Breakthrough Potential in Near-Infrared Spectroscopy: Spectra Simulation. A Review of Recent Developments

Nondestructive Detection of Weight Loss Rate, Surface Color, Vitamin C Content, and Firmness in Mini-Chinese Cabbage with Nanopackaging by Fourier Transform-Near Infrared Spectroscopy

A nondestructive optical method is described for the quality assessment of mini-Chinese cabbage with nanopackaging during its storage, using Fourier transform-near infrared (FT-NIR) spectroscopy. The sample quality attributes measured included weight loss rate, surface color index, vitamin C content, and firmness. The level of freshness of the mini-Chinese cabbage during storage was divided into three categories. Partial least squares regression (PLSR) and the least squares support vector machine were applied to spectral datasets in order to develop prediction models for each quality attribute. For a comparative analysis of performance, the five preprocessing methods applied were standard normal variable (SNV), first derivative (lst), second derivative (2nd), multiplicative scattering correction (MSC), and auto scale. The SNV-PLSR model exhibited the best prediction performance for weight loss rate (Rp2 = 0.96, RMSEP = 1.432%). The 1st-PLSR model showed the best prediction performance for L* value (Rp2 = 0.89, RMSEP = 3.25 mg/100 g), but also the lowest accuracy for firmness (Rp2 = 0.60, RMSEP = 2.453). The best classification model was able to predict freshness levels with 88.8% accuracy in mini-Chinese cabbage by supported vector classification (SVC). This study illustrates that the spectral profile obtained by FT-NIR spectroscopy could potentially be implemented for integral assessments of the internal and external quality attributes of mini-Chinese cabbage with nanopacking during storage.

Anharmonic DFT Study of Near-Infrared Spectra of Caffeine: Vibrational Analysis of the Second Overtones and Ternary Combinations

Anharmonic quantum chemical calculations were employed to simulate and interpret a near-infrared (NIR) spectrum of caffeine. First and second overtones, as well as binary and ternary combination bands, were obtained, accurately reproducing the lineshape of the experimental spectrum in the region of 10,000–4000 cm⁻¹ (1000–2500 nm). The calculations enabled performing a detailed analysis of NIR spectra of caffeine, including weak bands due to the second overtones and ternary combinations. A highly convoluted nature of NIR spectrum of caffeine was unveiled, with numerous overlapping bands found beneath the observed spectral lineshape. To properly reflect that intrinsic complexity, the band assignments were provided in the form of heat maps presenting the contributions to the NIR spectrum from various kinds of vibrational transitions. These contributions were also quantitatively assessed in terms of the integral intensities. It was found that the combination bands provide the decisively dominant contributions to the NIR spectrum of caffeine. The first overtones gain significant importance between 6500–5500 cm⁻¹, while the second overtones are meaningful in the higher wavenumber regions, particularly in the 10,000–7000 cm⁻¹ region. The obtained detailed band assignments enabled deep interpretation of the absorption regions of caffeine identified in the literature as meaningful for analytical applications of NIR spectroscopy focused on quantitative analysis of caffeine content in drugs and natural products.

Theoretical Simulation of Near-Infrared Spectrum of Piperine: Insight into Band Origins and the Features of Regression Models

We investigated the near-infrared spectrum of piperine using quantum mechanical calculations. We evaluated two efficient approaches, DVPT2//PM6 and DVPT2//ONIOM [PM6:B3LYP/6-311++G(2df, 2pd)] that yielded a simulated spectrum with varying accuracy versus computing time factor. We performed vibrational assignments and unveiled complex nature of the near-infrared spectrum of piperine, resulting from a high level of band convolution. The most meaningful contribution to the near-infrared absorption of piperine results from binary combination bands. With the available detailed near-infrared assignment of piperine, we interpreted the properties of partial least square regression models constructed in our earlier study to describe the piperine content in black pepper samples. Two models were compared with spectral data sets obtained with a benchtop and a miniaturized spectrometer. The two spectrometers implement distinct technology which leads to a profound instrumental difference and discrepancy in the predictive performance when analyzing piperine content. We concluded that the sensitivity of the two instruments to certain types of piperine vibrations is different and that the benchtop spectrometer unveiled higher selectivity. Such difference in obtaining chemical information from a sample can be one of the reasons why the benchtop spectrometer performs better in analyzing the piperine content of black pepper. This evidenced direct correspondence between the features critical for applied near-infrared spectroscopic routine and the underlying vibrational properties of the analyzed constituent in a complex sample.

Advances in differentiation and identification of foodborne bacteria using near infrared spectroscopy

Rapid and sensitive detection of foodborne bacteria is a growing concern for ensuring safe food supply and preventing human foodborne infections. It is difficult for conventional methods to meet these detection requirements because they are often tedious and time-consuming. In the recent years, near infrared (NIR) spectroscopy has been found to be a promising method for all sorts of analyses in microbiology due to its highly specific absorption signature and non-destructive measurements. In this review, we first briefly introduce the fundamental and basic operational procedure of NIR spectroscopy for foodborne bacteria detection. Then we summarize the main advances and contributions of this technique in the study of foodborne bacteria. Finally, we conclude that much work still remains to be done before NIR spectroscopy really becomes a viable alternative in the field of microbiological characterization.

