Showing papers in "Applied Spectroscopy in 2015"
TL;DR: The underlying technology, the physical phenomena governing the light–matter interaction at terahertz frequencies, recent examples of spectroscopic studies, and the current state of the art in assigning spectral features to vibrational modes based on computational techniques are outlined.
Abstract: With the ongoing proliferation of terahertz time-domain instrumentation from semiconductor physics into applied spectroscopy over the past decade, measurements at terahertz frequencies (1 THz ≡ 10(12) Hz ≡ 33 cm(-1)) have attracted a sustained growing interest, in particular the investigation of hydrogen-bonding interactions in organic materials. More recently, the availability of Raman spectrometers that are readily able to measure in the equivalent spectral region very close to the elastic scattering background has also grown significantly. This development has led to renewed efforts in performing spectroscopy at the interface between dielectric relaxation phenomena and vibrational spectroscopy. In this review, we briefly outline the underlying technology, the physical phenomena governing the light-matter interaction at terahertz frequencies, recent examples of spectroscopic studies, and the current state of the art in assigning spectral features to vibrational modes based on computational techniques.
147 citations
TL;DR: The results show that the refractive index of NaCI solution increases with NaCl concentrations and correlates nonlinearly with the concentration of NaCl solution, and the absorption index ofNaCl solution increases in the visible spectral range of 300-700 nm, but varies little in the near-infrared spectral range at room temperature.
Abstract: The optical properties of sodium chloride (NaCl) solution were experimentally determined by double optical pathlength transmission method in the spectral range from 300 to 2500 nm at the NaCl concentration range from 0 to 360 g/L. The results show that the refractive index of NaCl solution increases with NaCl concentrations and correlates nonlinearly with the concentration of NaCl solution. The absorption index of NaCl solution increases with NaCl concentrations in the visible spectral range of 300-700 nm, but varies little in the near-infrared spectral range of 700-2500 nm at room temperature. For the sake of applications, the fitted formulae of the refractive index and absorption index of NaCl solution as a function of wavelength and NaCl concentration are presented.
72 citations
TL;DR: This review intends to give an introduction to TERS, focusing on its basic principle and the experimental setup, the strengths followed by recent applications, developments, and perspectives in this field.
Abstract: Spectroscopic methods with high spatial resolution are essential to understand the physical and chemical properties of nanoscale materials including biological and chemical materials. Tip-enhanced Raman spectroscopy (TERS) is a combination of surface-enhanced Raman spectroscopy (SERS) and scanning probe microscopy (SPM), which can provide high-resolution topographic and spectral information simultaneously below the diffraction limit of light. Even examples of sub-nanometer resolution have been demonstrated. This review intends to give an introduction to TERS, focusing on its basic principle and the experimental setup, the strengths followed by recent applications, developments, and perspectives in this field.
65 citations
TL;DR: The absolute TDLAS spectrometer has been validated using reference gas mixtures with known CO2 and H2O amount fractions and traceability of all parameters used for amount fraction determination is discussed and a comprehensive uncertainty assessment is presented.
Abstract: Simultaneous detection of two analytes, carbon dioxide (CO2) and water vapor (H2O), has been realized using tunable diode laser absorption spectroscopy (TDLAS) with a single distributed feedback diode laser at 2.7 μm. The dynamic range of the spectrometer is extended from the low parts per million to the percentage range using two gas cells, a single-pass cell with 0.77 m, and a Herriott-type multipass cell with 76 m path length. Absolute measurements were carried out, i.e., amount fractions of the analytes were calculated based on previously determined spectral line parameters, without the need for an instrument calibration using gas standards. A thorough metrological characterization of the spectrometer is presented. We discuss traceability of all parameters used for amount fraction determination and provide a comprehensive uncertainty assessment. Relative expanded uncertainties (k = 2, 95% confidence level) of the measured amount fractions are shown to be in the 2-3% range for both analytes. Minimum detectable amount fractions are 0.16 μmol/mol for CO2 and 1.1 μmol/mol for H2O for 76 m path length and 5 s averaging time. This corresponds to normalized detection limits of 27 μmol/mol m Hz(-1/2) for CO2 and 221 μmol/mol m Hz(-1/2) for H2O. Precision of the spectrometer, determined using Allan variance analysis, is 3.3 nmol/mol for CO2 and 21 nmol/mol for H2O. The spectrometer has been validated using reference gas mixtures with known CO2 and H2O amount fractions. An application example of the absolute TDLAS spectrometer as a reference instrument to validate other sensors is also presented.
58 citations
TL;DR: A novel iterative algorithm named Goldindec is proposed, freely available for noncommercial use as noted in text, with a new cost function that not only conquers the influence of great peaks but also solves the problem of low correction accuracy when there is a high peak number.
