Reproducible quantification of ethanol in gasoline via a customized mobile near-infrared spectrometer

Gasoline discrimination using infrared spectroscopy and virtual samples based on measurement uncertainty

In a previous work, we proposed a methodology for pair-wise discrimination of gasoline samples by creating virtual samples based on physicochemical assays or distillation curves. Satisfactory results were achieved, although specialist and specific apparatus (not commonly available at police laboratories) were required. The present study goes a step further and for the first time investigates the possibility of infrared (IR) spectroscopy to enable a virtual samples-based methodology for comparison of gasoline samples in pairs. IR spectroscopy feasibility for in situ applications is attractive for forensic investigations. The performances of one handheld NIR device and one dual-range (FT-NIR and FT-IR) benchtop spectrometer were evaluated. The estimation of uncertainty in infrared spectral measurement (needed to generate virtual samples) is barely discussed in literature. So far, there are no literature reports describing quantification and comparison of measurement uncertainties for the spectral acquisitions evaluated here, especially regarding their use for generating virtual samples. A stepwise procedure to quantify uncertainties associated with IR spectral acquisition, at each wavenumber, is described. This method can be useful for understanding both the sources of variability in IR measurements and the system under investigation. Uncertainty estimation was based on experimental data and considered intermediate precision, repeatability and variations in sample temperature as sources of variability. Virtual samples were employed in a discrimination approach using SIMCA models. Results for portable NIR, FT-NIR and FT-IR data sets showed complete discrimination for 96.3%, 93.4% and 93.7% of the 1431 pairs of gasoline samples evaluated, respectively. These results were comparable and similar to those obtained for the physicochemical properties data set (95.7%), although slightly inferior to the result obtained for distillation curves (99.2%). Using IR non-destructive methods in this case could enable faster investigations and simpler analysis, especially for the low-cost handheld spectrometer. In a screening approach, atmospheric distillation assays can be employed only if infrared techniques are not capable of distinguishing the samples subject to comparison. In this work, a pair of samples was considered to be completely discriminated only when a null false positive error (FPR) was achieved, although a more flexible criterium may be acceptable in practice. Finally, the methodology could be extended to other applications where sample comparison is important.

Quality Monitoring of Biodiesel and Diesel/Biodiesel Blends: A Comparison between Benchtop FT-NIR versus a Portable Miniaturized NIR Spectroscopic Analysis

A methodology such as near-infrared (NIR) spectroscopy, which enables in situ and in real-time analysis, is crucial to perform quality control of biodiesel, since it is blended into diesel fuel and the presence of contaminants can hinder its performance. This work aimed to compare the performance of a benchtop Fourier Transform (FT) NIR spectrometer with a prototype of a portable, miniaturized near-infrared spectrometer (miniNIR) to detect and quantify contaminants in biodiesel and biodiesel in diesel. In general, good models based on principal component analysis-linear discriminant analysis (PCA-LDA) of FT-NIR spectra were obtained, predicting with high accuracies biodiesel contaminants and biodiesel in diesel (between 75% to 95%), as well as good partial least square (PLS) regression models to predict contaminants concentration in biodiesel and biodiesel concentration in diesel/biodiesel blends, with high coefficients of determination (between 0.83 and 0.99) and low prediction errors. The miniNIR prototype’s PCA-LDA models enabled the prediction of target contaminants with good accuracies (between 66% and 86%), and a PLS model enabled the prediction of biodiesel concentration in diesel with a reasonable coefficient of determination (0.68), pointing to the device’s potential for preliminary analysis of biodiesel which, associated with its potential low cost and portability, could increase biodiesel quality control.

Miniaturized NIR Spectroscopy in Food Analysis and Quality Control: Promises, Challenges, and Perspectives

