Remote gas detection and quantitative analysis from infrared emission spectra obtained by Fourier transform infrared spectroscopy

Techniques for obtaining quantitative values of the temperatures and concentrations of remote hot gaseous effluents from their measured passive emission spectra have been examined in laboratory experiments. The high sensitivity of the spectrometer in the vicinity of the 2397 cm-1 band head region of CO2 has allowed the gas temperature to be calculated from the relative intensity of the observed rotational lines. The spatial distribution of the CO2 in a methane flame has been reconstructed tomographically using a matrix inversion technique. The spectrometer has been calibrated against a black body source at different temperatures and a self absorption correction has been applied to the data avoiding the need to measure the transmission directly. Reconstruction artifacts have been reduced by applying a smoothing routine to the inversion matrix.

Development and validation of the quantitative analysis of cefuroxime sodium in powder for injection by infrared spectroscopy

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Development and validation of the quantitative analysis of ceftazidime in powder for injection by infrared spectroscopy

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Development and validation of the quantitative analysis of ampicillin sodium in powder for injection by Fourier-transform infrared spectroscopy (FT-IR)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Universally Applicable Model for the Quantitative Determination of Lake Sediment Composition Using Fourier Transform Infrared Spectroscopy

ABSTRACT: Fourier transform infrared spectroscopy (FTIRS) can provide detailed information on organic and minerogenic constituents of sediment records. Based on a large number of sediment samples of varying age (0�340 000 yrs) and from very diverse lake settings in Antarctica, Argentina, Canada, Macedonia/Albania, Siberia, and Sweden, we have developed universally applicable calibration models for the quantitative determination of biogenic silica (BSi; n = 816), total inorganic carbon (TIC; n = 879), and total organic carbon (TOC; n = 3164) using FTIRS. These models are based on the differential absorbance of infrared radiation at specific wavelengths with varying concentrations of individual parameters, due to molecular vibrations associated with each parameter. The calibration models have low prediction errors and the predicted values are highly correlated with conventionally measured values (R = 0.94�0.99). Robustness tests indicate the accuracy of the newly developed FTIRS calibration models is similar to that of conventional geochemical analyses. Consequently FTIRS offers a useful and rapid alternative to conventional analyses for the quantitative determination of BSi, TIC, and TOC. The rapidity, cost-effectiveness, and small sample size required enables FTIRS determination of geochemical properties to be undertaken at higher resolutions than would otherwise be possible with the same resource allocation, thus providing crucial sedimentological information for climatic and environmental reconstructions.

Application of fourier transform infrared spectroscopy, chemical and chemometrics analyses to the characterization of agro-industrial waste

Agroindustrial waste in general presents significant levels of nutrients and organic matter and has therefore been frequently put to agricultural use. In this context, the objective of this study was to determine the chemical composition, nitrogen, phosphorus, potassium, calcium, magnesium and carbon content, as well as the qualitative characteristics through Fourier transform infrared spectroscopy of four samples of poultry litter and one sample of cattle manure, from the southwestern region of Paraná, Brazil. Results revealed that, in general, the poultry litter presented higher amount of nutrients and carbon than the cattle manure. The infrared spectra allowed identification of the functional groups present and the differences in degree of sample humification. The statistical treatment confirmed the quantitative and qualitative differences revealed.

Evaluating mid-infrared spectroscopy as a new technique for predicting sensory texture attributes of processed cheese