Abstract: Raman spectra have been widely used in biology, physics, and chemistry and have become an essential tool for the studies of macromolecules. Nevertheless, the raw Raman signal is often obscured by a broad background curve (or baseline) due to the intrinsic fluorescence of the organic molecules, which leads to unpredictable negative effects in quantitative analysis of Raman spectra. Therefore, it is essential to correct this baseline before analyzing raw Raman spectra. Polynomial fitting has proven to be the most convenient and simplest method and has high accuracy. In polynomial fitting, the cost function used and its parameters are crucial. This article proposes a novel iterative algorithm named Goldindec, freely available for noncommercial use as noted in text, with a new cost function that not only conquers the influence of great peaks but also solves the problem of low correction accuracy when there is a high peak number. Goldindec automatically generates parameters from the raw data rather than by empirical choice, as in previous methods. Comparisons with other algorithms on the benchmark data show that Goldindec has a higher accuracy and computational efficiency, and is hardly affected by great peaks, peak number, and wavenumber.
55 citations
TL;DR: A prototype remote LIBS-Raman-fluorescence instrument, Q-switched laser-induced time-resolved spectroscopy (QuaLITy), which is approximately 70 000 times more efficient at recording signals than a commercially available LIBS instrument and fulfills all of the NASA expectations for proposed instruments.
Abstract: In the recent Mars 2020 Rover Science Definition Team Report, the National Aeronautics and Space Administration (NASA) has sought the capability to detect and identify elements, minerals, and most importantly, biosignatures, at fine scales for the preparation of a retrievable cache of samples. The current Mars rover, the Mars Science Laboratory Curiosity, has a remote laser-induced breakdown spectroscopy (LIBS) instrument, a type of quantitative elemental analysis, called the Chemistry Camera (ChemCam) that has shown that laser-induced spectroscopy instruments are not only feasible for space exploration, but are reliable and complementary to traditional elemental analysis instruments such as the Alpha Particle X-Ray Spectrometer. The superb track record of ChemCam has paved the way for other laser-induced spectroscopy instruments, such as Raman and fluorescence spectroscopy. We have developed a prototype remote LIBS-Raman-fluorescence instrument, Q-switched laser-induced time-resolved spectroscopy (QuaLITy), which is approximately 70 000 times more efficient at recording signals than a commercially available LIBS instrument. The increase in detection limits and sensitivity is due to our development of a directly coupled system, the use of an intensified charge-coupled device image detector, and a pulsed laser that allows for time-resolved measurements. We compare the LIBS capabilities of our system with an Ocean Optics spectrometer instrument at 7 m and 5 m distance. An increase in signal-to-noise ratio of at least an order of magnitude allows for greater quantitative analysis of the elements in a LIBS spectrum with 200-300 μm spatial resolution at 7 m, a Raman instrument capable of 1 mm spatial resolution at 3 m, and bioorganic fluorescence detection at longer distances. Thus, the new QuaLITy instrument fulfills all of the NASA expectations for proposed instruments.
53 citations
TL;DR: This article proposes a variation model that combines baseline correction and denoising, and describes an efficient optimization scheme that alternates between the latent spectrum estimation and the baseline correction until convergence.
Abstract: Laser instruments often suffer from the problem of baseline drift and random noise, which greatly degrade spectral quality In this article, we propose a variation model that combines baseline correction and denoising First, to guide the baseline estimation, morphological operations are adopted to extract the characteristics of the degraded spectrum Second, to suppress noise in both the spectrum and baseline, Tikhonov regularization is introduced Moreover, we describe an efficient optimization scheme that alternates between the latent spectrum estimation and the baseline correction until convergence The major novel aspect of the proposed algorithms is the estimation of a smooth spectrum and removal of the baseline simultaneously Results of a comparison with state-of-the-art methods demonstrate that the proposed method outperforms them in both qualitative and quantitative assessments
52 citations
TL;DR: Findings illustrated that nCeO2 induced compositional modifications in the root xylem of cereals with major peaks at 1744 or 1760cm−1 appeared in primary PC and 1728 cm−1 in secondary PC score loadings.
Abstract: Cerium oxide nanoparticles (nCeO2) have extensive industrial applications, and concerns regarding their threat to the environment have been raised. This study includes structural analysis of intact root xylem of rice (Oryza sativaL.), wheat (Triticum aestivumL.), and barley (Hordeum vulgareL.) seedlings exposed to nCeO2 suspensions (0, 62.5, 125, 250, and 500 mg L−1). Fourier transform infrared microspectroscopy was applied to determine compositional alterations in the root xylem, and principal component analysis (PCA) was carried out to examine spectral differences between nCeO2 treatments. Results demonstrated that nCeO2 at ≥ 125 mg L−1 changed the region of spectra around 1696-1760 cm−1 in rice root, 125 and 250 mg L−1 modified 1744-1792 cm−1 in wheat, and 62.5 and 125 mg L−1 altered 1727-1760 cm−1 in barley. PCA afforded the clustering of nCeO2 treatments at 0 and 62.5 mg L−1 in rice and wheat and 0 and 500 mg L−1 in barley. Furthermore, major peaks at 1744 or 1760 cm−1 appeared in primary PC and 1728 cm−1 in secondary PC score loadings. These findings illustrated that nCeO2 induced compositional modifications in the root xylem of cereals.