The ongoing miniaturization of spectrometers creates a perfect synergy with the common advantages of near-infrared (NIR) spectroscopy, which together provide particularly significant benefits in the field of food analysis. The combination of portability and direct onsite application with high throughput and a noninvasive way of analysis is a decisive advantage in the food industry, which features a diverse production and supply chain. A miniaturized NIR analytical framework is readily applicable to combat various food safety risks, where compromised quality may result from an accidental or intentional (i.e., food fraud) origin. In this review, the characteristics of miniaturized NIR sensors are discussed in comparison to benchtop laboratory spectrometers regarding their performance, applicability, and optimization of methodology. Miniaturized NIR spectrometers remarkably increase the flexibility of analysis; however, various factors affect the performance of these devices in different analytical scenarios. Currently, it is a focused research direction to perform systematic evaluation studies of the accuracy and reliability of various miniaturized spectrometers that are based on different technologies; e.g., Fourier transform (FT)-NIR, micro-optoelectro-mechanical system (MOEMS)-based Hadamard mask, or linear variable filter (LVF) coupled with an array detector, among others. Progressing technology has been accompanied by innovative data-analysis methods integrated into the package of a micro-NIR analytical framework to improve its accuracy, reliability, and applicability. Advanced calibration methods (e.g., artificial neural networks (ANN) and nonlinear regression) directly improve the performance of miniaturized instruments in challenging analyses, and balance the accuracy of these instruments toward laboratory spectrometers. The quantum-mechanical simulation of NIR spectra reveals the wavenumber regions where the best-correlated spectral information resides and unveils the interactions of the target analyte with the surrounding matrix, ultimately enhancing the information gathered from the NIR spectra. A data-fusion framework offers a combination of spectral information from sensors that operate in different wavelength regions and enables parallelization of spectral pretreatments. This set of methods enables the intelligent design of future NIR analyses using miniaturized instruments, which is critically important for samples with a complex matrix typical of food raw material and shelf products.

Near-Infrared Hyperspectral Imaging Pipelines for Pasture Seed Quality Evaluation: An Overview

Near-infrared (800–2500 nm; NIR) spectroscopy coupled to hyperspectral imaging (NIR-HSI) has greatly enhanced its capability and thus widened its application and use across various industries. This non-destructive technique that is sensitive to both physical and chemical attributes of virtually any material can be used for both qualitative and quantitative analyses. This review describes the advancement of NIR to NIR-HSI in agricultural applications with a focus on seed quality features for agronomically important seeds. NIR-HSI seed phenotyping, describing sample sizes used for building high-accuracy calibration and prediction models for full or selected wavelengths of the NIR region, is explored. The molecular interpretation of absorbance bands in the NIR region is difficult; hence, this review offers important NIR absorbance band assignments that have been reported in literature. Opportunities for NIR-HSI seed phenotyping in forage grass seed are described and a step-by-step data-acquisition and analysis pipeline for the determination of seed quality in perennial ryegrass seeds is also presented.

Rapid discrimination of Curcuma longa and Curcuma xanthorrhiza using Direct Analysis in Real Time Mass Spectrometry and Near Infrared Spectroscopy

This study describes a newly developed method for the fast and straightforward differentiation of two turmeric species using Direct Analysis in Real Time mass spectrometry and miniaturized Near Infrared spectroscopy. Multivariate analyses (PCA and LDA) were performed on the mass spectrometric data, thus creating a powerful model for the discrimination of Curcumalonga and Curcumaxanthorrhiza. Cross-validation of the model revealed correctness-scores of 100% with 20-fold as well as leave-one-out validation techniques. To further estimate the models prediction power, seven retail samples of turmeric powder were analyzed and assorted to a species. Looking for a fast, non-invasive, cost-efficient and laboratory independent method, miniaturized NIR spectrometers offer an alternative for quality control of turmeric species. However, different technologies implemented to compensate for their small size, lead to different applicability of these spectrometers. Therefore, we investigated the three handheld spectrometers microPHAZIR, MicroNIR 2200 and MicroNIR 1700ES for their application in spice analysis in hyphenation to PCA, LDA and ANN methods used for the discriminant analysis. While microPHAZIR proved to be the most valuable device for differentiating C.longa and C.xanthorrhiza, MicroNIR 1700ES offered the worst results. These findings are interpreted on the basis of a quantum chemical simulation of the NIR spectrum of curcumin as the representative constituent. It was found that the information accessible to MicroNIR 1700ES that is relevant to the analyzed constituents is located in the spectral region prone to interferences with the matrix, likely limiting the performance of this spectrometer in this analytical scenario.

