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The humankind is pretty dependent on food to control several biological processes into the organism. As the world population increases, the demand for foodstuffs follows the same trend claiming for a high food production situation. For this reason, a substantial amount of chemicals is used in agriculture and livestock husbandries every year, enhancing the likelihood of contaminated foodstuffs being commercialized. This outlook becomes a public health concern; thus, the governmental regulatory agencies impose laws to control the residues and contaminants in food matrices. Currently, one of the most important analytical techniques to perform it is LC. Despite its already recognized effectiveness, it is often time consuming and requires significant volumes of reagents, which are transformed into toxic waste. In this context, miniaturized LC modes emerge as a greener and more effective analytical technique. They have remarkable advantages, including higher sensitivity, lower sample amount, solvent and stationary phase requirements, and more natural coupling to MS. In this review, most of the critical characteristics of them are discussed, focusing on the benchtop instruments and their related analytical columns. Additionally, a discussion regarding the last 10 years of publications reporting miniaturized LC application for the analysis of natural and industrial food samples is categorized. The main chemical classes as applied in the crops are highlighted, including pesticides, veterinary drugs, and mycotoxins.

Raman spectroscopy is a nondestructive and in situ analytical technique that could provide information on the chemical structure and structural ordering of carbonaceous materials. Based on theE(2g)symmetric stretching vibration mode in the aromatic layers (G band, ~1,580 cm(-1)) and the defect structure in graphite (D band, ~1,350 cm(-1)), Raman spectroscopy has been used extensively to characterize the structural features of carbonaceous matters since 1970. Coal is a complex organic compound made up mainly by carbon showing characteristic Raman bands. This article reviews the application of Raman spectroscopy for coal structure characterization under room temperature, to determine its chemical structure, crystallite size, coal rank, and combustion reactivity. Future research for collecting Raman spectra during coal pyrolysis at high temperatures is also discussed. The combination of high-temperature hot stage with Raman spectroscopy technology allows direct collection of Raman spectra at high temperature.

Quantitative nuclear magnetic resonance (qNMR) is an analytical technique that offers numerous advantages in pharmaceutical applications including minimum sample preparation and rapid data collection times with no need for response factor corrections, being a powerful tool for assaying drug content in both drug discovery and early drug development. In the present work, we have applied qNMR, using both the internal standard and the electronic reference to access in vivo concentrations 2 calibration methods, to assess the purity of RI76, a novel antifungal drug candidate. NMR acquisition and processing parameters were optimized in order to obtain spectra with intense, well-resolved signals of completely relaxed nuclei. The analytical method was validated following current guidelines, demonstrating selectivity, linearity, accuracy, precision, and robustness. The calibration approaches were statistically compared, and no significant difference was observed when comparing the obtained results and their dispersion in terms of relative standard deviation. The proposed qNMR method may, therefore, be used for both qualitative and quantitative assessments of RI76 in early drug development and for characterization of this compound.

Electrospray ionization mass spectrometry (ESI-MS) is an analytical technique that measures the mass of a sample through "soft" ionization. Recent years have witnessed a rapid growth of its application in noble-metal nanocluster (NC) analysis. ESI-MS is able to provide the mass of a noble-metal NC analyte for the analysis of their composition (n, m, q values in a general formula [Mn Lm ]q ), which is crucial in understanding their properties. This review attempts to present various developed techniques for the determination of the composition of noble metal NCs by ESI-MS. Additionally, advanced applications that use ESI-MS to further understand the reaction mechanism, complexation behavior, and structure of noble metal NCs are introduced. From the comprehensive applications of ESI-MS on noble-metal NCs, more possibilities in nanochemistry can be opened up by this powerful technique.

The manufacture of biotherapeutic proteins consists of complex upstream unit operations requiring multiple raw materials, analytical techniques, and control strategies to produce safe and consistent products for patients. Raman spectroscopy is a ubiquitous multipurpose analytical technique in biopharmaceutical manufacturing for real-time predictions of critical parameters in cell culture processes. The accuracy of Raman spectroscopy relies on chemometric models that need to be carefully calibrated. The existing calibration procedure is nontrivial to implement as it necessitates executing multiple carefully designed experiments for generating relevant calibration sets. Further, existing procedure yields calibration models that are reliable only in operating conditions they were calibrated in. This creates a unique challenge in clinical manufacturing where products have limited production history. In this paper, a novel machine-learning procedure based on just-in-time learning (JITL) is proposed to calibrate Raman models. Unlike traditional techniques, JITL-based generic Raman models can be reliably used for different modalities, cell lines, culture media, and operating conditions. The accuracy of JITL-based generic models is demonstrated on several validation studies involving real-time predictions of critical cell culture performance parameters, such as glucose, glutamate, glutamine, ammonium, lactate, sodium, calcium, viability, and viable cell density. The proposed JITL framework introduces a paradigm shift in the way industrial Raman models are calibrated, which to the best of authors' knowledge have not been done before.

Nuclear magnetic resonance (NMR) is a well-known analytical technique for the analysis of complex mixtures. Its quantitative capability makes it ideally suited to metabolomics or lipidomics studies involving large sample collections of complex biological samples. To overcome the ubiquitous limitation of spectral overcrowding when recording 1D NMR spectra on such samples, the acquisition of 2D NMR spectra allows a better separation between overlapped resonances while yielding accurate quantitative data when appropriate analytical protocols are implemented. Moreover, the experiment duration can be considerably reduced by applying fast acquisition methods. Here, we describe the general workflow to acquire fast quantitative 2D NMR spectra in the "omics" context. It is illustrated on three representative and complementary experiments: UF COSY, ZF-TOCSY with nonuniform sampling, and HSQC with nonuniform sampling. After giving some details and recommendations on how to apply this protocol, its implementation in the case of targeted and untargeted metabolomics/lipidomics studies is described.