47 citations
TL;DR: The SERS substrate prepared from macro-mesoporous silicon template showed significantly broader size distribution of irregular silver nanoparticles as well as localized surface plasmon resonance closer to excitation laser wavelength, which might indicate possible single molecule detection.
Abstract: Microporous and macro-mesoporous silicon templates for surface-enhanced Raman scattering (SERS) substrates were produced by anodization of low doped p-type silicon wafers. By immersion plating in AgNO3, the templates were covered with silver metallic film consisting of different silver nanostructures. Scanning electron microscopy (SEM) micrographs of these SERS substrates showed diverse morphology with significant difference in an average size and size distribution of silver nanoparticles. Ultraviolet-visible-near-infrared (UV-Vis-NIR) reflection spectroscopy showed plasmonic absorption at 398 and 469 nm, which is in accordance with the SEM findings. The activity of the SERS substrates was tested using rhodamine 6G (R6G) dye molecules and 514.5 nm laser excitation. Contrary to the microporous silicon template, the SERS substrate prepared from macro-mesoporous silicon template showed significantly broader size distribution of irregular silver nanoparticles as well as localized surface plasmon resonance closer to excitation laser wavelength. Such silver morphology has high SERS sensitivity that enables ultralow concentration detection of R6G dye molecules up to 10(-15) M. To our knowledge, this is the lowest concentration detected of R6G dye molecules on porous silicon-based SERS substrates, which might even indicate possible single molecule detection.
46 citations
TL;DR: The utility of RS to identify a biological response in human tumor cells exposed to therapeutic doses of radiation was found to be governed by the extent of the biochemical changes induced by a radiation response and is therefore cell line specific.
Abstract: The drive toward personalized radiation therapy (RT) has created significant interest in determining patient-specific tumor and normal tissue responses to radiation. Raman spectroscopy (RS) is a non-invasive and label-free technique that can detect radiation response through assessment of radiation-induced biochemical changes in tumor cells. In the current study, single-cell RS identified specific radiation-induced responses in four human epithelial tumor cell lines: lung (H460), breast (MCF-7, MDA-MB-231), and prostate (LNCaP), following exposure to clinical doses of radiation (2-10 Gy). At low radiation doses (2 Gy), H460 and MCF-7 cell lines showed an increase in glycogen-related spectral features, and the LNCaP cell line showed a membrane phospholipid-related radiation response. In these cell lines, only spectral information from populations receiving 10 Gy or less was required to identify radiation-related features using principal component analysis (PCA). In contrast, the MDA-MB-231 cell line showed a significant increase in protein relative to nucleic acid and lipid spectral features at doses of 6 Gy or higher, and high-dose information (30, 50 Gy) was required for PCA to identify this biological response. The biochemical nature of the radiation-related changes occurring in cells exposed to clinical doses was found to segregate by status of p53 and radiation sensitivity. Furthermore, the utility of RS to identify a biological response in human tumor cells exposed to therapeutic doses of radiation was found to be governed by the extent of the biochemical changes induced by a radiation response and is therefore cell line specific. The results of this study demonstrate the utility and effectiveness of single-cell RS to identify and measure biological responses in tumor cells exposed to standard radiotherapy doses.
45 citations
TL;DR: This study quantitatively evaluates the precision of the main differential NIR spectroscopy measurements considering similar conditions and minimized random disturbances and proposes noninvasive glucose-sensing methods that hold promise for future clinical application.
Abstract: The noninvasive sensing of the blood glucose concentration is usually based on optical, electrical, or acoustical signals induced by blood glucose; these signals are extremely weak and subject to fluctuations caused by the variation in the body or surroundings. Therefore, it is challenging to detect blood glucose noninvasively with high accuracy, and no successful accurate and noninvasive clinical application has been reported. We found that there are two key measurement issues to be addressed: systematic errors, such as the errors induced by the drifts of devices or by variations in body temperature, among others, are too large to guarantee the trueness of measurement at present; and random disturbances in repeated tests, such as disturbances associated with variations in the human-machine interface, pulses, and the thermal noise of the devices, cause larger repeated measurement errors and compromise precision. Recent novel reference measurements based on differential near-infrared (NIR) spectroscopy are considered promising for solving the systematic error issue by establishing matched references, collected at another detection site or at another time, and subsequently differencing to remove the common systematic errors. However, differencing weakens the signal of interest itself and enlarges the effects of the second issue, random disturbances affecting the precision. It is understood that only reference measurements that can meet the precision requirement will be promising for future applications. Therefore, this study quantitatively evaluates the precision of the main differential NIR spectroscopy measurements considering similar conditions and minimized random disturbances. The precision of the measurements under these conditions should represent their optimal precision levels. After the evaluation, noninvasive glucose-sensing methods that hold promise for future clinical application are proposed. Finally, the evaluation criteria could be a reference for the noninvasive detection of other physiological components.
