while taking advantage of water spectral patterns, particularly around 1400-1500 nm. Our results suggested that, in contrast to DNA, the formation of cis-syn T<>Ts increased the strongly hydrogen bonded water. Additionally, NIRS could qualitatively and quantitatively detect cis-syn T<>Ts in isolated DNA aqueous solutions upon UVC exposure.

Solvation shell resolved THz spectra of simple aqua ions – distinct distance- and frequency-dependent contributions of solvation shells

Spatial decomposition schemes for infrared spectra reveal the importance of both dipolar couplings and correlations in particle motion in aqueous solutions of Na⁺and Cl⁻.