Inorganic polymers in aqueous solutions are being proposed as essential components in new theories concerning nonclassical nucleation and growth of nanominerals relevant to environmental nanogeosciences. The study of those complex natural processes requires multi-technique analytical approaches able to characterize the solutions and their constituents (solutes, oligomers, polymers, clusters and nanominerals) from atomic to micrometric scales. A novel analytical approach involving an electrospray ionization source (ESI) coupled to time-of-flight mass spectrometry (TOF/MS) was developed to identify inorganic polymers in aqueous solution. To this end, the presence of initial Al oligomers and their polymerization processes was studied during a nanomineral aqueous synthesis (hydrobasaluminte, Al4 SO4 (OH)10 ·12-36H2 O). Ensuring the feasibility and robustness of the methodology as well as the stability of the polymers under study (avoiding undesirable fragmentation), a meticulous study of the ESI-TOF MS working conditions was performed. Precision of the methodology was evaluated obtaining relative standard deviations below 3.3%. For the first time in the study of inorganic polymers in the earth sciences, the mass accuracy error (ppm) has been reported and the use of significant decimal figures of the m/z signal has been taken into account. Complementary to this, a four-step polymer assignment methodology and a database with the Al- and Al-SO42- polymers assigned were created. Several polymers have been assigned for the first time, including Al (SO4 )+ ·H2 O, Al2 O(SO4 )2+ ·H2 O, Al5 O4 (OH)52+ ·2H2 O, and Al3 O5 (OH)2- ·4H2 O, among others. The results obtained in the present study help create a foundation to include mass spectrometry as a routine analytical technique to study mineral formation in aqueous solution.

A significant hurdle in conducting effective health and safety hazard analysis and risk assessment for the nanotechnology workforce is the lack of a rapid method for the direct visualization and analysis of filter media used to sample nanomaterials from work environments that represent potential worker exposure. Current best-known methods include transmission electron microscopy (TEM) coupled with energy dispersive x-ray spectroscopy (EDS) for elemental identification. TEM-EDS is considerably time-, cost-, and resource-intensive, which may prevent timely health and safety recommendations and corrective actions. A rapid screening method is currently being explored using enhanced darkfield microscopy with hyperspectral imaging (EDFM-HSI). For this approach to be effective, rapid, and easy, sample preparation that is amenable to the analytical technique is needed. Here, we compare the sample preparation steps for mixed cellulose ester (MCE) filter media specified in NIOSH Method 7400-Asbestos and Other Fibers by Phase Contrast Microscopy (PCM)-against a new method, which involves saturation of the filter media with acetone. NIOSH Method 7400 was chosen as a starting point since it is an established technique for preparing transparent MCE filters for optical microscopy. Limitations in this method led to the development and comparison of a new method. The new method was faster, easier, and rendered filters more transparent, resulting in improved visualization and analysis of nanomaterials via EDFM-HSI. This new method is suitable for a rapid screening protocol due to its speed, ease of use, and the improvement in image acquisition and analysis.

Fluorinated coatings, often used for oil and water repellency and stain resistance in fabrics, are potentially persistent forensic fiber markers. However, they have received limited attention because of challenges in their detection caused by the small size of a single fiber and thin nature of stain-resistant coatings. Here, we utilize a sensitive fluorine-selective analytical technique to detect and evaluate diversity of fluorinated coatings in apparel. Twelve clothing items marketed as stain-resistant were tested with nine showing oil- and water-repellent properties. Fluorinated pyrolysis products of single fibers from all of the nine items were detected by gas chromatography coupled to plasma-assisted reaction chemical ionization mass spectrometry (GC-PARCI-MS), indicating the prevalence of fluoropolymer coatings in stain-resistant clothing articles. Furthermore, three major classes of fluorinated coatings were identified via principal component analysis of pyrogram patterns. The classes were coating-specific and did not correlate with fiber core and color, highlighting a robust detection methodology. To evaluate the effect of fiber lifting in crime scenes, fibers from the 9 clothing items were used to develop a multinomial logistic regression model based on pyrogram principal components. The model was then tested using fibers subjected to contact with Post-it® notes. The test set fibers were sampled from the clothing items of the training set and from three additional garments of differing color but the same brands as the training set. The coating classes were predicted with 98.4% accuracy, confirming robust classification of fiber coatings using py-GC-PARCI-MS regardless of fiber color, core, and fiber lifting.

Elemental metals are critical raw material attributes which can impact cell culture performance and associated therapeutic protein product quality profiles. Metals such as copper and manganese act as cofactors and reagents for numerous metabolic pathways which govern cell growth, protein expression, and glycosylation, thus mandating elemental monitoring. The growing complexity of modern cell culture media formulations adds additional opportunities for elemental variance and its associated impact risks. This article describes an analytical technique applying inductively coupled plasma mass spectrometry to characterize a list of common raw materials and media powders used in mammalian cell culture and therapeutic protein production. We aim to describe a method qualification approach suitable for biopharmaceutical raw materials. Furthermore, we present detailed profiles of many common raw materials and discuss trends in raw material subtypes. Finally, a case study demonstrating the impact of an unexpected source of raw material variation is presented along with recommendations for raw material elemental risk profiling and control.

While liquid chromatography/high-resolution mass spectrometry (LC/HRMS) is a versatile analytical technique, it is also sensitive to trace impurities. These impurities may come from a variety of sources, including reagents, solvents, and the sample matrix itself. Impurities in reagents may become concentrated and elute as peaks when a gradient method is used, and these peaks may cause suppression of peaks of interest both in the electrospray source, as well as in the C-trap in systems that contain one. Methods We observed a notable increase in the size of several impurity peaks in a reversed-phase gradient method upon switching suppliers of formic acid. We used LC/HRMS to separate and fragment these impurity compounds and assign probable formulae. Results The mass spectra were compared with those of compounds found in the literature with the same formulae, and the observed peaks were matched to two amine compounds not previously reported as impurities in LC/MS systems: trihexylamine and N-methyldihexylamine. The identities were confirmed by high-resolution accurate mass and retention time matching against commercially available standards of these compounds. Conclusions To the best of our knowledge, this is the first time that trihexylamine and N-methyldihexylamine have been reported in such systems. We hypothesize that these are derived from the formic acid manufacturing process and recommend that users monitor purchased formic acid for the presence of impurities.