TL;DR: The specificity of the coordination chemistry provided both di-DMT and TMT with excellent selectivity for the detection of Hg2+ and Cu2+ in the presence of other interfering metal ion species.
Abstract: We report the development of a surface-enhanced Raman scattering (SERS)-based heavy metal ion sensor targeting the detection of mercury(II) ion (Hg(2+)) and copper(II) ion (Cu(2+)) with high sensitivity and selectivity. To achieve the detection of vibrational-spectroscopically silent heavy metal ions, the SERS substrate composed of gold nanorod (AuNR)-polycaprolactone (PCL) nanocomposite fibers was first functionalized using metal ion-binding ligands. Specifically, 2,5-dimercapto-1,3,4-thiadiazole dimer (di-DMT) and trimercaptotriazine (TMT) were attached to the SERS substrates serving as bridging molecules to capture Hg(2+) and Cu(2+), respectively, from solution. Upon heavy metal ion coordination, changes in the vibrational spectra of the bridging molecules, including variations in the peak-intensity ratios and peak shifts were observed and taken as indicators of the capture of the target ions. With rigorous spectral analysis, the coordination mechanism between the heavy metal ion and the corresponding bridging molecule was investigated. Mercury(II) ion primarily interacts with di-DMT through the cleavage of the disulfide bond, whereas Cu(2+) preferentially interacts with the heterocyclic N atoms in TMT. The specificity of the coordination chemistry provided both di-DMT and TMT with excellent selectivity for the detection of Hg(2+) and Cu(2+) in the presence of other interfering metal ion species. In addition, quantitative analysis of the concentration of the heavy metal ions was achieved through the construction of internal calibration curves using the peak-intensity ratios of 287/387 cm(-1) for Hg(2+) and 1234/973 cm(-1) for Cu(2+).
TL;DR: In this paper, the matrix effects in transmission NIR and Raman spectroscopy were systematically investigated for a solid pharmaceutical formulation for quantitative assessment, using orthogonal partial least squares regression.
Abstract: Raman spectroscopy can be an alternative to near-infrared spectroscopy (NIR) for nondestructive quantitative analysis of solid pharmaceutical formulations. Compared with NIR spectra, Raman spectra have much better selectivity, but subsampling was always an issue for quantitative assessment. Raman spectroscopy in transmission mode has reduced this issue, since a large volume of the sample is measured in transmission mode. The sample matrix, such as particle size of the drug substance in a tablet, may affect the Raman signal. In this work, matrix effects in transmission NIR and Raman spectroscopy were systematically investigated for a solid pharmaceutical formulation. Tablets were manufactured according to an experimental design, varying the factors particle size of the drug substance (DS), particle size of the filler, compression force, and content of drug substance. All factors were varied at two levels plus a center point, except the drug substance content, which was varied at five levels. Six tablets from each experimental point were measured with transmission NIR and Raman spectroscopy, and their concentration of DS was determined for a third of those tablets. Principal component analysis of NIR and Raman spectra showed that the drug substance content and particle size, the particle size of the filler, and the compression force affected both NIR and Raman spectra. For quantitative assessment, orthogonal partial least squares regression was applied. All factors varied in the experimental design influenced the prediction of the DS content to some extent, both for NIR and Raman spectroscopy, the particle size of the filler having the largest effect. When all matrix variations were included in the multivariate calibrations, however, good predictions of all types of tablets were obtained, both for NIR and Raman spectroscopy. The prediction error using transmission Raman spectroscopy was about 30% lower than that obtained with transmission NIR spectroscopy.
TL;DR: Future studies using controlled experiments with variable nutrient applications are required for quantification of foliar nutrients by using LIBS-based sensing.
Abstract: Nutrient assessment and management are important to maintain productivity in citrus orchards. In this study, laser-induced breakdown spectroscopy (LIBS) was applied for rapid and real-time detection of citrus anomalies. Laser-induced breakdown spectroscopy spectra were collected from citrus leaves with anomalies such as diseases (Huanglongbing, citrus canker) and nutrient deficiencies (iron, manganese, magnesium, zinc), and compared with those of healthy leaves. Baseline correction, wavelet multivariate denoising, and normalization techniques were applied to the LIBS spectra before analysis. After spectral pre-processing, features were extracted using principal component analysis and classified using two models, quadratic discriminant analysis and support vector machine (SVM). The SVM resulted in a high average classification accuracy of 97.5%, with high average canker classification accuracy (96.5%). LIBS peak analysis indicated that high intensities at 229.7, 247.9, 280.3, 393.5, 397.0, and 769.8 nm were observed of 11 peaks found in all the samples. Future studies using controlled experiments with variable nutrient applications are required for quantification of foliar nutrients by using LIBS-based sensing.