The objective of this study was to investigate the potential application of mid-infrared spectroscopy for determination of selected sensory attributes in a range of experimentally manufactured processed cheese samples. This study also evaluates mid-infrared spectroscopy against other recently proposed techniques for predicting sensory texture attributes. Processed cheeses (n = 32) of varying compositions were manufactured on a pilot scale. After 2 and 4 wk of storage at 4 degrees C, mid-infrared spectra ( 640 to 4,000 cm(-1)) were recorded and samples were scored on a scale of 0 to 100 for 9 attributes using descriptive sensory analysis. Models were developed by partial least squares regression using raw and pretreated spectra. The mouth-coating and mass-forming models were improved by using a reduced spectral range ( 930 to 1,767 cm(-1)). The remaining attributes were most successfully modeled using a combined range ( 930 to 1,767 cm(-1) and 2,839 to 4,000 cm(-1)). The root mean square errors of cross-validation for the models were 7.4(firmness; range 65.3), 4.6 ( rubbery; range 41.7), 7.1 ( creamy; range 60.9), 5.1(chewy; range 43.3), 5.2(mouth-coating; range 37.4), 5.3 (fragmentable; range 51.0), 7.4 ( melting; range 69.3), and 3.1 (mass-forming; range 23.6). These models had a good practical utility. Model accuracy ranged from approximate quantitative predictions to excellent predictions ( range error ratio = 9.6). In general, the models compared favorably with previously reported instrumental texture models and near-infrared models, although the creamy, chewy, and melting models were slightly weaker than the previously reported near-infrared models. We concluded that mid-infrared spectroscopy could be successfully used for the nondestructive and objective assessment of processed cheese sensory quality..

Prediction of processed cheese instrumental texture and meltability by mid-infrared spectroscopy coupled with chemometric tools

The objective of this study was to determine the potential of mid-infrared spectroscopy coupled with multidimensional statistical analysis for the prediction of processed cheese instrumental texture and meltability attributes. Processed cheeses (n = 32) of varying composition were manufactured in a pilot plant. Following two and four weeks storage at 4 degrees C samples were analysed using texture profile analysis, two meltability tests (computer vision, Olson and Price) and mid-infrared spectroscopy (4000-640 cm(-1)). Partial least squares regression was used to develop predictive models for all measured attributes. Five attributes were successfully modelled with varying degrees of accuracy. The computer vision meltability model allowed for discrimination between high and low melt values (R-2 = 0.64). The hardness and springiness models gave approximate quantitative results (R-2 = 0.77) and the cohesiveness (R-2 = 0.81) and Olson and Price meltability (R-2 = 0.88) models gave good prediction results. (c) 2006 Elsevier Ltd. All rights reserved..

Infrared spectroscopy: a tool for determination of the degree of conversion in dental composites

Infrared spectroscopy is one of the most widely used techniques for measurement of conversion degree in dental composites. However, to obtain good quality spectra and quantitative analysis from spectral data, appropriate expertise and knowledge of the technique are mandatory. This paper presents important details to use infrared spectroscopy for determination of the conversion degree.

A platform for designing quantitative infrared spectrophotometric method for drugs and pharmaceuticals analysis: a rediscover for an ecological and safer technique in the routine quality control laboratories

This paper describes the importance of an innovative analytical technique for drugs and pharmaceuticals quantification, using Fouriertransform infrared (FTIR) transmission spectroscopy. This method does not use organic solvents, which is one great advantage over the most common analytical methods. This fact contributes to minimize the generation of organic solvent waste by the industry and thereby reduces the impact of its activities on the environment. The method involved absorbance measurements of the band corresponding to one of the chosen group in the molecule. Obviously, the method should be validated according to ICH guidelines, showing linearity, precision, accuracy and robustness, over a concentration range, using small amounts to prepare the analyte. The validated method is able to quantify drugs and pharmaceuticals and can be used as an environmentally friendly alternative for the routine analysis in pharmaceutical industry quality control.

Fourier transform infrared spectroscopy, a new method for rapid determination of total organic and inorganic carbon and biogenic silica concentration in lake sediments

Abstract We demonstrate the use of Fourier transform infrared spectroscopy (FTIRS) to make quantitative measures of total organic carbon (TOC), total inorganic carbon (TIC) and biogenic silica (BSi) concentrations in sediment. FTIRS is a fast and costeffective technique and only small sediment samples are needed (0.01 g). Statistically significant models were developed using sediment samples from northern Sweden and were applied to sediment records from Sweden, northeast Siberia and Macedonia. The correlation between FTIRS-inferred values and amounts of biogeochemical constituents assessed conventionally varied between r = 0.84–0.99 for TOC, r = 0.85– 0.99 for TIC, and r = 0.68–0.94 for BSi. Because FTIR spectra contain information on a large number of both inorganic and organic components, there is great potential for FTIRS to become an important tool in paleolimnology.