Capillary electrophoresis (CE) offers fast and high-resolution separation of charged analytes from small injection volumes. Coupled to mass spectrometry (MS), it represents a powerful analytical technique providing (exact) mass information and enables molecular characterization based on fragmentation. Although hyphenation of CE and MS is not straightforward, much emphasis has been placed on enabling efficient ionization and user-friendly coupling. Though several interfaces are now commercially available, research on more efficient and robust interfacing with nano-electrospray ionization (ESI), matrix-assisted laser desorption/ionization (MALDI) and inductively coupled plasma mass spectrometry (ICP) continues with considerable results. At the same time, CE-MS has been used in many fields, predominantly for the analysis of proteins, peptides and metabolites. This review belongs to a series of regularly published articles, summarizing 248 articles covering the time between June 2016 and May 2018. Latest developments on hyphenation of CE with MS as well as instrumental developments such as two-dimensional separation systems with MS detection are mentioned. Furthermore, applications of various CE-modes including capillary zone electrophoresis (CZE), nonaqueous capillary electrophoresis (NACE), capillary gel electrophoresis (CGE) and capillary isoelectric focusing (CIEF) coupled to MS in biological, pharmaceutical and environmental research are summarized.

Ion mobility spectrometry (IMS) is an analytical technique used for fast and sensitive detection of illegal substances in customs and airports, diagnosis of diseases through detection of metabolites in breath, fundamental studies in physics and chemistry, space exploration, and many more applications. Ion mobility spectrometry separates ions in the gas-phase drifting under an electric field according to their size to charge ratio. Ion mobility spectrometry disadvantages are false positives that delay transportation, compromise patient's health and other negative issues when IMS is used for detection. To prevent false positives, IMS measures the ion mobilities in 2 different conditions, in pure buffer gas or when shift reagents (SRs) are introduced in this gas, providing 2 different characteristic properties of the ion and increasing the chances of right identification. Mobility shifts with the introduction of SRs in the buffer gas are due to clustering of analyte ions with SRs. Effective SRs are polar volatile compounds with free electron pairs with a tendency to form clusters with the analyte ion. Formation of clusters is favored by formation of stable analyte ion-SR hydrogen bonds, high analytes' proton affinity, and low steric hindrance in the ion charge while stabilization of ion charge by resonance may disfavor it. Inductive effects and the number of adduction sites also affect cluster formation. The prediction of IMS separations of overlapping peaks is important because it simplifies a trial and error procedure. Doping experiments to simplify IMS spectra by changing the ion-analyte reactions forming the so-called alternative reactant ions are not considered in this review and techniques other than drift tube IMS are marginally covered.

The purpose of this work is to introduce a new method for quantitatively analyzing water absorption capacity in wheat flour by a headspace gas chromatographic technique. This headspace gas chromatographic technique was based on measuring the water vapor released from a series of wheat flour samples with different contents of water addition. According to the different trends between the vapor and wheat flour phase before and after the water absorption capacity in wheat flour, a turning point (corresponding to water absorption capacity in wheat flour) can be obtained by fitting the data of the water gas chromatography peak area from different wheat flour samples. The data showed that the phase equilibrium in the vial can be achieved in 25 min at desired temperature (35°C). The relative standard deviation of the reaction headspace gas chromatographic technique in water absorption capacity determination was within 3.48%, the relative differences has been determined by comparing the water absorption capacity obtained from this new analytical technique with the data from the reference technique (i.e., the filtration method), which are less than 8.92%. The new headspace gas chromatographic method is automated, accurate and be a reliable tool for quantifying water absorption capacity in wheat flour in both laboratory research and mill applications.

A fast and reliable analytical technique for the determination of total sulfur levels in complex hydrocarbon matrices is introduced. The method employed flow injection technique using a gas chromatograph as a sample introduction device and a gas phase dual-plasma sulfur chemiluminescence detector for sulfur quantification. Using the technique described, total sulfur measurement in challenging hydrocarbon matrices can be achieved in less than 10 s with sample-to-sample time of less than 2 min. The high degree of selectivity and sensitivity towards sulfur compounds of the detector offers the ability to measure low sulfur levels with a detection limit in the range of 20 ppb (w/w) S. The equimolar response characteristic of the detector allows the quantitation of unknown sulfur compounds and simplifies the calibration process. Response is linear over a concentration range of five orders of magnitude, with a high degree of repeatability. The detector's lack of response to hydrocarbons enables direct analysis without the need for time-consuming sample preparation and chromatographic separation processes. This flow injection based sulfur chemiluminescence detection technique is ideal for fast analysis or trace sulfur analysis. This article is protected by copyright. All rights reserved

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is a high throughput, easy to use analytical technique. The simple sample preparation of this technique and its tolerance to the presence of contaminants are among its advantages. In contrast, depending on the matrix used, MALDI can ionize and generates ions in the low m/z range that complicate the interpretation of the spectra of low molecular weight compounds. To address this issue, one can envisage the use of tunable ionic matrices that can reduce the low m/z interferents. In this work, the ionic matrices triethylammonium α-cyano-4-hydroxycinnamate and diisopropylammonium α-cyano-4-hydroxycinnamate were used to directly analyze 14 pharmaceutical drugs in different formulations (coated tablets, noncoated tablets, capsules, and solutions). This methodology enabled the detection of their active compounds with minimum sample preparation, thus providing a straightforward approach for the forensic analysis of pharmaceutical drugs in the quest for detecting counterfeits. LDI-MS experiments were also performed, and the active ingredient in all of the medicines analyzed were detected. However, MALDI-MS spectra for the medicines analyzed herein showed less or no fragmentation than LDI-MS, which makes the analysis easier.