TL;DR: The suitability of low-frequency Raman spectroscopy to monitor IND in a suspension was demonstrated, suggesting that the technique will be a valuable tool for at-line and on-line monitoring of active pharmaceutical ingredient crystallization.
Abstract: Raman spectroscopy using the mid-frequency (1800-1500 cm(-1)) and low-frequency (200-8 cm(-1)) spectral regions is used to study the transformation of amorphous indomethacin (IND) to the γ-crystalline form. The low-frequency spectral region provides access to collective vibrations of molecules in the crystalline and amorphous state, while the mid-frequency spectral region provides access to the molecular vibrations that are sensitive to the local functional group environment. Both spectral regions provide distinct Raman bands for the amorphous and crystalline forms of IND. The more intense low-frequency Raman bands provide greater sensitivity for detecting the onset of crystallization in an amorphous matrix. Subtle differences in the behavior of the initial crystalline process of IND are observed between the low-frequency and mid-frequency Raman bands. These observations suggest that different responses for mid- and low-frequency Raman bands occur for the microcrystalline domains present during the initial crystallization process. The suitability of low-frequency Raman spectroscopy to monitor IND in a suspension was demonstrated. This suggests that the technique will be a valuable tool for at-line and on-line monitoring of active pharmaceutical ingredient crystallization.
TL;DR: It was found that Raman spectroscopy enables identification of primarily the major components in dye mixtures, and MSP UV–Vis showed limited possibilities for discriminatory analysis of cotton fibers dyed with a mixture of reactive dyes.
Abstract: Presented in this paper is an assessment of the applicability of Raman spectroscopy and microspectrophotometry (MSP) in visible and ultraviolet light (UV-Vis) in the examination of textile fibers dyed with mixtures of synthetic dyes. Fragments of single polyester fibers, stained with ternary mixtures of disperse dyes in small mass concentrations, and fragments of single cotton fibers, dyed with binary or ternary mixtures of reactive dyes, were subjected to the study. Three types of excitation sources, 514, 633, and 785 nm, were used during Raman examinations, while the MSP study was conducted in the 200 to 800 nm range. The results indicate that the capabilities for discernment of dye mixtures are similar in the spectroscopic methods that were employed. Both methods have a limited capacity to distinguish slightly dyed polyester fiber; additionally, it was found that Raman spectroscopy enables identification of primarily the major components in dye mixtures. The best results, in terms of the quality of Raman spectra, were obtained using an excitation source from the near infrared. MSP studies led to the conclusion that polyester testing should be carried out in the range above 310 nm, while for cotton fibers there is no limitation or restriction of the applied range. Also, MSP UV-Vis showed limited possibilities for discriminatory analysis of cotton fibers dyed with a mixture of reactive dyes, where the ratio of the concentration of the main dye used in the dyeing process to minor dye was higher than four. The results presented have practical applications in forensic studies, inter alia.
TL;DR: In this feasibility study, Raman spectra of several compounds are measured to demonstrate the spectral resolution and range of the system and the use of a large laser spot to minimize UV-laser-induced sample degradation.
Abstract: A deep-ultraviolet (UV) 244 nm excitation spatial heterodyne Raman spectrometer (SHRS) is demonstrated for the first time. The deep-UV SHRS has no moving parts, and even though it is small for a deep-UV Raman spectrometer, the spectral resolution is shown to be about 4 cm−1. The deep-UV SHRS also has a large input aperture and acceptance angle, and the resulting large field of view is shown to be useful to avoid laser-induced sample degradation. In this feasibility study, Raman spectra of several compounds are measured to demonstrate the spectral resolution and range of the system. A photosensitive compound is also measured to demonstrate the use of a large laser spot to minimize UV-laser-induced sample degradation.
TL;DR: A novel methodology-based discrete wavelet transform (DWT) and the choice of the optimal wavelet pairs to adaptively process tunable diode laser absorption spectroscopy (TDLAS) spectra for quantitative analysis, such as molecular Spectroscopy and trace gas detection are presented.
Abstract: This paper presents a novel methodology-based discrete wavelet transform (DWT) and the choice of the optimal wavelet pairs to adaptively process tunable diode laser absorption spectroscopy (TDLAS) spectra for quantitative analysis, such as molecular spectroscopy and trace gas detection. The proposed methodology aims to construct an optimal calibration model for a TDLAS spectrum, regardless of its background structural characteristics, thus facilitating the application of TDLAS as a powerful tool for analytical chemistry. The performance of the proposed method is verified using analysis of both synthetic and observed signals, characterized with different noise levels and baseline drift. In terms of fitting precision and signal-to-noise ratio, both have been improved significantly using the proposed method.