Near-infrared spectra of liquid and gas samples by diffuse reflectance employing benchtop and handheld spectrophotometers

This paper describes a new method to obtain NIR spectra of liquid and gas samples by diffuse reflectance, which is especially suitable for handheld spectrophotometers, since most of these instruments are designed to acquire spectrum using this geometry. The core of the method is a diffuse reflectance cell, which consists of a vial containing a mixture of the liquid or gas sample (rare medium) and a powder (dense medium). Using this strategy, no adaptation is required to measure spectra with most portable NIR spectrometers. This new method was used to obtain NIR spectra of several liquids and gases, which were compared with traditional transmittance spectra. As a proof of concept, measurements of biodiesel/vegetable oil/diesel blends were used to build multivariate calibrations to predict the contents of biodiesel and vegetable oil in diesel blends using benchtop and handheld FT-NIR spectrophotometers. This low-cost method was demonstrated to be suitable for overcoming problems related to the handling of viscous samples and expand the applications with portable NIR instruments.

Quantification of Silymarin in Silybi mariani fructus: Challenging the Analytical Performance of Benchtop vs. Handheld NIR Spectrometers on Whole Seeds

The content of the flavonolignan mixture silymarin and its individual components (silichristin, silidianin, silibinin A, silibinin B, isosilibinin A, and isosilibinin B) in whole and milled milk thistle seeds (Silybi mariani fructus) was analyzed with near-infrared spectroscopy. The analytical performance of one benchtop and two handheld near-infrared spectrometers was compared. Reference analysis was performed with HPLC following a Soxhlet extraction (European Pharmacopoeia) and a more resource-efficient ultrasonic extraction. The reliability of near-infrared spectral analysis determined through partial least squares regression models constructed independently for the spectral datasets obtained by the three spectrometers was as follows. The benchtop device NIRFlex N-500 performed the best both for milled and whole seeds with a root mean square error of CV between 0.01 and 0.17%. The handheld spectrometer MicroNIR 2200 as well as the microPHAZIR provided a similar performance (root mean square error of CV between 0.01 and 0.18% and between 0.01 and 0.23%, respectively). We carried out quantum chemical simulation of near-infrared spectra of silichristin, silidianin, silibinin, and isosilibinin for interpretation of the results of spectral analysis. This provided understanding of the absorption regions meaningful for the calibration. Further, it helped to better separate how the chemical and physical properties of the samples affect the analysis. While the study demonstrated that milling of samples slightly improves the performance, it was deemed to be critical only for the analysis carried out with the microPHAZIR. This study evidenced that rapid and nondestructive quantification of silymarin and individual flavonolignans is possible with miniaturized near-infrared spectroscopy in whole milk thistle seeds.

Spectra-structure correlations in NIR region of polymers from quantum chemical calculations. The cases of aromatic ring, C=O, C≡N and C-Cl functionalities

Near-infrared (NIR) spectroscopy is a valued analytical tool in various applications involving polymers. However, complex nature of NIR spectra imposes difficulties in their direct interpretation. Here, anharmonic quantum chemical calculations are used to simulate NIR spectra of nine polymers; acrylonitrile butadiene styrene (ABS), ethylene-vinyl acetate (EVAC), polycarbonate (PC), polyethylene terephthalate (PET), polylactide or polylactic acid (PLA), polymethylmethacrylate (PMMA), polyoxymethylene (POM), polystyrene (PS) and polyvinylchloride (PVC). The generalized spectra-structure correlations are derived for these systems with focus given to the manifestation in NIR spectra of aromatic ring, C=O, C≡N and C-Cl functionalities. It is concluded that the nature of NIR polymer bands is only moderately sensitive to the remote chemical neighborhood. The majority of NIR absorption of polymers originates from binary combination bands, while the first overtones are meaningful only in ca. 6200-5500 cm^-1 region. The contribution of the overtone bands is relatively higher for the polymers bearing aromatic rings because of higher intensity of C-H stretching overtones. Highly characteristic combination bands of the modes localized in aromatic ring (ring deformation and CH stretching) are relatively independent on the remaining structure of the polymer. The combination bands originating from C=O group are more sensitive to the chemical neighborhood in near proximity, forming a useful fingerprint for a specific polymer. In contrast, the vibrational bands of C≡N functionality are far less useful in NIR region than in infrared (IR) region. With aid of the calculated absorption bands, structural specificity of NIR spectroscopy of polymers can be markedly improved.