Probing penile hemodynamics by using photoplethysmography as objective indicators for male erection quality and sexual function

Erectile dysfunction (ED) is mostly due to the lack of blood flow into the penis. In the past 20 years, near-infrared spectroscopy (NIRS) was used in measuring the concentrations and temporal dynamics of different hemoglobin types. However, the dynamics of the light absorption (photoplethysmography; PPG) have not been applied to survey penile hemodynamics and erection quality. This paper compared the use of photoplethysmography (PPG) to study vascular ED with standard penile Doppler ultrasonography. Men diagnosed with vascular ED for at least 6 months and nominated for penile ultrasonography were included. PPG signals were collected during the ultrasound examination. All beat-to-beat PPG waveforms were aligned with the peak and averaged to one representative template waveform for feature analysis, including amplitude differences (APD) index, reflection time index (RTI), augmentation index (AI), and perfusion index (PI). An inverse correlation was found between end-erection amplitude and both erection hardness score (EHS) and resistive index (RI). APD index and EHS as well as the international index of erectile function-5 (IIEF) and RI were positively correlated. RTI and AI were inversely correlated to IIEF and RI. PI was positively correlated to RI. PPG may therefore be useful as a noninvasive, convenient, technique for sexual function evaluation.

Current and future research directions in computer-aided near-infrared spectroscopy: A perspective

The present review aims to draw a perspective on the vibrational spectroscopy combined with the tools of computational chemistry. This includes an overview of the accomplishments made so far, the assessment of the present development trends and the prospects for continuing these advances. State-of-the-art methods, current challenges and the expected future advances are evaluated from the point-of-view of the practical application in vibrational spectroscopy. A special attention is given to near-infrared (NIR) spectroscopy, which occupies a distinct position among the techniques of vibrational spectroscopy. As the result of intrinsically complex spectra, reliance on the anharmonicity as well as keen interest given to complex materials, NIR spectroscopy may particularly benefit from computational chemistry. The present key limitations hindering development of NIR spectroscopy are identified; these constitute primarily the limit in the treatable system size and the inability to effectively include chemical matrix effects. Given the expanding role of NIR spectroscopy in science and industry, lifting these limitations would directly enhance the general potential of this technique.

Recent Advances in Transducers for Intravascular Ultrasound (IVUS) Imaging

As a well-known medical imaging methodology, intravascular ultrasound (IVUS) imaging plays a critical role in diagnosis, treatment guidance and post-treatment assessment of coronary artery diseases. By cannulating a miniature ultrasound transducer mounted catheter into an artery, the vessel lumen opening, vessel wall morphology and other associated blood and vessel properties can be precisely assessed in IVUS imaging. Ultrasound transducer, as the key component of an IVUS system, is critical in determining the IVUS imaging performance. In recent years, a wide range of achievements in ultrasound transducers have been reported for IVUS imaging applications. Herein, a comprehensive review is given on recent advances in ultrasound transducers for IVUS imaging. Firstly, a fundamental understanding of IVUS imaging principle, evaluation parameters and IVUS catheter are summarized. Secondly, three different types of ultrasound transducers (piezoelectric ultrasound transducer, piezoelectric micromachined ultrasound transducer and capacitive micromachined ultrasound transducer) for IVUS imaging are presented. Particularly, the recent advances in piezoelectric ultrasound transducer for IVUS imaging are extensively examined according to their different working mechanisms, configurations and materials adopted. Thirdly, IVUS-based multimodality intravascular imaging of atherosclerotic plaque is discussed. Finally, summary and perspectives on the future studies are highlighted for IVUS imaging applications.

Miniaturized integrated spectrometer using a silicon ring-grating design

We introduce and experimentally demonstrate a miniaturized integrated spectrometer operating over a broad bandwidth in the short-wavelength infrared (SWIR) spectrum that combines an add-drop ring resonator narrow band filter with a distributed Bragg reflector (DBR) based broadband filter realized in a silicon photonic platform. The contra-directional coupling DBR filter in this design consists of a pair of waveguide sidewall gratings that act as a broadband filter (i.e., 3.9 nm). The re-directed beam is then fed into the ring resonator which functions as a narrowband filter (i.e., 0.121 nm). In this scheme the free spectral range (FSR) limitation of the ring resonator is overcome by using the DBR as a filter to isolate a single ring resonance line. The overall design of the spectrometer is further simplified by simultaneously tuning both components through the thermo-optic effect. Moreover, several ring-grating spectrometer cells with different central wavelengths can be stacked in cascade in order to cover a broader spectrum bandwidth. This can be done by centering each unit cell on a different center wavelength such that the maximum range of one-unit cell corresponds to the minimum range of the next unit cell. This configuration enables high spectral resolution over a large spectral bandwidth and high extinction ratio (ER), making it suitable for a wide variety of applications.

Nondestructive qualitative and quantitative analysis of Yaobitong capsule using near-infrared spectroscopy in tandem with chemometrics

The purpose of the study is to present a nondestructive qualitative and quantitative approach of hard-shell capsule using near-infrared (NIR) spectroscopy combined with chemometrics. The Yaobitong capsule (YBTC) was used for demonstration of the proposed approach and the NIR spectra were collected using a handheld fiber probe (FP) without the damage of capsule shell. By comparing the differences and similarities of the NIR spectra of capsule shells, contents and intact capsules, a preliminary conclusion can be drawn that the NIR spectra contained the information of the contents. Characteristic variables were selected by competitive adaptive weighted resampling (CARS) method, and least squares support vector machine (LSSVM) method based on particle swarm optimization (PSO) algorithm was applied to the construction of quantitative models. The relative standard error of prediction (RSEP) values of five saponins including notoginsenoside R1, ginsenoside Rg1, Re, Rb1, and Rd were 3.240%, 5.468%, 5.303%, 5.043%, and 3.745%, respectively. In addition, for qualitative model, three different types of adulterated capsules were designed. The model established by data driven version of soft independent modeling of class analogy (DD-SIMCA) demonstrated a satisfactory result that all adulterated capsules were identified accurately after an appropriate number of principal components (PCs) were chosen. The results indicated that although the NIR spectra collection was affected by capsule shell, sufficient content information can be obtained for quantitative and qualitative analysis after combining with chemometrics. It further proved that acquired NIR spectra do contain the effective component information of the capsule. This study provided a reference for the rapid nondestructive quality analysis of traditional Chinese medicine (TCM) capsule without damaging capsule shell.