TL;DR: A protocol created for acephate detection on particulates and vapors surrounding farmworkers as well as in urine samples is reported and Optimal SERS sensor metal choice and post-production treatments to improve sensor stability in aqueous solutions containing Acephate are presented.
Abstract: A protocol created for acephate detection on particulates and vapors surrounding farmworkers as well as in urine samples is reported. Acephate is detected to the low parts-per-billion (ppb) range using surface-enhanced Raman spectroscopy (SERS). Optimal SERS sensor metal choice and post-production treatments to improve sensor stability in aqueous solutions containing acephate are presented. Acephate is detected in the vapor phase and can be differentiated from urine components and structurally similar pesticides, including the acephate metabolite-degradation product methamidophos. Protocol evaluation and preliminary field tests from North Carolina farms are discussed.
TL;DR: Good partial least squares (PLS) regression models were built, yielding high coefficients of determination and low predictive errors (root mean square error, or RMSE) to estimate host cell growth, plasmid production, carbon source consumption, and by-product acetate production and consumption in recombinant Escherichia coli cultures.
Abstract: The development of biopharmaceutical manufacturing processes presents critical constraints, with the major constraint being that living cells synthesize these molecules, presenting inherent behavior variability due to their high sensitivity to small fluctuations in the cultivation environment. To speed up the development process and to control this critical manufacturing step, it is relevant to develop high-throughput and in situ monitoring techniques, respectively. Here, high-throughput mid-infrared (MIR) spectral analysis of dehydrated cell pellets and in situ near-infrared (NIR) spectral analysis of the whole culture broth were compared to monitor plasmid production in recombinant Escherichia coli cultures. Good partial least squares (PLS) regression models were built, either based on MIR or NIR spectral data, yielding high coefficients of determination (R2) and low predictive errors (root mean square error, or RMSE) to estimate host cell growth, plasmid production, carbon source consumption (glucose a...
TL;DR: The present study reveals that in order to maximize the separation of the peaks in the second derivative spectra, the original spectra should be recorded at high resolution and differentiated using a small window size and high polynomial order.
Abstract: Derivative spectroscopy is a powerful tool for the resolution enhancement in infrared, near-infrared, Raman, ultraviolet-visible, nuclear magnetic resonance, electron paramagnetic resonance, and fluorescence spectroscopy. Despite its great significance in analytical chemistry, not all aspects of the applications of this method have been explored as yet. This is the first systematic study of the parameters that influence the resolution enhancement in the second derivative spectra. The derivative spectra were calculated with the Savitzky-Golay method with different window size (5, 15, 25) and polynomial order (2, 4). The results obtained in this work show that the resolution enhancement in the second derivative spectra strongly depends on the data spacing in the original spectra, window size, polynomial order, and peak profile. As shown, the resolution enhancement is related to variations in the width of the peaks upon the differentiation. The present study reveals that in order to maximize the separation of the peaks in the second derivative spectra, the original spectra should be recorded at high resolution and differentiated using a small window size and high polynomial order. However, working with the real spectra one has to compromise between the noise reduction and optimization of the resolution enhancement in the second derivative spectra.
TL;DR: Experimental results show that the proposed algorithm has better performance than spatial based algorithm because the new algorithm can jointly use the spatial and spectral information of blood cells.
Abstract: Red blood cell counts have been proven to be one of the most frequently performed blood tests and are valuable for early diagnosis of some diseases. This paper describes an automated red blood cell counting method based on microscopic hyperspectral imaging technology. Unlike the light microscopy-based red blood count methods, a combined spatial and spectral algorithm is proposed to identify red blood cells by integrating active contour models and automated two-dimensional k-means with spectral angle mapper algorithm. Experimental results show that the proposed algorithm has better performance than spatial based algorithm because the new algorithm can jointly use the spatial and spectral information of blood cells.
TL;DR: The present inexpensive analytical method, applied as a means of differentiating various types of writing, office, and photocopy papers on the basis of reflectance and absorbance spectra, provides nondestructive, quantitative, reliable, and repeatable results.