Identification of monosaccharide derivatives using an analytical technique is difficult due to their isomeric structures and similar physical properties. Although mass spectrometry (MS) has emerged as a prominent technique for this purpose, a comprehensive MS-based method for analyzing diverse monosaccharide species is yet to be developed. Herein, we employ host-guest chemistry using cucurbit[7]uril (CB[7]) with MS to identify four different monosaccharide derivative species. Tandem MS analysis distinguishes the monosaccharide derivatives based on the unique fragmentation pattern produced when forming gas-phase complexes with CB[7]. The ion mobility studies combined with computational calculations reveal that subtle differences in isomers cause distinct orientations inside CB[7] cavity, resulting in different fragmentation patterns of the isomers. This unique study demonstrates that host-guest chemistry combined with MS can be used for developing effective isomer analysis techniques.

Raman spectroscopy is a very powerful analytical technique with an increasing acceptance in the scientific community. For the optimization of the Raman acquisition, two main parameters, the integration time and the number of accumulations, need to be adjusted to the sample under analysis, as the sample, or even different spots on the same sample, can provide very different Raman responses one from another. In this paper, we present a suite of algorithms to automate the acquisition parameter adjustment to the sample under analysis, addressing issues such as spectral saturation, fluorescence, cosmic ray detection and removal, and adjustment of the acquisition parameters to optimize the acquired spectral data. This suite has been developed in the framework of the Raman Laser Spectrometer (RLS) instrument development for the Exomars mission but can be applied to any Raman spectrometer. This will allow the spectrometer to adapt to the characteristics of the sample that is being analyzed, optimizing the total operative time, while improving the usability and overall efficiency of the system. Copyright © 2017 John Wiley & Sons, Ltd.

Gas chromatography-mass spectrometry (GC-MS) is an important analytical technique for the analysis of organophosphorus pesticides in food products. Because of the complex matrices of food products, multiple preprocessing steps are required prior to performing the GC-MS analysis. Despite that, it is difficult to totally eliminate the interference of complex matrix background. In this work, we introduce an entropy minimization technique that can eliminate the need for comprehensive preprocessing steps to detect organophosphorus pesticides in a fortified orange juice sample. The pure mass spectra and extracted-ion chromatograms of the pesticides were extracted and reconstructed. The results achieved higher National Institute of Standard and Technology (NIST) match scores in comparison to the conventional background subtraction technique. Taken together, the entropy minimization technique is capable of providing rapid qualitative and quantitative analyses of complex GC-MS data. This technique is expected to have great potential for natural products and food analysis applications.

The automatic analysis of NMR data has been a much-desired endeavour for the last six decades, as it is the case with any other analytical technique. This need for automation has only grown as advances in hardware; pulse sequences and automation have opened new research areas to NMR and increased the throughput of data. Full automatic analysis is a worthy, albeit hard, challenge, but in a world of artificial intelligence, instant communication and big data, it seems that this particular fight is happening with only one technique at a time (let this be NMR, MS, IR, UV or any other), when the reality of most laboratories is that there are several types of analytical instrumentation present. Data aggregation, verification and elucidation by using complementary techniques (e.g. MS and NMR) is a desirable outcome to pursue, although a time-consuming one if performed manually; hence, the use of automation to perform the heavy lifting for users is required to make the approach attractive for scientists. Many of the decisions and workflows that could be implemented under automation will depend on the two-way communication with databases that understand analytical data, because it is desirable not only to query these databases but also to grow them in as much of an automatic manner as possible. How these databases are designed, set up and the data inside classified will determine what workflows can be implemented. Copyright © 2016 John Wiley & Sons, Ltd.

Mass spectrometry imaging (MSI) is a label-free analytical technique capable of molecularly characterizing biological samples, including tissues and cell lines. The constant development of analytical instrumentation and strategies over the previous decade makes MSI a key tool in clinical research. Nevertheless, most MSI studies are limited to targeted analysis or the mere visualization of a few molecular species (proteins, peptides, metabolites, or lipids) in a region of interest without fully exploiting the possibilities inherent in the MSI technique, such as tissue classification and segmentation or the identification of relevant biomarkers from an untargeted approach. MSI data processing is challenging due to several factors. The large volume of mass spectra involved in a MSI experiment makes choosing the correct computational strategies critical. Furthermore, pixel to pixel variation inherent in the technique makes choosing the correct preprocessing steps critical. The primary aim of this review was to provide an overview of the data-processing steps and tools that can be applied to an MSI experiment, from preprocessing the raw data to the more advanced strategies for image visualization and segmentation. This review is particularly aimed at researchers performing MSI experiments and who are interested in incorporating new data-processing features, improving their computational strategy, and/or desire access to data-processing tools currently available. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 37:281-306, 2018.