NEAR INFRARED SPECTROSCOPY FOR ESTIMATING SUGARCANE BAGASSE CONTENT IN MEDIUM DENSITY FIBERBOARD

Medium density fiberboard (MDF) is an engineered wood product formed by breaking down selected lignin-cellulosic material residuals into fibers, combining it with wax and a resin binder, and then forming panels by applying high temperature and pressure. Because the raw material in the industrial process is ever-changing, the panel industry requires methods for monitoring the composition of their products. The aim of this study was to estimate the ratio of sugarcane (SC) bagasse to Eucalyptus wood in MDF panels using near infrared (NIR) spectroscopy. Principal component analysis (PCA) and partial least square (PLS) regressions were performed. MDF panels having different bagasse contents were easily distinguished from each other by the PCA of their NIR spectra with clearly different patterns of response. The PLS-R models for SC content of these MDF samples presented a strong coefficient of determination (0.96) between the NIR-predicted and Lab-determined values and a low standard error of prediction (similar to 1.5%) in the cross-validations. A key role of resins (adhesives), cellulose, and lignin for such PLS-R calibrations was shown. PLS-DA model correctly classified ninety-four percent of MDF samples by cross-validations and ninety-eight percent of the panels by independent test set. These NIR-based models can be useful to quickly estimate sugarcane bagasse vs. Eucalyptus wood content ratio in unknown MDF samples and to verify the quality of these engineered wood products in an online process.

[O/Fe] ESTIMATES FOR CARBON-ENHANCED METAL-POOR STARS FROM NEAR-INFRARED SPECTROSCOPY

We report on oxygen abundances determined from medium-resolution near-infrared spectroscopy for a sample of 57 carbon-enhanced metal-poor (CEMP) stars selected from the Hamburg/ESO Survey. The majority of our program stars exhibit oxygen-to-iron ratios in the range +0.5 < [O/Fe]< + 2.0. The [O/Fe] values for this sample are statistically compared to available high-resolution estimates for known CEMP stars as well as to high-resolution estimates for a set of carbon-normal metal-poor stars. Carbon, nitrogen, and oxygen abundance patterns for a sub-sample of these stars are compared to yield predictions for very metal-poor asymptotic giant branch (AGB) abundances in the recent literature. We find that the majority of our sample exhibit patterns that are consistent with previously studied CEMP stars having s-process-element enhancements and thus have very likely been polluted by carbon- and oxygen-enhanced material transferred from a metal-poor AGB companion.

Near infrared spectroscopy for soil bulk density assessment

P>Soil bulk density values are needed to convert organic carbon content to mass of organic carbon per unit area. However, field sampling and measurement of soil bulk density are labour-intensive, costly and tedious. Near-infrared reflectance spectroscopy (NIRS) is a physically non-destructive, rapid, reproducible and low-cost method that characterizes materials according to their reflectance in the near-infrared spectral region. The aim of this paper was to investigate the ability of NIRS to predict soil bulk density and to compare its performance with published pedotransfer functions. The study was carried out on a dataset of 1184 soil samples originating from a reforestation area in the Brazilian Amazon basin, and conventional soil bulk density values were obtained with metallic ""core cylinders"". The results indicate that the modified partial least squares regression used on spectral data is an alternative method for soil bulk density predictions to the published pedotransfer functions tested in this study. The NIRS method presented the closest-to-zero accuracy error (-0.002 g cm-3) and the lowest prediction error (0.13 g cm-3) and the coefficient of variation of the validation sets ranged from 8.1 to 8.9% of the mean reference values. Nevertheless, further research is required to assess the limits and specificities of the NIRS method, but it may have advantages for soil bulk density predictions, especially in environments such as the Amazon forest.