Abstract: Diffuse reflectance ultraviolet-visible-near-infrared (UV-Vis-NIR) spectroscopy is applied as a means of differentiating various types of writing, office, and photocopy papers (collected from stationery shops in India) on the basis of reflectance and absorbance spectra that otherwise seem to be almost alike in different illumination conditions. In order to minimize bias, spectra from both sides of paper were obtained. In addition, three spectra from three different locations (from one side) were recorded covering the upper, middle, and bottom portions of the paper sample, and the mean average reflectivity of both the sides was calculated. A significant difference was observed in mean average reflectivity of Side A and Side B of the paper using Student's pair >t-test. Three different approaches were used for discrimination: (1) qualitative features of the whole set of samples, (2) principal component analysis, and (3) a combination of both approaches. On the basis of the first approach, i.e., qualitative features, 96.49% discriminating power (DP) was observed, which shows highly significant results with the UV-Vis-NIR technique. In the second approach the discriminating power is further enhanced by incorporating the principal component analysis (PCA) statistical method, where this method describes each UV-Vis spectrum in a group through numerical loading values connected to the first few principal components. All components described 100% variance of the samples, but only the first three PCs are good enough to explain the variance (PC1 = 51.64%, PC2 = 47.52%, and PC3 = 0.54%) of the samples; i.e., the first three PCs described 99.70% of the data, whereas in the third approach, the four samples, C, G, K, and N, out of a total 19 samples, which were not differentiated using qualitative features (approach no. 1), were therefore subjected to PCA. The first two PCs described 99.37% of the spectral features. The discrimination was achieved by using a loading plot between PC1 and PC2. It is therefore concluded that maximum discrimination of writing, office, and photocopy paper could be achieved on the basis of the second approach. Hence, the present inexpensive analytical method can be appropriate for application to routine questioned document examination work in forensic laboratories because it provides nondestructive, quantitative, reliable, and repeatable results.
TL;DR: Results indicate that Raman spectroscopy in conjunction with a chemometrics method is reliable for the quantitative determination of the lipid composition accumulated in the cells of marine diatoms.
Abstract: An in vivo non-invasive quantitative analysis technique was introduced for evaluating the fat composition of living marine diatoms by using Raman spectroscopy in conjunction with a chemometric method. This technique enabled the observation of real-time variations in individual lipids in diatom cells without specific treatment or fat extraction. A confocal Raman spectroscope was used to measure the marine centric diatom Thalassiosira (T.) pseudonana that was cultured under six stress conditions, and the spectral data of accumulated fatty acids were obtained. A model-based chemometrics technique, ordinary least square was then used to extract specific signals from Raman spectra obtained for a mixture of fatty acids. The levels of four major lipid moieties from diatoms were extracted simultaneously, including myristic acid, palmitic acid, palmitoleic acid, and eicosapentaenoic acid from the Raman spectra. These results indicate that Raman spectroscopy in conjunction with a chemometrics method is reliable for the quantitative determination of the lipid composition accumulated in the cells of marine diatoms.
TL;DR: Micro-hyperspectral imaging coupled to the MCR method is confirmed to be an appropriate tool for the direct analysis of the constituents of chocolate samples, and by extension, it is proposed for the analysis of other mixture constituents in commercial food samples.
Abstract: This paper shows the application of Raman and infrared hyperspectral imaging combined with multivariate curve resolution (MCR) to the analysis of the constituents of commercial chocolate samples. The combination of different spectral data pretreatment methods allowed decreasing the high fluorescent Raman signal contribution of whey in the investigated chocolate samples. Using equality constraints during MCR analysis, estimations of the pure spectra of the chocolate sample constituents were improved, as well as their relative contributions and their spatial distribution on the analyzed samples. In addition, unknown constituents could be also resolved. White chocolate constituents resolved from Raman hyperspectral image indicate that, at macro scale, sucrose, lactose, fat, and whey constituents were intermixed in particles. Infrared hyperspectral imaging did not suffer from fluorescence and could be applied for white and milk chocolate. As a conclusion of this study, micro-hyperspectral imaging coupled to the MCR method is confirmed to be an appropriate tool for the direct analysis of the constituents of chocolate samples, and by extension, it is proposed for the analysis of other mixture constituents in commercial food samples.
TL;DR: Pattern recognition techniques have been developed to search the infrared (IR) spectral libraries of the PDQ database to differentiate between similar but nonidentical IR clear coat paint spectra, and the model of the automobile from which the unknown paint sample was obtained could be identified from its IR spectrum.
Abstract: Pattern recognition techniques have been developed to search the infrared (IR) spectral libraries of the paint data query (PDQ) database to differentiate between similar but nonidentical IR clear coat paint spectra. The library search system consists of two separate but interrelated components: search prefilters to reduce the size of the IR library to a specific assembly plant or plants corresponding to the unknown paint sample and a cross-correlation searching algorithm to identify IR spectra most similar to the unknown in the subset of spectra identified by the prefilters. To develop search prefilters with the necessary degree of accuracy, IR spectra from the PDQ database were preprocessed using wavelets to enhance subtle but significant features in the data. Wavelet coefficients characteristic of the assembly plant of the vehicle were identified using a genetic algorithm for pattern recognition and feature selection. A search algorithm was then used to cross-correlate the unknown with each IR spectrum in the subset of library spectra identified by the search prefilters. Each cross-correlated IR spectrum was simultaneously compared to an autocorrelated IR spectrum of the unknown using several spectral windows that span different regions of the cross-correlated and autocorrelated data from the midpoint. The top five hits identified in each search window are compiled, and a histogram is computed that summarizes the frequency of occurrence for each selected library sample. The five library samples with the highest frequency of occurrence are selected as potential hits. Even in challenging trials where the clear coat paint samples evaluated were all the same make (e.g., General Motors) within a limited production year range, the model of the automobile from which the unknown paint sample was obtained could be identified from its IR spectrum.