In this study, a simple effervescence-assisted dispersive solid-phase extraction method was developed to detect fungicides in honey and juice. Most significantly, an innovative ionic-liquid-modified magnetic β-cyclodextrin/attapulgite sorbent was used because its large specific surface area enhanced the extraction capacity and also led to facile separation. A one-factor-at-a-time approach and orthogonal design were employed to optimize the experimental parameters. Under the optimized conditions, the entire extraction procedure was completed within 3 min. In addition, the calibration curves exhibited good linearity, and high enrichment factors were achieved for pure water and honey samples. For the honey samples, the extraction efficiencies for the target fungicides ranged from 77.0 to 94.3% with relative standard deviations of 2.3–5.44%. The detection and quantitation limits were in the ranges of 0.07–0.38 and 0.23–1.27 μg·L−1, respectively. Finally, the developed technique was successfully applied to real samples, and satisfactory results were achieved. This analytical technique is cost-effective, environmentally friendly, and time-saving. This article is protected by copyright. All rights reserved

RATIONALE Time-of-Flight (TOF) Mass Spectrometry is a powerful analytical technique, provided that an accurate calibration by standard molecules in the same m/z range of the analytes is performed. Calibration in a very large m/z range is a difficult task, particularly in studies focusing on the detection of high molecular weight clusters of different molecules or high molecular weight species. METHODS External calibration is the most common procedure used for TOF mass spectrometric analysis in the gas phase and, generally, the only available standards are made up of mixtures of noble gases, covering a small mass range for calibration, up to m/z 136 (higher mass isotope of xenon). In this work, an accurate calibration of a Molecular Beam Time-of Flight Mass Spectrometer (MB-TOFMS) is presented, based on the use of water clusters up to m/z 3000. RESULTS The advantages of calibrating a MB-TOFMS with water clusters for the detection of analytes with masses above those of the traditional calibrants such as noble gases were quantitatively shown by statistical calculations. A comparison of the water cluster and noble gases calibration procedures in attributing the masses to a test mixture extending up to m/z 800 is also reported. In the case of the analysis of combustion products, another important feature of water cluster calibration was shown, that is the possibility of using them as "internal standard" directly formed from the combustion water, under suitable experimental conditions. CONCLUSIONS The water clusters calibration of a MB-TOFMS gives rise to a ten-fold reduction in error compared to the traditional calibration with noble gases. The consequent improvement in mass accuracy in the calibration of a MB-TOFMS has important implications in various fields where detection of high molecular mass species is required. In combustion products analysis, it is also possible to obtain a new calibration spectrum before the acquisition of each spectrum, only modifying some operative conditions. Copyright © 2016 John Wiley & Sons, Ltd.

Near infrared (NIR) spectroscopy is an efficient, low-cost analytical technique widely applied to identify the origin of food and pharmaceutical products. NIR spectra-based classification strategies typically use thousands of equally spaced wavelengths as input information, some of which may not carry relevant information for product classification. When that is the case, the performance of predictive and exploratory multivariate techniques may be undermined by such noisy information. In this paper, we propose an iterative framework for selecting subsets of NIR wavelengths aimed at classifying samples into categories. For that matter, we integrate Principal Components Analysis (PCA) and three classification techniques: k-Nearest Neighbor (KNN), Probabilistic Neural Network (PNN) and Linear Discriminant Analysis (LDA). PCA is first applied to NIR data, and a wavelength importance index is derived based on the PCA loadings. Samples are then categorized using the wavelength with the highest index and the classification accuracy is calculated; next, the wavelength with the second highest index is inserted into the dataset and a new classification is performed. This forward-based iterative procedure is carried out until all original wavelengths are inserted into the dataset used for classification. The subset of wavelengths leading to the maximum accuracy is chosen as the recommended subset. Our propositions performed remarkably well when applied to four datasets related to food and pharmaceutical products. Copyright © 2016 John Wiley & Sons, Ltd.

Rationale Desorption electrospray ionization (DESI) imaging is a fast analytical technique used to assess spatially resolved biological processes over unmodified sample surfaces. Although DESI profiling experiments have demonstrated that the properties of the sample surface significantly affect the outcomes of DESI analyses, the potential implications of these phenomena in imaging applications have not yet been explored extensively. Methods The distribution of endogenous and exogenous organic acids in pith and out pith region of grapevine stems was investigated by using DESI imaging, ion chromatography and direct infusion methods. Several common normalization strategies to account for the surface effect, including TIC normalization, addition of the internal standard in the spray solvent and deposition of the standard over the sample surface, were critically evaluated. Results DESI imaging results show that, in our case, the measured distributions of these small organic acids are not consistent with their 'true' localizations within the tissues. Furthermore, our results indicate that the common normalization strategies are not able to completely compensate for the observed surface effect. Conclusions Variations in the tissue surface properties across the tissue sample can greatly affect the semi-quantitative detection of organic acids. Attention should be paid when interpreting DESI imaging results and an independent analytical validation step is important in untargeted DESI imaging investigations. Copyright © 2016 John Wiley & Sons, Ltd.

The analytical methods used for routine moisture determination are based on a loss on drying (LOD) approach performed by conventional heating in ovens, but infrared loss on drying (IRLOD) and microwave-assisted loss on drying (MALOD) drying methods have been used to reduce the analysis time. MALOD speeds up water removal from meat products 64 times in comparison to LOD and provided similar results (agreement between 98 and 101%), but with lower energy consumption (

Surface-enhanced Raman scattering (SERS) is increasingly becoming an important analytical technique in various fields, which can mostly be attributed to the significant evolution of SERS-active substrates. The semiconductor-based SERS technique is particularly interesting because the inherent physicochemical properties of semiconductor materials offer several possibilities for the development and improvement of SERS-based analytical techniques. According to the effect of the semiconductor materials in SERS, semiconductor-based SERS techniques can be categorized into two areas: (1) semiconductor-enhanced Raman scattering, in which a semiconductor material is directly used as a substrate for enhancing Raman signals of adsorbed molecules, and (2) semiconductor-mediated-enhanced Raman scattering, in which a semiconductor is employed as an ‘antenna’ or ‘trap’ to modulate the Raman enhancement originating from a metal substrate. While the theory on semiconductor-based SERS is still incomplete and evolving, semiconductor-based SERS techniques have already resulted in substantial progress in biological analysis, photocatalysis, solar cells, sensing, and optoelectronic devices. The aim of this review is to outline the recent progress in this emerging research field, with a special emphasis on its analytical performance and application areas. Copyright © 2015 John Wiley & Sons, Ltd.