Insect Protein Content Analysis in Handcrafted Fitness Bars by NIR Spectroscopy. Gaussian Process Regression and Data Fusion for Performance Enhancement of Miniaturized Cost-Effective Consumer-Grade Sensors

Future food supply will become increasingly dependent on edible material extracted from insects. The growing popularity of artisanal food products enhanced by insect proteins creates particular needs for establishing effective methods for quality control. This study focuses on developing rapid and efficient on-site quantitative analysis of protein content in handcrafted insect bars by miniaturized near-infrared (NIR) spectrometers. Benchtop (Büchi NIRFlex N-500) and three miniaturized (MicroNIR 1700 ES, Tellspec Enterprise Sensor and SCiO Sensor) in hyphenation to partial least squares regression (PLSR) and Gaussian process regression (GPR) calibration methods and data fusion concept were evaluated via test-set validation in performance of protein content analysis. These NIR spectrometers markedly differ by technical principles, operational characteristics and cost-effectiveness. In the non-destructive analysis of intact bars, the root mean square error of cross prediction (RMSEP) values were 0.611% (benchtop) and 0.545–0.659% (miniaturized) with PLSR, and 0.506% (benchtop) and 0.482–0.580% (miniaturized) with GPR calibration, while the analyzed total protein content was 19.3–23.0%. For milled samples, with PLSR the RMSEP values improved to 0.210% for benchtop spectrometer but remained in the inferior range of 0.525–0.571% for the miniaturized ones. GPR calibration improved the predictive performance of the miniaturized spectrometers, with RMSEP values of 0.230% (MicroNIR 1700 ES), 0.326% (Tellspec) and 0.338% (SCiO). Furthermore, Tellspec and SCiO sensors are consumer-oriented devices, and their combined use for enhanced performance remains a viable economical choice. With GPR calibration and test-set validation performed for fused (Tellspec + SCiO) data, the RMSEP values were improved to 0.517% (in the analysis of intact samples) and 0.295% (for milled samples).

Odor-Based Nanomechanical Discrimination of Fuel Oils Using a Single Type of Designed Nanoparticles with Nonlinear Viscoelasticity

Odors are one of the most diverse and complicated gaseous mixtures so that their discrimination is challenging yet attractive because of the rich information about their origin. The more similar the properties of odors are, the more difficult the discrimination becomes. The practical applications, however, often demand such discrimination, especially with a compact sensing platform. In this paper, we show that a nanomaterial designed for a specific type of odors can clearly discriminate them even with a single nanomechanical sensing channel. Fuel oils and their mixture are used as a model target that has similar chemical properties but different compositions mainly consisting of paraffinic, olefinic, naphthenic, and aromatic hydrocarbons. We demonstrate using octadecyl functionalized silica-titania nanoparticles that the difference in the compositions is successfully picked up based on their high affinity for the aliphatic hydrocarbons and alkyl chain length dependent nonlinear viscoelastic behavior. Such a properly designed material is proved to derive sufficient information from a series of analytes to discriminate them even with a single sensing element. This approach provides a guideline to prepare various sensors whose response properties are distinct and optimized depending on applications.

Advances, challenges and perspectives of quantum chemical approaches in molecular spectroscopy of the condensed phase

The purpose of this review is to demonstrate advances, challenges and perspectives of quantum chemical approaches in molecular spectroscopy of the condensed phase. Molecular spectroscopy, particularly vibrational spectroscopy and electronic spectroscopy, has been used extensively for a wide range of areas of chemical sciences and materials science as well as nano- and biosciences because it provides valuable information about structure, functions, and reactions of molecules. In the meantime, quantum chemical approaches play crucial roles in the spectral analysis. They also yield important knowledge about molecular and electronic structures as well as electronic transitions. The combination of spectroscopic approaches and quantum chemical calculations is a powerful tool for science, in general. Thus, our article, which treats various spectroscopy and quantum chemical approaches, should have strong implications in the wider scientific community. This review covers a wide area of molecular spectroscopy from far-ultraviolet (FUV, 120-200 nm) to far-infrared (FIR, 400-10 cm-1)/terahertz and Raman spectroscopy. As quantum chemical approaches, we introduce several anharmonic approaches such as vibrational self-consistent field (VSCF) and the combination of periodic harmonic calculations with anharmonic corrections based on finite models, grid-based techniques like the Numerov approach, the Cartesian coordinate tensor transfer (CCT) method, Symmetry-Adapted Cluster Configuration-Interaction (SAC-CI), and the ZINDO (Semi-empirical calculations at Zerner's Intermediate Neglect of Differential Overlap). One can use anharmonic approaches and grid-based approaches for both infrared (IR) and near-infrared (NIR) spectroscopy, while CCT methods are employed for Raman, Raman optical activity (ROA), FIR/terahertz and low-frequency Raman spectroscopy. Therefore, this review overviews cross relations between molecular spectroscopy and quantum chemical approaches, and provides various kinds of close-reality advanced spectral simulation for condensed phases.