TL;DR: A novel camera-based measurement technique that enables robust quantification of a wide range of reduced scattering coefficients and absorption coefficients and is suitable for a rapid, non-contact, and non-invasive inspection that can deduce physically interpretable properties.
Abstract: The quality of a dairy product is largely determined by its microstructure which also affects its optical properties. Consequently, an assessment of the optical properties during production may be part of a feedback system for ensuring the quality of the production process. This paper presents a novel camera-based measurement technique that enables robust quantification of a wide range of reduced scattering coefficients and absorption coefficients. Measurements are based on hyperspectral images of diffuse reflectance in the wavelength range of 470 to 1020 nm. The optical properties of commercially available milk and yogurt products with three different levels of fat content are measured. These constitute a relevant range of products at a dairy plant. The measured reduced scattering properties of the samples are presented and show a clear discrimination between levels of fat contents as well as fermentation. The presented measurement technique and method of analysis is thus suitable for a rapid, non-contact, and non-invasive inspection that can deduce physically interpretable properties.
TL;DR: It is concluded that the NIR spectra of apatites are useful in the structural characterization of synthetic and biogenic apatite.
Abstract: Near-infrared spectroscopy (NIR) was used to analyze synthetic hydroxyapatite calcined at various temperatures, synthetic carbonated hydroxyapatite, and human hard dental tissues (enamel and dentin). The NIR bands of those materials in the combination, first-overtone, and second-overtone spectral regions were assigned and evaluated for structural characterization. They were attributed to adsorbed and structural water, structural hydroxyl (OH) groups and surface P-OH groups. The NIR spectral features were quantitatively discussed in view of proton solid-state magic-angle spinning nuclear magnetic resonance (1H MAS NMR) results. We conclude that the NIR spectra of apatites are useful in the structural characterization of synthetic and biogenic apatites.
TL;DR: The results of the multivariate analysis demonstrated the potential of chemometric approaches for characterizing and identifying drying oils, and also for gaining a deeper insight into the aging process.
Abstract: This work explores the application of chemometric techniques to the analysis of lipidic paint binders (i.e., drying oils) by means of Raman and near-infrared spectroscopy. These binders have been widely used by artists throughout history, both individually and in mixtures. We prepared various model samples of the pure binders (linseed, poppy seed, and walnut oils) obtained from different manufacturers. These model samples were left to dry and then characterized by Raman and reflectance near-infrared spectroscopy. Multivariate analysis was performed by applying principal component analysis (PCA) on the first derivative of the corresponding Raman spectra (1800-750 cm(-1)), near-infrared spectra (6000-3900 cm(-1)), and their combination to test whether spectral differences could enable samples to be distinguished on the basis of their composition. The vibrational bands we found most useful to discriminate between the different products we studied are the fundamental ν(C=C) stretching and methylenic stretching and bending combination bands. The results of the multivariate analysis demonstrated the potential of chemometric approaches for characterizing and identifying drying oils, and also for gaining a deeper insight into the aging process. Comparison with high-performance liquid chromatography data was conducted to check the PCA results.
TL;DR: Both infrared (IR) techniques performed well for the analysis of the three key analytes, and the samples were qualitatively discriminated according to their provinces of origin, although the NIR technique would be preferred.
Abstract: The Chinese yam (Dioscorea opposita) is a basic food in Asia and especially China. Consequently, an uncomplicated, reliable method should be available for the analysis of the quality and origin of the yams. Thus, near-infrared (NIR) and mid-infrared (mid-IR) spectroscopic methods were developed to discriminate among Chinese yam samples collected from four geographical regions. The yam samples were analyzed also for total sugar, polysaccharides, and flavonoids. These three analytes were used to compare the performance of the analytical methods. Overlapping spectra were resolved using chemometrics methods. Such spectra were compared qualitatively using principal component analysis (PCA) and quantitatively using partial least squares (PLS) and least squares-support vector machine (LS-SVM) models. We discriminated among the four sets of yam data using PCA, and the NIR data performed somewhat better than the mid-IR data. We constructed the PLS and LS-SVM calibration models for the prediction of the three key variables, and the LS-SVM model produced better results. Also, the NIR prediction model produced better outcomes than the mid-IR prediction model. Thus, both infrared (IR) techniques performed well for the analysis of the three key analytes, and the samples were qualitatively discriminated according to their provinces of origin. Both techniques may be recommended for the analysis of Chinese yams, although the NIR technique would be preferred.