For decades Raman spectroscopy has been used as a specialized tool in a variety of fields. Forensic science is one discipline in particular that has greatly benefited from the application of Raman spectroscopic research. Here, studies using Raman spectroscopy for analyzing criminalistic evidence, including body fluids, human tissue, bones, gunshot residue, fibers, and hair, are reviewed. Many of these methods demonstrate the significance of incorporating chemometrics for data analysis to provide more reliable and quantitative results with associated errors. Currently, there are only a few branches of forensic science that use Raman spectroscopy in practice, despite its wide range of advantages. However, many more applications have been developed in the research setting and are presented here. These studies showcase the versatility and dependability of Raman spectroscopy, specifically for criminalistic purposes. The advantages of developing and transitioning these techniques to be used in practice are also discussed, including the tremendous benefits of portable instrumentation. Raman spectroscopy can easily become an established analytical technique for many criminalistics disciplines because it allows for obtaining real-time, rapid, impartial, statistically confident results. Consequently, the improvements to forensic science as a whole will be revolutionary. Copyright © 2015 John Wiley & Sons, Ltd.

Since its introduction in the cultural heritage field, nearly 30 years ago, surface-enhanced Raman spectroscopy (SERS) has emerged as a promising analytical technique that is particularly suitable for the detection and identification of organic colorants. Its great molecular selectivity and specificity, and unparalleled sensitivity compared to other instrumental methods, have allowed researchers to successfully characterize a wide number of natural dyes and a few synthetic ones in microscopic samples from objects of artistic, historical, and archaeological significance. Continued research over the course of the past decade has led to the construction of comprehensive databases of dyes, whose adsorption and spectral properties have been investigated at length; to the comparative study of the efficiency and performance of various metal substrates; and to the evaluation of several sample treatment methods and ad-hoc analytical protocols. In addition, recent literature in the field of SERS for art and archaeology has described instrumentation and technique advancements aimed at solving the unique challenges posed by the analysis of irreplaceable objects, namely, quasi non-destructive sampling, spatial resolution improvement, examination of insoluble compounds, and resolution of dye mixtures. Reviewing the most salient methodological and technological milestones that have traced the history of SERS for cultural heritage to date, the present article is intended as a practical resource for those researchers who would like to undertake systematic characterization of organic colorants from artworks using this powerful technique. Copyright © 2015 John Wiley & Sons, Ltd.

The classical traditional Chinese formulation LiuweiDihuang, shown to have clinical efficacy for "nourishing kidney-yin" in traditional Chinese medicine, has been used for thousands of years in China. Little attention, however, has been paid to quality control methods for this formulation. Hence, a rapid and sensitive analytical technique is urgently needed for the evaluation of LiuweiDihuang preparations to assess its quality and pharmacological functionality. In this study, an ultra high performance liquid chromatography dual-wavelength method was developed to simultaneously determine 11 constituents in LiuweiDihuang preparations. This robust approach provided a fast and comprehensive quantitative determination of the major bioactive markers within LiuweiDihuang preparations. To distinguish four dosage forms of LiuweiDihuang preparations, a random forest technique was applied on the spectrometric fingerprint data obtained. This combination approach of chromatographic techniques and data analyses might serve as a rapid and efficient tool to ensure the quality of LiuweiDihuang preparations and other Chinese medicinal formulations and can support quality control and scientific research into the pharmacological potential for these formulations.

To improve the quality of transistor modeling, the nonlinear behavior of each element of the equivalent circuit must be known. There are few works devoted to the extraction of bias-dependent drain resistance Rd, which strongly affects the transistor modeling. In this work, a new analytical technique for the extraction of bias-dependent drain resistance in HEMT small signal model (SSM) is proposed. The efficiency of the new technique is demonstrated for GaN and GaAs HEMTs. It is shown that the new approach leads to the better SSM accuracy in the range of DC biases as compared to the widespread extraction methods. © 2015 Wiley Periodicals, Inc. Microwave Opt Technol Lett 55:2536–2539, 2015

Summary Benzylglucosinolate (BG) was extracted by 70% methanol from maca and purified on acidic alumina column and semi-preparative Cosmosil cholester column. The purified sample was verified as BG by electrospray ionisation mass spectrometry (ESI-MS) and nuclear magnetic resonance spectra. The purity was 98.3% as determined by HPLC-MS. BG content of maca was quantified using external standard method by HPLC. Effect of physical and thermal processing on BG content of maca was investigated. When maca was steamed for 5 min before shredding, no significant difference of BG content was observed during postshredding time, while raw maca lost 57.2% of BG in 24 h. Steamed maca showed no significant loss of BG after drying at the temperature from 20 to 80 °C in 24 h. Thermal degradation was described by the first-order kinetics–Arrhenius equation for BG in the temperature range of 90–100 °C.

The high content of amino acids of Chinese rice wine (CRW), especially essential amino acids makes it a food increasingly demanded by consumers. Rapid detection technique of amino acid content, which is an important quality and function index of CRW, is highly desirable for consumers, producers as well as administrative authorities. In this study, the potential of Fourier transform infrared spectroscopy (FT-IR) as a novel and rapid analytical technique to determine 17 free amino acids in CRW were investigated. Genetic algorithms (GA) and synergy interval partial least squares (SiPLS) were used to select the most efficient spectral variables to improve the prediction precision of the classic partial least squares (PLS) model constructed on the full-spectrum. The results demonstrated that compared with the PLS model using all wavelengths of FT-IR spectra, the prediction precision of model based on the spectral variables selected by GA and SiPLS was significantly improved, especially for arginine and proline. After systemic comparison and discussion, it was found that GA-SiPLS model achieved the best performance, with the correlation coefficient in calibration (R2 (cal)) higher than 0.80 and the residual predictive deviation higher than 2.00 for all of the free amino acids analyzed in this study. The overall results confirmed that FT-IR combined with efficient variable selection algorithms is a method that may be useful to replace the traditional methods for routine analysis of free amino acids in CRW. Practical Application This research presented a rapid and accurate method to determine the free amino acid contents in Chinese rice wine without sophisticated pretreatment of the samples. The approach reported in this study could be applied to quality control in wineries. It would also be useful to authenticity assurance to prevent illegal adulteration and to guarantee the correct value estimation.