A Near-Infrared "Matchbox Size" Spectrometer to Detect and Quantify Malaria Parasitemia

New point-of-care diagnostic approaches for malaria that are sensitive to low parasitemia, easy to use in a field setting, and affordable are urgently required to meet the World Health Organization's objective of reducing malaria cases and related life losses by 90% globally on or before 2030. In this study, an inexpensive "matchbox size" near-infrared (NIR) spectrophotometer was used for the first time to detect and quantify malaria infection in vitro from isolated dried red blood cells using a fingerpick volume of blood. This the first study to apply a miniaturized NIR device to diagnose a parasitic infection and identify marker bands indicative of malaria infection in the NIR region. An NIR device has many advantages including wavelength accuracy and repeatability, speed, resolution, and a greatly improved signal-to-noise ratio compared to existing spectroscopic options. Using multivariate data analysis, we discriminated control red blood cells from infected cells and established the limit of detection of the technique. Principal component analysis displayed a good separation between the infected and uninfected RBCs, while partial least-squares regression analysis yielded a robust parasitemia prediction with root-mean-square error of prediction values of 0.446 and 0.001% for the higher and lower parasitemia models, respectively. The R² values of the higher and lower parasitemia models were 0.947 and 0.931, respectively. Finally, an estimated parasitemia detection limit of 0.00001% and a qunatification limit of 0.001% was achieved; to ascertain the true efficacy of the technique for point-of-care screening, clinical studies using large patient numbers are required, which is the subject of future studies.

Alginate enriched with phytic acid for hydrogels preparation

Alginate hydrogels are extremely versatile and flexible biomaterials, with an enormous potential for bio-applications use. Their similarity with extracellular matrix is a key factor in their performance for cell and tissue regeneration. In this study superabsorbent high porous hydrogels based on sodium alginate physical crosslinked with a natural crosslinker compound namely phytic acid were prepared and evaluated from the viewpoint of their specific properties. The resulting hydrogels obtained with different ratios between alginate and phytic acid were characterized by Fourier transform infrared spectroscopy technique, scanning electron microscopy, XRD measurements, swelling tests in physiological environment, and thermal analysis by using a simultaneous TG/FT-IR/MS system. There are put into evidence the differences in physico-chemical properties of the hydrogels in relation with their composition, which endows them tunable properties and versatility.

Unravelling the structural complexity of glycolipids with cryogenic infrared spectroscopy

Glycolipids are complex glycoconjugates composed of a glycan headgroup and a lipid moiety. Their modular biosynthesis creates a vast amount of diverse and often isomeric structures, which fulfill highly specific biological functions. To date, no gold-standard analytical technique can provide a comprehensive structural elucidation of complex glycolipids, and insufficient tools for isomer distinction can lead to wrong assignments. Herein we use cryogenic gas-phase infrared spectroscopy to systematically investigate different kinds of isomerism in immunologically relevant glycolipids. We show that all structural features, including isomeric glycan headgroups, anomeric configurations and different lipid moieties, can be unambiguously resolved by diagnostic spectroscopic fingerprints in a narrow spectral range. The results allow for the characterization of isomeric glycolipid mixtures and biological applications.

Glycolipids are glycoconjugates with important biological functions, but techniques for their analysis are deficient. Here, the authors report the use of cryogenic gas-phase infrared spectroscopy to investigate isomerism in a set of immunologically relevant glycolipids, and show that their structural features can be accurately resolved based on a narrow spectral fingerprint region.

Mid-Infrared Spectroscopy as a Valuable Tool to Tackle Food Analysis: A Literature Review on Coffee, Dairies, Honey, Olive Oil and Wine

Nowadays, food adulteration and authentication are topics of utmost importance for consumers, food producers, business operators and regulatory agencies. Therefore, there is an increasing search for rapid, robust and accurate analytical techniques to determine the authenticity and to detect adulteration and misrepresentation. Mid-infrared spectroscopy (MIR), often associated with chemometric techniques, offers a fast and accurate method to detect and predict food adulteration based on the fingerprint characteristics of the food matrix. In the first part of this review the basic concepts of infrared spectroscopy, sampling techniques, as well as an overview of chemometric tools are summarized. In the second part, recent applications of MIR spectroscopy to the analysis of foods such as coffee, dairy products, honey, olive oil and wine are discussed, covering a timespan from 2010 to mid-2020. The literature gathered in this article clearly reveals that the MIR spectroscopy associated with attenuated total reflection acquisition mode and different chemometric tools have been broadly applied to address quality, authenticity and adulteration issues. This technique has the advantages of being simple, fast and easy to use, non-destructive, environmentally friendly and, in the future, it can be applied in routine analyses and official food control.