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.

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.

Rapid evaluation on pharmacodynamics of Curcumae Rhizoma based on Micro-NIR and benchtop-NIR

It's far from enough to describe the blood circulation promoting effect of Curcumae Rhizoma (CR), which is widely grown as a functional vegetable or spice in south and southeast Asian countries, and processed Curcumae Rhizoma (PCR), only by disclosing the content of a couple of relative compounds. In this study, the thrombin inhibitory effect as well as 2,2'-azino-bis (3-ethylbenz-thiazoline-6-sulfonic acid) (ABTS) and 2,2-diphenyl-picrylhydrazyl (DPPH) free radical scavenging ability of CR/PCR extracts was investigated, and TANGO Fourier transform near-infrared (FT-NIR, Bruker, Germany)-a benchtop instrument allowing the full range NIR wavelength scanning-and handheld-NIR spectrometer (Micro-NIR, NIR-S-G1, InnoSpectra corporation, China) that can be connected to smart phones were used to realize the rapid detection of pharmacodynamic indicators. model was evaluated based on the determination coefficient (R2), root mean square error (RMSE), standard error of test set (SEP) and ratio of performance to deviation (RPD). The results of pharmacodynamics experiment confirmed for the first time that CR has significant inhibitory effect on thrombin, and the modeling results revealed that Micro-NIR had a good prediction on the antioxidant capacity (ABTS and DPPH free radical clearance) with RPD greater than 3, but showed a general predictive performance on thrombin inhibition ability (RPD = 2.434). In contrast, FT-NIR provided a good prediction for all the three indicators, with R² greater than 0.9 and RPD greater than 4.5. Further insights into the capability of the two devices were obtained by analyzing the wavebands selection work. In the full wavelength range, wavebands related to thrombin inhibition were mainly distributed in the combination area which is out of the reach of handheld Micro-NIR, thus resulting in a decrease in the prediction ability. Therefore, compared to the benchtop-NIR, the detection range of the handheld-NIR is the main factor limiting its capability Based on an overall assessment, handheld NIR spectrometer, by greatly expanding the application scenario of NIR technology, is considered as a useful device with a satisfying predictive ability through model construction.

Challenging handheld NIR spectrometers with moisture analysis in plant matrices: Performance of PLSR vs. GPR vs. ANN modelling

The global demand for natural products grows rapidly, intensifying the request for the development of high-throughput, fast, non-invasive tools for quality control applicable on-site. Moisture content is one of the most important quality parameters of natural products. It determines their market suitability, stability and shelf life and should preferably be constantly monitored. Miniaturized near-infrared (NIR) spectroscopy is a powerful method for on-site analysis, potentially fulfilling this requirement. Here, a feasibility study for applicability and analytical performance of three miniaturized NIR spectrometers and two benchtop instruments was evaluated in that scenario. The case study involved 192 dried plant extracts composed of five different plants harvested in different countries at various times within two years. The reference analysis by Karl Fischer titration determined the water content in this sample set between 1.36% and 6.47%. For the spectroscopic analysis half of the samples were laced with a drying agent to comply with the industry standard. The performance of various calibration models for NIR analysis was evaluated on the basis of root-mean square error of prediction (RMSEP) determined for an independent test set. Partial least squares regression (PLSR), Gaussian process regression (GPR) and artificial neural network (ANN) models were constructed for the spectral sets from each instrument. GPR and ANN models performed superior for all samples measured by handheld spectrometers and for native ones analyzed by benchtop instruments. Moreover, the accuracy penalty when analyzing native samples was lower for GPR and ANN prediction as well. With GPR or ANN calibration, miniaturized spectrometers offered the prediction performance at the level of the benchtop instruments. Therefore, in this analytical application miniaturized spectrometers can be used on-site with no penalty to the performance vs. laboratory-based NIR analysis.