In this paper, we compared two different methods, one numerical technique, viz Legendre multiwavelet method, and the other analytical technique, viz optimal homotopy asymptotic method (OHAM), for solving fractional-order Kaup–Kupershmidt (KK) equation. Two-dimensional Legendre multiwavelet expansion together with operational matrices of fractional integration and derivative of wavelet functions is used to compute the numerical solution of nonlinear time-fractional KK equation. The approximate solutions of time fractional Kaup–Kupershmidt equation thus obtained by Legendre multiwavelet method are compared with the exact solutions as well as with OHAM. The present numerical scheme is quite simple, effective, and expedient for obtaining numerical solution of fractional KK equation in comparison to analytical approach of OHAM. Copyright © 2016 John Wiley & Sons, Ltd.

Phenolic compounds are used extensively in industrialproducts, which can accumulate in the environment andthe ecological food chain via the consumption of thesecompounds by wildlife or uptake by plants [1]. Due totheir presence in water, air and food matrices, they repre-sent significant toxic risks to the environment and humanhealth [2,3]. Phenolic compounds exhibit variable toxici-ties and their detection and quantification are very impor-tant for evaluating the overall toxicity of environmentalsamples [2,4]. In particular, catechol, p-cresol and p-ni-trophenol compounds are included as priority pollutantsthat are monitored by international bodies, such as theUS Environmental Protection Agency and the EuropeanUnion [5,6]. These phenolic compounds are also of greatimportance in the food and medical industries and areclosely associated with the aesthetic and nutritional quali-ty of fresh and processed plant foods [7]. The inhibitoryeffect of phenolic compounds on mutagenesis and carci-nogenesis likely constitutes their most critical biologicalactivity [8,9]. Therefore, the development of a simple, re-liable and sensitive analytical technique is required forthe simultaneous detection and quantification of catechol,p-cresol and p-nitrophenol for both biological detectionand environmental protection.Several methods, such as high performance liquid chro-matography [10], flow-injection analysis [11], synchro-nous fluorescence [12], chemiluminescence [13], gas chro-matography-mass spectrometry [14], have been reportedfor the detection and quantification of isolated phenoliccompounds such as catechol, p-cresol and p-nitrophenol.In particular, chromatographic separation is generally re-quired prior for the detection of phenolic compounds[15]. Even though these methods are sensitive and selec-tive, they are time consuming, and often require expen-sive equipment that is generally not portable [16]. Re-cently, Yuan et al. [13] demonstrated that the electrogen-erated chemiluminescence (ECL) based detection of phe-nolic compounds such as hydroquinone, resorcinol, p-cresol, p-chlorophenol and o-bromophenol using a gra-phene/multiwall carbon nanotube/gold nanoclusterhybrid. It was reported that the fabricated sensor was uti-lized for various phenolic compounds; however, the pres-ent method cannot be applied to their simultaneous de-termination and discrimination. In contrast to these meth-ods, electrochemical techniques have a number of advan-tages in the detection and determination of chemical andbiological compounds, due to their rapid response,straightforward operation, time savings, and cost effec-tiveness [17–19]. In addition, when considering their criti-cal importance for practical use, electrochemical sensingdevices have the ability to perform real-time analysis forthe simultaneous sensing of phenolic compounds withinmixtures because of their inherent sensitivity and minia-turization, stability of performance and high compatibilitywith micro- and nanotechnologies [20,21].Owing to miniaturization, inexpensive instrumentation,excellent detection limits, high sensitivity and selectivity,carbon nanotube-based electrochemical sensors representa potentially powerful sensing approach, with applicationsin chemical and biochemical sensors, which have beenwidely reported [17,21,22]. Carbon nanotubes are a classof nanomaterials with unique geometrical, mechanical,Abstract: A mediator-free electrochemical sensing plat-form was designed by utilizing single-walled carbon nano-tube (SWCNT) modified glassy carbon (GC) electrodesfor the electrocatalytic oxidation of phenolic compounds.The proposed sensing platform permits the sensitive si-multaneous detection of catechol, p-cresol and p-nitro-phenol with the lowest detection limits of 2.3, 3.7 and7.7 nM, and high sensitivities of 135.08, 94.90 and110.38 mA/mM, respectively. The non-enzymatic electro-chemical sensor designed in this study also exhibited highstablility and reproducible as well as rapid response, pro-viding new opportunities for the development of sensingdevices in the detection of multiple phenolic compoundssimultaneously for practical environmental applications.

Speed, manageability and above all non-destructivity are the main features that make portable X-ray fluorescence (PXRF) a versatile analytical technique widely used in archaeometry. The extensively use of PXRF instruments in recent years during in situ investigations[1-3] makes the scientific community wonder how to use in the best way the data collected, as close attention must be paid when analysing non-standard materials such as ancient handcrafted works. Copyright © 2015 John Wiley & Sons, Ltd.