The Use of a Micro Near Infrared Portable Instrument to Predict Bioactive Compounds in a Wild Harvested Fruit-Kakadu Plum (Terminalia ferdinandiana)

Kakadu plum (KP; Terminalia ferdinandiana Exell, Combretaceae) is an emergent indigenous fruit originating from Northern Australia, with valuable health and nutritional characteristics and properties (e.g., high levels of vitamin C and ellagic acid). In recent years, the utilization of handheld NIR instruments has allowed for the in situ quantification of a wide range of bioactive compounds in fruit and vegetables. The objective of this study was to evaluate the ability of a handheld NIR spectrophotometer to measure vitamin C and ellagic acid in wild harvested KP fruit samples. Whole and pureed fruit samples were collected from two locations in the Kimberley region (Western Australia, Australia) and were analysed using both reference and NIR methods. The standard error in cross validation (SECV) and the residual predictive deviation (RPD) values were 1.81% dry matter (DM) with an RPD of 2.1, and 3.8 mg g⁻¹ DM with an RPD of 1.9 for the prediction of vitamin C and ellagic acid, respectively, in whole KP fruit. The SECV and RPD values were 1.73% DM with an RPD of 2.2, and 5.6 mg g⁻¹ DM with an RPD of 1.3 for the prediction of vitamin C and ellagic acid, respectively, in powdered KP samples. The results of this study demonstrated the ability of a handheld NIR instrument to predict vitamin C and ellagic acid in whole and pureed KP fruit samples. Although the RPD values obtained were not considered adequate to quantify these bioactive compounds (e.g., analytical quantification), this technique can be used as a rapid tool to screen vitamin C in KP fruit samples for high and low quality vitamin C.

Principles and Applications of Miniaturized Near-Infrared (NIR) Spectrometers

This review article focuses on the principles and applications of miniaturized near-infrared (NIR) spectrometers. This technology and its applicability has advanced considerably over the last few years and revolutionized several fields of application. What is particularly remarkable is that the applications have a distinctly diverse nature, ranging from agriculture and the food sector, through to materials science, industry and environmental studies. Unlike a rather uniform design of a mature benchtop FTNIR spectrometer, miniaturized instruments employ diverse technological solutions, which have an impact on their operational characteristics. Continuous progress leads to new instruments appearing on the market. The current focus in analytical NIR spectroscopy is on the evaluation of the devices and associated methods, and to systematic characterization of their performance profiles.

Rapid quantification of active pharmaceutical ingredient for sugar-free Yangwei granules in commercial production using FT-NIR spectroscopy based on machine learning techniques

Rapid quantification methods for sugar-free Yangwei granules were developed based on near-infrared (NIR) spectroscopy combined with machine learning approaches as a quality control strategy for Chinese medicine granules (CMGs). Different machine learning approaches-i.e., interval partial least squares optimized by the genetic algorithm (GA-iPLS), the backpropagation artificial neural network (BP-ANN), and the particle swarm optimization-support vector machine (PSO-SVM)-were used to develop prediction models for three active pharmaceutical ingredients (APIs), namely, albiflorin, paeoniflorin, and benzoylpaeoniflorin. The partial least squares (PLS) algorithm was used for linear model calibration and comparison of the prediction performance of these developed models. The performance of the final models was assessed by the correlation coefficient (R), root mean square error of calibration set (RMSEC), and root mean square error of prediction set (RMSEP). All models performed well in model fitting and provided satisfactory prediction accuracy. The results indicate that the machine learning approaches are more stable, predictable, and suitable for CMGs when a high-accuracy analysis is required. In summary, NIR spectroscopy coupled with machine learning techniques is a suitable tool for the straightforward quantification of CMGs.

NIR associated to PLS and SVM for fast and non-destructive determination of C, N, P, and K contents in poultry litter

Using near-infrared (NIR) spectroscopy for poultry litter characterization can be a rapid, non-destructive, and low-cost alternative. This study aims to estimate the C, N, P, and K content in poultry litter samples using for first time NIR spectroscopy. For these purposes, the building models were carried out using Partial Least Squares (PLS) and Support Vector Machines (SVM) methods. A total of 160 litter samples were analyzed in poultry houses of different rearing systems, seeking the highest possible variability in their chemical composition. NIR spectroscopy, combined with PLS and SVM methods, is an alternative method for non-destructive C, N, P, and K determination in poultry samples. The regression models using SVM provide better accuracy for all elements, laying the basis for the nonlinear regression approach's application. The K determination on poultry litter using NIR was possible only by the SVM model (R² = 0.8620 and RPD = 2.7330). Conclusively, the predictive ability was improved using the SVM method.

Application of Near-Infrared Spectroscopy to Investigate Some Endogenic Properties of Pleurotus ostreatus Cultivars

Fourteen different Pleurotus ostreatus cultivars (Po_1–Po_14) were tested for free amino acid content (fAA), total polyphenol content (TPC), and antioxidant capacity (Ferric Reducing Ability of Plasma—FRAP) to select the cultivars with the most favorable traits. Automatic amino acid analyzer (fAA) and spectrophotometric assay (TPC, FRAP) results as well as Fourier-transform near infrared (FT-NIR) spectra were evaluated with different chemometric methods (Kruskal–Wallis test, Principal Component Analysis—PCA, Linear Discriminant Analysis—LDA). Based on total free amino acid concentrations and FRAP values, the Po_2 cultivar was found to be the most favorable. Types Po_3, Po_8, Po_10 and Po_12 were separated using PCA. Based on the spectral profile, they may contain polyphenols and reducing compounds of different qualities. LDA classification that was based on the concentrations of all free amino acids, cysteine, and proline of the cultivars was performed with an accuracy of over 90%. LDA classification that was based on the TPC and FRAP values was performed with an accuracy of over 83%.

TAO-DFT-Based Ab Initio Molecular Dynamics

Recently, AIMD (ab initio molecular dynamics) has been extensively employed to explore the dynamical information of electronic systems. However, it remains extremely challenging to reliably predict the properties of nanosystems with a radical nature using conventional electronic structure methods (e.g., Kohn-Sham density functional theory) due to the presence of static correlation. To address this challenge, we combine the recently formulated TAO-DFT (thermally-assisted-occupation density functional theory) with AIMD. The resulting TAO-AIMD method is employed to investigate the instantaneous/average radical nature and infrared spectra of n-acenes containing n linearly fused benzene rings (n = 2-8) at 300 K. According to the TAO-AIMD simulations, on average, the smaller n-acenes (up to n = 5) possess a nonradical nature, and the larger n-acenes (n = 6-8) possess an increasing radical nature, showing remarkable similarities to the ground-state counterparts at 0 K. Besides, the infrared spectra of n-acenes obtained with the TAO-AIMD simulations are in qualitative agreement with the existing experimental data.