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.

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.

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

Near-infrared (12,500–4,000 cm⁻¹; 800–2,500 nm) spectroscopy is the hallmark for one of the most rapidly advancing analytical techniques over the last few decades. Although it is mainly recognized as an analytical tool, near-infrared spectroscopy has also contributed significantly to physical chemistry, e.g., by delivering invaluable data on the anharmonic nature of molecular vibrations or peculiarities of intermolecular interactions. In all these contexts, a major barrier in the form of an intrinsic complexity of near-infrared spectra has been encountered. A large number of overlapping vibrational contributions influenced by anharmonic effects create complex patterns of spectral dependencies, in many cases hindering our comprehension of near-infrared spectra. Quantum mechanical calculations commonly serve as a major support to infrared and Raman studies; conversely, near-infrared spectroscopy has long been hindered in this regard due to practical limitations. Advances in anharmonic theories in hyphenation with ever-growing computer technology have enabled feasible theoretical near-infrared spectroscopy in recent times. Accordingly, a growing number of quantum mechanical investigations aimed at near-infrared region has been witnessed. The present review article summarizes these most recent accomplishments in the emerging field. Applications of generalized approaches, such as vibrational self-consistent field and vibrational second order perturbation theories as well as their derivatives, and dense grid-based studies of vibrational potential, are overviewed. Basic and applied studies are discussed, with special attention paid to the ones which aim at improving analytical spectroscopy. A remarkable potential arises from the growing applicability of anharmonic computations to solving the problems which arise in both basic and analytical near-infrared spectroscopy. This review highlights an increased value of quantum mechanical calculations to near-infrared spectroscopy in relation to other kinds of vibrational spectroscopy.

Theoretical and technical advancements of near-infrared spectroscopy and its operational impact in industry

This article provides a summary of the plenary lecture given at ICNIRS2017 at Copenhagen, Denmark. In principle, near infrared spectroscopy enjoys increasing popularity due to its possibilities for non-invasive, fast, and simultaneous analysis of chemical and physical parameters. Therefore, more frequently in laboratories, time-consuming classical methods including wet-chemical analysis, chromatography, electrophoresis, etc., get substituted by near infrared spectroscopy approaches. On the other hand, hardly any other discipline in analytical chemistry is making such fast technical and theoretical advancements. One of the major challenges is the development of portable devices based on micro-electro mechanical systems or linear variable filters. It belongs to the responsibility of the near infrared spectroscopist to critically evaluate the performance of those with benchtop instruments. For method development, design of experiment and quantum chemical calculation of spectra can give fundamental support. Finally, serious care is to be taken when methods are transferred into the industrial environment.

Application of benchtop and portable near-infrared spectrometers for predicting the optimum harvest time of Verbena officinalis

This study examined the applicability of near-infrared (NIR) spectroscopy coupled with multivariate data analysis (MVA) to determine the ideal harvest time of Verbena officinalis. NIR analyses were performed non-invasively on the fresh plant material based on the quantification of the key constituents verbenalin and verbascoside. Vibrational spectroscopic measurements were performed applying a conventional NIR benchtop device as well as a laboratory independent handheld NIR spectrometer. A novel high performance liquid chromatography (HPLC) method was applied as a reference method. For both instruments partial least squares (PLS) regression models were established performing cross validations (CV) and test-set validations (TSV). Quality parameters obtained for the benchtop device revealed that the newly established NIR method enabled reliable quantifications of the main compounds verbenalin and verbascoside related to the dried and fresh plant material. The results of the miniaturised spectrometer revealed that accurate quantitative calibration models could be developed for verbascoside achieving a comparable prediction power to the benchtop device. PLS models for verbenalin were less precise suggesting the application of portable devices including a different spectral range and resolution. The work demonstrated the feasibility of NIR vibrational spectroscopy performing direct measurements on pharmaceutically relevant fresh plant material enabling a quick and simple determination of the ideal harvest time of Verbena officinalis.