Summary This paper describes in detail a novel, fully analytical technique for the determination of high frequency noise parameters. The technique can be applied at any frequency of interest because the requirement of an external tuner is dropped. The absence of an input tuner removes the practical constraint of operational bandwidth of the system and opens the door to the direct evaluation of noise parameters of active devices in frequency ranges currently inaccessible. The mathematical formulation at the basis of the present technique is applied to the Pospieszalski noise model and is described in detail. The new technique provides an analytical tool to determine the equivalent noise temperatures Tgs and Tds against measured data over a broad frequency range. Limitations and opportunities of the new technique are discussed including new insights into the Pospieszalski noise model. Copyright © 2015 John Wiley & Sons, Ltd.

As a typical miniaturized analytical technique, CEC has attracted much attention because of its low sample and solvent consumption, high efficiency, high selectivity, high resolution, and fast speed. In this review, we mainly cover the development of capillary columns and detection techniques in the CEC since 2009. Herein, three types of capillary columns, namely, open-tubular capillary columns, monolithic columns and packed columns, and several types of detectors are reviewed in detail. Moreover, a 2D separation system based on CEC is also reported.

Biologically active compounds are found in biological samples at relatively low concentration levels. The sample preparation of target compounds from biological, pharmaceutical, environmental, and food matrices is one of the most time-consuming steps in the analytical procedure. The microextraction techniques are dominant. Metabolomic studies also require application of proper analytical technique for the determination of endogenic metabolites present in biological matrix on trace concentration levels. Due to the reproducibility of data, precision, relatively low cost of the appropriate analysis, simplicity of the determination, and the possibility of direct combination of those techniques with other methods (combination types on-line and off-line), they have become the most widespread in routine determinations. Additionally, sample pretreatment procedures have to be more selective, cheap, quick, and environmentally friendly. This review summarizes the current achievements and applications of microextraction techniques. The main aim is to deal with the utilization of different types of sorbents for microextraction and emphasize the use of new synthesized sorbents as well as to bring together studies concerning the systematic approach to method development. This review is dedicated to the description of microextraction techniques and their application in biomedical analysis.

Mycotoxins are highly toxic compounds often found in the food. It is of paramount importance to have analytical technique for point-of-care on-spot detection for authorised personnel to immediately take the action required. Electrochemistry offers the portability for miniaturized sensor of mycotoxins. Here we show that edge-plane pyrolytic electrode offers excellent selectivity and sensitivity towards simultaneous detection of zearalenone and citrinin. This will have a great impact for point-of-care mycotoxin detection.

RATIONALE In recent years, research and applications of the N2O site-specific nitrogen isotope composition have advanced, reflecting awareness of the contribution of N2O to the anthropogenic greenhouse effect, and leading to significant progress in instrument development. Further dissemination of N2O isotopomer analysis, however, is hampered by a lack of internationally agreed gaseous N2O reference materials and an uncertain compatibility of different laboratories and analytical techniques. METHODS In a first comparison approach, eleven laboratories were each provided with N2O at tropospheric mole fractions (target gas T) and two reference gases (REF1 and REF2). The laboratories analysed all gases, applying their specific analytical routines. Compatibility of laboratories was assessed based on N2O isotopocule data for T, REF1 and REF2. Results for T were then standardised using REF1 and REF2 to evaluate the potential of N2O reference materials for improving compatibility between laboratories. RESULTS Compatibility between laboratories depended on the analytical technique: isotope ratio mass spectrometry (IRMS) results showed better compatibility for δ(15)N values, while the performance of laser spectroscopy was superior with respect to N2O site preference. This comparison, however, is restricted by the small number of participating laboratories applying laser spectroscopy. Offset and two-point calibration correction of the N2O isotopomer data significantly improved the consistency of position-dependent nitrogen isotope data while the effect on δ(15)N values was only minor. CONCLUSIONS The study reveals that for future research on N2O isotopocules, standardisation against N2O reference material is essential to improve interlaboratory compatibility. For atmospheric monitoring activities, we suggest N2O in whole air as a unifying scale anchor.

SUMMARY Nonlinear viscous dampers are supplemental devices widely used for enhancing the performance of structural systems exposed to seismic hazard. A rigorous evaluation of the effect of these damping devices on the seismic performance of a structural system should be based on a probabilistic approach and take into account the evolutionary characteristics of the earthquake input and of the corresponding system response. In this paper, an approximate analytical technique is proposed for studying the nonstationary stochastic response characteristics of hysteretic single degree of freedom systems equipped with viscous dampers subjected to a fully nonstationary random process representing the seismic input. In this regard, a stochastic averaging/linearization technique is utilized to cast the original nonlinear stochastic differential equation of motion into a simple first-order nonlinear ordinary differential equation for the nonstationary system response variance. In comparison with standard linearization schemes, the herein proposed technique has the significant advantage that it allows to handle realistic seismic excitations with time-varying frequency content. Further, it allows deriving a formula for determining the nonlinear system response evolutionary power spectrum. By this way, ‘moving resonance’ effects, related to both the evolutionary seismic excitation and the nonlinear system behavior, can be observed and quantified. Several applications involving various system and input properties are included. Furthermore, various response parameters of interest for the seismic performance assessment are considered as well. Comparisons with pertinent Monte Carlo simulations demonstrate the reliability of the proposed technique. Copyright © 2014 John Wiley & Sons, Ltd.

RATIONALE: Imaging mass spectrometry is a powerful analytical technique capable of accessing a large volume of spatially resolved, chemical data from two-dimensional samples. Probing the entire surface of a sample simultaneously requires a detector with high spatial and temporal resolutions, and the ability to observe events relating to different mass-to-charge ratios. METHODS: A commercially available time-of-flight mass spectrometer, designed for matrix-assisted laser desorption/ionization (MALDI) analysis, was combined with the novel pixel imaging mass spectrometry (PImMS) camera in order to perform multi-mass, microscope-mode imaging experiments. A number of minor modifications were made to the spectrometer hardware and ion optics so that spatial imaging was achieved for a number of small molecules. RESULTS: It was shown that a peak width of Δm50 %