Historical Evolution and Food Control Achievements of Near Infrared Spectroscopy, Electronic Nose, and Electronic Tongue-Critical Overview

Amid today's stringent regulations and rising consumer awareness, failing to meet quality standards often results in health and financial compromises. In the lookout for solutions, the food industry has seen a surge in high-performing systems all along the production chain. By virtue of their wide-range designs, speed, and real-time data processing, the electronic tongue (E-tongue), electronic nose (E-nose), and near infrared (NIR) spectroscopy have been at the forefront of quality control technologies. The instruments have been used to fingerprint food properties and to control food production from farm-to-fork. Coupled with advanced chemometric tools, these high-throughput yet cost-effective tools have shifted the focus away from lengthy and laborious conventional methods. This special issue paper focuses on the historical overview of the instruments and their role in food quality measurements based on defined food matrices from the Codex General Standards. The instruments have been used to detect, classify, and predict adulteration of dairy products, sweeteners, beverages, fruits and vegetables, meat, and fish products. Multiple physico-chemical and sensory parameters of these foods have also been predicted with the instruments in combination with chemometrics. Their inherent potential for speedy, affordable, and reliable measurements makes them a perfect choice for food control. The high sensitivity of the instruments can sometimes be generally challenging due to the influence of environmental conditions, but mathematical correction techniques exist to combat these challenges.

Near-Infrared Spectroscopy as a Rapid Screening Method for the Determination of Total Anthocyanin Content in Sambucus Fructus

Elderberry (Sambucus nigra L., fructus) is a very potent herbal drug, deriving from traditional European medicine (TEM). Ripe elderberries are rich in anthocyanins, flavonols, flavonol esters, flavonol glycosides, lectins, essential oils, unsaturated fatty acids and vitamins. Nevertheless, unripe elderflower fruits contain a certain amount of sambunigrin, a toxic cyanogenic glycoside, whose concentration decreases in the ripening process. Therefore, quality assurance must be carried out. The standard method described in literature is the photometric determination (pH-differential method) of the total anthocyanin content (TAC) that is the highest when the berries are ripe. The drawback of the pH-differential method is the extensive sample preparation and the low accuracy of the method. Therefore, the goal of this publication was to develop a fast non invasive near-infrared (NIR) method for the determination of TAC in whole berries. TAC of elderberries was measured using pH-differentiation method where TAC values of 632.87 mg/kg to 4342.01 mg/kg were measured. Additionally, cyanidin-3-O-glucoside, cyanidin-3-O-sambubioside and cyanidin-3-O-sambubioside-5-O-glucoside which represent more than 98% of TAC in elderberry were quantified using ultra high performance liquid chromatography-multiple wavelength detection-ultra high resolution-quadrupole-time of flight-mass spectrometry (UHPLC-MWD-UHR-Q-TOF-MS) and their sum parameter was determined, ranging between 499.43 mg/kg and 8199.07 mg/kg. Using those two methods as reference, whole elderberries were investigated by NIR spectroscopy with the Büchi NIRFlex N-500 benchtop spectrometer. According to the constructed partial least squares regression (PLSR) models the performance was as follows: a relative standard deviation (RSDPLSR) of 13.5% and root mean square error of calibration (RMSECV/RMSEC) of 1.31 for pH-differentiation reference and a RSDPLSR of 12.9% and RMSECV/RMSEC of 1.28 for the HPLC reference method. In this study, we confirm that it is possible to perform a NIR screening for TAC in whole elderberries. Using quantum chemical calculations, we obtained detailed NIR band assignments of the analyzed compounds and interpreted the wavenumber regions established in PLSR models as meaningful for anthocyanin content. The NIR measurement turned out to be a fast and cost-efficient alternative for the determination of TAC compared to pH-differential method and UHPLC-MWD-UHR-Q-TOF-MS. Due to the benefit of no sample preparation and extraction the technology can be considered as sustainable green technology. With the above mentioned inversely proportional ratio of TAC to total amount of toxic cyanogenic glycosides, NIR proves to be a reliable screening method for the ideal harvest time with maximal content of TAC and lowest content of cyanogenic glycosides in elderberry.

The Sample, the Spectra and the Maths-The Critical Pillars in the Development of Robust and Sound Applications of Vibrational Spectroscopy

The last two decades have witnessed an increasing interest in the use of the so-called rapid analytical methods or high throughput techniques. Most of these applications reported the use of vibrational spectroscopy methods (near infrared (NIR), mid infrared (MIR), and Raman) in a wide range of samples (e.g., food ingredients and natural products). In these applications, the analytical method is integrated with a wide range of multivariate data analysis (MVA) techniques (e.g., pattern recognition, modelling techniques, calibration, etc.) to develop the target application. The availability of modern and inexpensive instrumentation together with the access to easy to use software is determining a steady growth in the number of uses of these technologies. This paper underlines and briefly discusses the three critical pillars-the sample (e.g., sampling, variability, etc.), the spectra and the mathematics (e.g., algorithms, pre-processing, data interpretation, etc.)-that support the development and implementation of vibrational spectroscopy applications.