Critical evaluation of spectral information of benchtop vs. portable near-infrared spectrometers: quantum chemistry and two-dimensional correlation spectroscopy for a better understanding of PLS regression models of the rosmarinic acid content in Rosmarini folium

In the present work the performances of one benchtop and two different types of miniaturized near-infrared (NIR)-spectrometers were tested and compared for the first time by the determination of the rosmarinic acid (RA) content of dried and powdered Rosmarini folium. The recorded NIR spectra were utilized in hyphenation with multivariate data analysis (MVA) to calculate Partial Least Squares (PLS) regression models. Quality parameters obtained from Cross Validation (CV) revealed that the benchtop NIR-device "NIRFlex N-500 FT-NIR spectrometer" achieved the best result with a R2 of 0.91 and a RPD of 3.27. The miniaturized NIR-device "MicroNIR 2200 spectrometer" showed a satisfying calibration quality with a R2 of 0.84 and a RPD of 2.46. The miniaturized NIR-device "ThermoScientific microPHAZIR" with a R2 of 0.73 and a RPD of 1.88 was less precise and needs to be improved. The measured spectra of the different devices were additionally investigated by two-dimensional correlation spectroscopy (2D-COS) analysis, which supported the performed PLS regression models as well as identified the discrepancies for microPHAZIR and MicroNIR 2200 compared to NIRFlex N-500. With the aim to obtain a better understanding of the factors which determine the analyzed PLS regression models, the NIR spectrum of RA was reproduced through application of fully anharmonic quantum chemical calculation. A good agreement between the experimental and theoretical NIR spectra and detailed band assignments of RA were obtained in the 8000-4000 cm-1 wavenumber region. Subsequently, this enabled us to attribute the main influences in the regression coefficients plots. This study demonstrated that the performance of NIR spectroscopy with benchtop and miniaturized devices as a fast and non-invasive technique is able to replace time- and resource-consuming analytical tools. Referring to the developed application of the RA content quantification this work is especially interesting for the continuous growing phytopharmaceutical industry and its quality control. The results reveal the importance of monitoring the performances of available NIR-spectrometers in every analytical area.

iHEART: a miniaturized near-infrared in-line gas sensor using heart-shaped substrate-integrated hollow waveguides

A novel heart-shaped substrate-integrated hollow waveguide (hiHWG) was integrated with a near-infrared micro-spectrometer (μNIR) for sensing natural gases, resulting in an ultra-compact near-infrared gas sensing system - iHEART. The iHEART system was evaluated using two different μNIR spectrometers, and the performance was compared with a laboratory NIR spectrometer for gas analysis based on an acousto-optic tunable filter (AOTF). The spectral data were pre-processed using the 1(st) derivative Savitzky-Golay algorithm, and then used for establishing multivariate regression models based on partial least squares (PLS). The root mean square errors of prediction (RMSEPs) obtained for major components of natural gas with both iHEART systems were similar to those associated with the AOTF spectrophotometer combined with a conventional long-path measurement cell. It was demonstrated that the iHEART system has significant potential for the development of compact in-line gas sensing systems, thus facilitating monitoring of (petro)chemically relevant processes and products. However, the flexibility and modularity of the system also allows tailoring iHEART to a wide range of other relevant analytical measurement scenarios requiring short response times and minute gas sample volumes.

Spectroscopic and Computational Study of Acetic Acid and Its Cyclic Dimer in the Near-Infrared Region