Multi-Sensor Approach to Improve Bathymetric Lidar Mapping of Semi-Arid Groundwater-Dependent Streams: Devils River, Texas

Remote sensing technology enables detecting, acquiring, and recording certain information about objects and locations from distances relative to their geographic locations. Airborne Lidar bathymetry (ALB) is an active, non-imaging, remote sensing technology for measuring the depths of shallow and relatively transparent water bodies using light beams from an airborne platform. In this study, we acquired Lidar datasets using near-infrared and visible (green) wavelength with the Leica Airborne Hydrography AB Chiroptera-I system over the Devils River basin of southwestern Texas. Devils River is a highly groundwater-dependent stream that flows 150 km from source springs to Lake Amistad on the lower Rio Grande. To improve spatially distributed stream bathymetry in aquatic habitats of species of state and federal conservation interest, we conducted supplementary water-depth observations using other remote sensing technologies integrated with the airborne Lidar datasets. Ground penetrating radar (GPR) mapped the river bottom where vegetation impeded other active sensors in attaining depth measurements. We confirmed the accuracy of bathymetric Lidar datasets with a differential global positioning system (GPS) and compared the findings to sonar and GPR measurements. The study revealed that seamless bathymetric and geomorphic mapping of karst environments in complex settings (e.g., aquatic vegetation, entrained air bubbles, riparian zone obstructions) require the integration of a variety of terrestrial and remotely operated survey methods. We apply this approach to Devils River of Texas. However, the methods are applicable to similar streams globally.

An Intuitively Understandable Quality Measure for Theoretical Vibrational Spectra

Computational chemistry has become a central tool in spectroscopic studies in most of chemical science. The quality of a calculated vibrational spectrum is commonly expressed as the deviation of the peak position from the experimental reference. With the increasing application of vibrational spectroscopy to complex (biological) systems, this is likely not sustainable. Here we present a quality measure for theoretical vibrational spectra based on matching the spectra to a reference database with the help of correlation coefficients. This approach can easily be applied to large sets of data and complex spectra without easily identifiable peak positions. We demonstrate this on a database of infrared spectra of 670 compounds using six different theoretical (DFT and force field) methods. Most importantly, it is intuitively understandable by both theoreticians and experimentalists.

Near-Infrared Spectroscopy in Bio-Applications

Near-infrared (NIR) spectroscopy occupies a specific spot across the field of bioscience and related disciplines. Its characteristics and application potential differs from infrared (IR) or Raman spectroscopy. This vibrational spectroscopy technique elucidates molecular information from the examined sample by measuring absorption bands resulting from overtones and combination excitations. Recent decades brought significant progress in the instrumentation (e.g., miniaturized spectrometers) and spectral analysis methods (e.g., spectral image processing and analysis, quantum chemical calculation of NIR spectra), which made notable impact on its applicability. This review aims to present NIR spectroscopy as a matured technique, yet with great potential for further advances in several directions throughout broadly understood bio-applications. Its practical value is critically assessed and compared with competing techniques. Attention is given to link the bio-application potential of NIR spectroscopy with its fundamental characteristics and principal features of NIR spectra.

Detecting Low Concentrations of Nitrogen-Based Adulterants in Whey Protein Powder Using Benchtop and Handheld NIR Spectrometers and the Feasibility of Scanning through Plastic Bag

Nitrogen-rich adulterants in protein powders present sensitivity challenges to conventional combustion methods of protein determination which can be overcome by near Infrared spectroscopy (NIRS). NIRS is a rapid analytical method with high sensitivity and non-invasive advantages. This study developed robust models using benchtop and handheld spectrometers to predict low concentrations of urea, glycine, taurine, and melamine in whey protein powder (WPP). Effectiveness of scanning samples through optical glass and polyethylene bags was also tested for the handheld NIRS. WPP was adulterated up to six concentration levels from 0.5% to 3% w/w. The two spectrometers were used to obtain three datasets of 819 diffuse reflectance spectra each that were pretreated before linear discriminant analysis (LDA) and regression (PLSR). Pretreatment was effective and revealed important absorption bands that could be correlated with the chemical properties of the mixtures. Benchtop NIR spectrometer showed the best results in LDA and PLSR but handheld NIR spectrometers showed comparatively good results. There were high prediction accuracies and low errors attesting to the robustness of the developed PLSR models using independent test set validation. Both the plastic bag and optical glass gave good results with accuracies depending on the adulterant of interest and can be used for field applications.

Theae nigrae folium: Comparing the analytical performance of benchtop and handheld near-infrared spectrometers

We investigated caffeine and l-theanine, quality characteristics for camellia sinensis, in milled and ground black tea samples with near-infrared (NIR) spectroscopy giving a direct comparison between the performances of benchtop and handheld NIR spectrometers. The constructed partial least squares regression (PLSR) models for all spectrometers were validated by test-set-validation and according to the obtained root mean square errors of prediction (RMSEP). The performances of the spectrometers were as follows: The benchtop spectrometer NIRFlex N-500 (Büchi, Flawil, Switzerland) showed the best results for milled samples with a RMSEP of 0.14% for caffeine and 0.12% for l-theanine. For the ground samples, a RMSEP of 0.17% for caffeine and 0.12% for l-theanine was gained. While the handheld spectrometers MicroNIR 2200 (Viavi Solutions (former: JDS Uniphase Corporation), Milpitas, USA) and the microPHAZIR (Thermo Fisher Scientific, Waltham, USA) both provided good results for the prediction of caffeine in milled samples (RMSEP of 0.22% and 0.26%), only the microPHAZIR was able to satisfactorily determine the caffeine content in ground samples (RMSEP of 0.28%). The investigation of l-theanine with handheld spectrometers did not lead to convincing results, since R² was 0.75 for milled samples while ground samples could not be calculated. Decisive differences were concluded in how different NIR instruments capture the chemical information on caffeine vs. l-theanine. The handheld spectrometers manifested limited applicability to l-theanine. Deeper insight was obtained through the detailed NIR band assignments of caffeine and l-theanine derived from quantum mechanical simulation. Narrow working spectral region of handhelds omits the characteristic absorption bands of l-theanine. Therefore, information on l-theanine content measured by the evaluated miniaturized spectrometers is insufficient to enable its effective quantification. In contrast, the most characteristic NIR absorption of caffeine matches the working spectral regions of the handheld NIR spectrometers, hence their performance is comparable with the benchtop device.