Anharmonic vibrational analysis of near-infrared (NIR) spectra of acetic acid was carried out by anharmonic quantum chemical calculation in a wide concentration range of its CCl4 solution. By predicting vibrational spectra of acetic acid for the first time over a wide NIR region, it was possible to elucidate the influence of the formation of acetic acid cyclic dimer on its NIR spectrum. Quantum chemical simulations were based on coupled cluster and density functional theory quantum methods. Additionally, Møller-Plesset perturbation theory was employed for the additional calculation of hydrogen bonding stabilization energies. An anharmonic vibrational analysis was performed with the use of generalized second-order vibrational perturbation theory (GVPT2). A hybrid approach was assumed, in which monomeric species was treated by CCSD(T)/aug-cc-pVDZ (harmonic approximation) and B3LYP/SNSD (anharmonic approximation) methods. For the cyclic dimer, B3LYP and B2PLYP single and double hybrid functionals, paired with an SNSD basis set, were employed. DFT calculations were augmented with additional empirical dispersion correction. It was found that quantum chemically calculated vibrational modes in the NIR region are in a good agreement with experimental data. The results of anharmonic vibrational analysis were supported by a harmonic shift analysis, for elucidating the very strong anharmonic coupling observed between stretching modes of hydrogen bonded bridge in the cyclic dimer. However, the calculated wavenumbers for combination modes of double hydrogen bonded bridge in the cyclic dimer, which are very sensitive to the formation of hydrogen bonding, were found to be underestimated by quantum chemical methods. Therefore, by band fitting, the wavenumbers and shape parameters for these bands were found, and the modeled spectra were adjusted accordingly. A high accuracy of simulated spectra was achieved, and a detailed analysis of the experimental NIR spectra of acetic acid was possible, with successful identification of numerous experimental bands, including those which originate from concentration effects. It was also found that the main spectral features observed in the NIR spectra of carboxylic acid upon the formation of hydrogen bond should be accounted for combination modes of the stretching and bending vibrations of double hydrogen-bonded bridge in the cyclic dimers of acetic acid.

Recent Developments in Solid-Phase Extraction for Near and Attenuated Total Reflection Infrared Spectroscopic Analysis

A review with more than 100 references on the principles and recent developments in the solid-phase extraction (SPE) prior and for in situ near and attenuated total reflection (ATR) infrared spectroscopic analysis is presented. New materials, chromatographic modalities, experimental setups and configurations are described. Their advantages for fast sample preparation for distinct classes of compounds containing different functional groups in order to enhance selectivity and sensitivity are discussed and compared. This is the first review highlighting both the fundamentals of SPE, near and ATR spectroscopy with a view to real sample applicability and routine analysis. Most of real sample analyses examples are found in environmental research, followed by food- and bioanalysis. In this contribution a comprehensive overview of the most potent SPE-NIR and SPE-ATR approaches is summarized and provided.

A spectroscopic and theoretical study in the near-infrared region of low concentration aliphatic alcohols

The near-infrared (NIR) spectra of low-concentration (5 × 10⁻³ M) solutions in CCl₄ of basic aliphatic alcohols, methanol, ethanol, and 1-propanol were, for the first time, calculated by second-order vibrational perturbation theory computations and were compared with the corresponding experimental data.

On-line quantitative monitoring of liquid-liquid extraction of Lonicera japonica and Artemisia annua using near-infrared spectroscopy and chemometrics

BACKGROUND

Liquid-liquid extraction of Lonicera japonica and Artemisia annua (JQ) plays a significant role in manufacturing Reduning injection. Many process parameters may influence liquid-liquid extraction and cause fluctuations in product quality.

OBJECTIVE

To develop a near-infrared (NIR) spectroscopy method for on-line monitoring of liquid-liquid extraction of JQ.

MATERIALS AND METHODS

Eleven batches of JQ extraction solution were obtained, ten for building quantitative models and one for assessing the predictive accuracy of established models. Neochlorogenic acid (NCA), chlorogenic acid (CA), cryptochlorogenic acid (CCA), isochlorogenic acid B (ICAB), isochlorogenic acid A (ICAA), isochlorogenic acid C (ICAC) and soluble solid content (SSC) were selected as quality control indicators, and measured by reference methods. NIR spectra were collected in transmittance mode. After selecting the spectral sub-ranges, optimizing the spectral pretreatment and neglecting outliers, partial least squares regression models were built to predict the content of indicators. The model performance was evaluated by the coefficients of determination (R (2)), the root mean square errors of prediction (RMSEP) and the relative standard error of prediction (RSEP).

RESULTS

For NCA, CA, CCA, ICAB, ICAA, ICAC and SSC, R (2) was 0.9674, 0.9704, 0.9641, 0.9514, 0.9436, 0.9640, 0.9809, RMSEP was 0.0280, 0.2913, 0.0710, 0.0590, 0.0815, 0.1506, 1.167, and RSEP was 2.32%, 4.14%, 3.86%, 5.65%, 7.29%, 6.95% and 4.18%, respectively.

CONCLUSION

This study demonstrated that NIR spectroscopy could provide good predictive ability in monitoring of the content of quality control indicators in liquid-liquid extraction of JQ.