Interaction between tau and water during the induced aggregation revealed by near-infrared spectroscopy

Near-infrared (NIR) spectra are sensitive to the variation of water structure. In this work, NIR spectroscopy was used to investigate the variation of hydration water during the aggregation of R2/wt induced by heparin. The osmolytes, urea and trehalose, were used to slow down and speed up the aggregation. The spectra of R2/wt aqueous solution obtained by NIR spectroscopy at 37 °C were adopted to analyze the structure of water during the aggregation. The spectral features of different water species were observed by principal component analysis (PCA) from the resolution enhanced NIR spectra. The existence of the water molecules with one and two hydrogen bonds around the NH and CH groups of R2/wt, respectively, was suggested, and the variation of the hydrogen-bonded water was found to be an indicator to monitor the process of aggregation. Then, the variation of the water species during the aggregation was analyzed by two-dimensional correlation spectroscopy. The water hydrogen bonded with NH group was found to change earlier than the water around the hydrophobic groups. The results suggest that β-sheet forms though the hydrogen bonds of amide groups in the early stage of the aggregation, and the destruction of the hydrogen bond network of the water around the side chains maybe the main reason for the formation of the ordered amyloid fibers.

Vibrations of the guanine-cytosine pair in chloroform: an anharmonic computational study

We compute at the anharmonic level the vibrational spectra of the Watson-Crick dimer formed by guanosine (G) and cytidine (C) in chloroform, together with those of G, C and the most populated GG dimer. The spectra for deuterated and partially deuterated GC are also computed. We use DFT calculations, with B3LYP and CAM-B3LYP as reference functionals. Solvent effects from chloroform are included via the Polarizable Continuum Model (PCM), and by performing tests on models including up two chloroform molecules. Both B3LYP and CAM-B3LYP calculations reproduce the shape of the experimental spectra well in the fingerprint region (1500-1700 cm-1) and in the N-H stretching region (2800-3600 cm-1), with B3LYP providing better quantitative agreement with experiments. According to our calculations, the N-H amido streching mode of G falls at ∼2900 cm-1, while the N-H amino of G and C falls at ∼3100 cm-1 when hydrogen-bonded, or ∼3500 cm-1 when free. Overtone and combination bands strongly contribute to the absorption band at ∼3300 cm-1. Inclusion of bulk solvent effects significantly increases the accuracy of the computed spectra, while solute-solvent interactions have a smaller, though still noticeable, effect. Some key aspects of the anharmonic treatment of strongly vibrationally coupled supermolecular systems and the related methodological issues are also discussed.

Solvation effects on wavenumbers and absorption intensities of the OH-stretch vibration in phenolic compounds – electrical- and mechanical anharmonicity via a combined DFT/Numerov approach

A previously measured oscillatory intensity pattern in phenolic compounds between different solvents was successfully reproduced for the first time, employing modern grid-based methods to solve the time-independent vibrational Schrödinger equation.

Principles and Applications of Vibrational Spectroscopic Imaging in Plant Science: A Review

Detailed knowledge about plant chemical constituents and their distributions from organ level to sub-cellular level is of critical interest to basic and applied sciences. Spectral imaging techniques offer unparalleled advantages in that regard. The core advantage of these technologies is that they acquire spatially distributed semi-quantitative information of high specificity towards chemical constituents of plants. This forms invaluable asset in the studies on plant biochemical and structural features. In certain applications, non-invasive analysis is possible. The information harvested through spectral imaging can be used for exploration of plant biochemistry, physiology, metabolism, classification, and phenotyping among others, with significant gains for basic and applied research. This article aims to present a general perspective about vibrational spectral imaging/micro-spectroscopy in the context of plant research. Within the scope of this review are infrared (IR), near-infrared (NIR) and Raman imaging techniques. To better expose the potential and limitations of these techniques, fluorescence imaging is briefly overviewed as a method relatively less flexible but particularly powerful for the investigation of photosynthesis. Included is a brief introduction to the physical, instrumental, and data-analytical background essential for the applications of imaging techniques. The applications are discussed on the basis of recent literature.

Spectroscopic evidence of a particular intermolecular interaction in iodomethane–ethanol mixtures: the cooperative effect of halogen bonding, hydrogen bonding, and the solvent effect

The particular intermolecular interaction of an iodomethane–ethanol mixture is revealed by NIR, Raman, DFT calculation, and 2D correlation analysis.

Simulated NIR spectra as sensitive markers of the structure and interactions in nucleobases

Near-infrared (near-IR; NIR) spectroscopy is continuously advancing in biophysical and biochemical fields of investigation. For instance, recent progresses in NIR hyperspectral imaging of biological systems may be noted. However, interpretation of NIR bands for biological samples is difficult and creates a considerable barrier in exploring the full potential of NIR spectroscopy in bioscience. For this reason, we carried out a systematic study of NIR spectra of adenine, cytosine, guanine, and thymine in polycrystalline state. Interpretation of NIR spectra of these nucleobases was supported by anharmonic vibrational analysis using Deperturbed Vibrational Second-Order Perturbation Theory (DVPT2). A number of molecular models of nucleobases was applied to study the effect of the inter-molecular interactions on the NIR spectra. The accuracy of simulated NIR spectra appears to depend on the intra-layer interactions; in contrast, the inter-layer interactions are less influential. The best results were achieved by combining the simulated spectra of monomers and dimers. It is of particular note that in-plane deformation bands are far more populated than out-of-plane ones and the importance of ring modes is relatively small. This trend is in contrast to that observed in mid-IR region. As shown, the local, short-range chemical neighborhood of nucleobase molecules influence their NIR spectra more considerably. This suggests that NIR spectra are more sensitive probe of the nucleobase pairing than mid-IR ones. The obtained results allow, for the first time, to construct a frequency correlation table for NIR spectra of purines and pyrimidines.

Comparison of Multivariate Regression Models Based on Water- and Carbohydrate-Related Spectral Regions in the Near-Infrared for Aqueous Solutions of Glucose

The predictive power of the two major water bands centered at 6900 cm-1 and 5200 cm-1 in the near-infrared (NIR) region was compared to carbohydrate-related spectral areas located in the first overtone (around 6000 cm-1) and combination (around 4500 cm-1) region using glucose in aqueous solutions as a model substance. For the purpose of optimal coverage of stronger as well as weaker absorbing NIR regions, cells with three different declared optical pathlengths were employed. The sample set consisted of multiple separately prepared batches in the range of 50–200 mmol/L. Moreover, the samples were divided into a calibration set for the construction of the partial least squares regression (PLS-R) models and a test set for the validation process with independent samples. The first overtone and combination region showed relative prediction errors between 0.4–1.6% with only one PLS-R factor required. On the other hand, the errors for the water bands were found between 1.6–8.3% and up to three PLS-R factors required. The best PLS-R models resulted from the cell with 1 mm optical pathlength. In general, the results suggested that the carbohydrate-related regions in the first overtone and combination region should be preferred over the regions of the two dominant water bands.

Spectra-Structure Correlations in Isotopomers of Ethanol (CX3CX2OX; X = H, D): Combined Near-Infrared and Anharmonic Computational Study

The effect of isotopic substitution on near-infrared (NIR) spectra has not been studied in detail. With an exception of few major bands, it is difficult to follow the spectral changes due to complexity of NIR spectra. Recent progress in anharmonic quantum mechanical calculations allows for accurate reconstruction of NIR spectra. Taking this opportunity, we carried out a systematic study of NIR spectra of six isotopomers of ethanol (CX₃CX₂OX; X = H, D). Besides, we calculated the theoretical spectra of two other isotopomers (CH₃CD₂OD and CD₃CH₂OD) for which the experimental spectra are not available. The anharmonic calculations were based on generalized vibrational second-order perturbation theory (GVPT2) at DFT and MP2 levels with several basis sets. We compared the accuracy and efficiency of various computational methods. It appears that the best results were obtained with B2PLYP-GD3BJ/def2-TZVP//CPCM approach. Our simulations included the first and second overtones, as well as binary and ternary combinations bands. This way, we reliably reproduced even minor bands in the spectra of diluted samples (0.1 M in CCl₄). On this basis, the effect of isotopic substitution on NIR spectra of ethanol was accurately reproduced and comprehensively explained.

Recent advances in modeling vibrational spectra of food adulterants – Theoretical simulation of IR and NIR bands of melamine

Food safety may be one of the major concerns of the global society in the forthcoming decades. Analytical vibrational spectroscopy is expected to become a major tool used for controlling the food quality at every stage of its production, storage and delivery. Near-infrared and infrared spectroscopy have rapidly been evolving in analytical applications over the last decades with strong hyphenation to numerical and statistical methods of analysis of complex data, which are known as chemometrics. Analytical spectroscopy has reached a remarkable value for both industrial and institutional laboratories nowadays. However, the routinely used methods of analysis do not attempt to interpret the analysed spectral information in physicochemical sense. Therefore, analytical routines seldom take advantage of the molecular background underlying the properties of analysed sample. In the present article, we review the most recent accomplishments that evidence the progress which may be achieved when that background becomes actually available. We focus on the example of infrared and near-infrared spectra simulation applied to melamine, one of the most infamous food adulterant. This sheds light on the correspondences between infrared and near-infrared region observed earlier in the analytical papers dealing with detection and quantification of melamine in food products.

Distinct Difference in Sensitivity of NIR vs. IR Bands of Melamine to Inter-Molecular Interactions with Impact on Analytical Spectroscopy Explained by Anharmonic Quantum Mechanical Study

Melamine (IUPAC: 1,3,5-Triazine-2,4,6-triamine) attracts high attention in analytical vibrational spectroscopy due to its misuse as a food adulterant. Vibrational spectroscopy [infrared (IR) and Raman and near-infrared (NIR) spectroscopy] is a major quality control tool in the detection and quantification of melamine content. The physical background for the measured spectra is not interpreted in analytical spectroscopy using chemometrics. In contrast, quantum mechanical calculations are capable of providing deep and independent insights therein. So far, the NIR region of crystalline melamine has not been studied by quantum mechanical calculations, while the investigations of its IR spectra have remained limited. In the present work, we employed fully anharmonic calculation of the NIR spectrum of melamine based on finite models, and also performed IR spectral simulation by using an infinite crystal model—periodic in three dimensions. This yielded detailed and unambiguous NIR band assignments and revised the previously known IR band assignments. We found that the out-of-plane fundamental transitions, which are essential in the IR region, are markedly more sensitive to out-of-plane inter-molecular interactions of melamine than NIR transitions. Proper description of the chemical surrounding of the molecule of melamine is more important than the anharmonicity of its vibrations. In contrast, the NIR bands mostly arise from in-plane vibrations, and remain surprisingly insensitive to the chemical environment. These findings explain previous observations that were reported in IR and NIR analytical studies of melamine.