Using chemometric methods and NIR spectrophotometry in the textile industry

A quantitative and qualitative technique for identification of textiles, moisture measurements, textile coatings and process control was developed, using near infra-red spectroscopy (NIR) in combination with chemometric methods. These applications demonstrate by the use of computer assisted data processing the possibility of identifying textile fibers, not only for quality control but also for online textile recycling processes. In this study, seven various textile fibers (cotton, polyester, viscose, silk, wool, polyacrylonitrile, acetate) were used and all combinations of two factor blends were qualitatively identified using NIR spectroscopy and the chemometric PLS2 method for the calibration.

A quantitative analysis of textile moisture can also be performed with this technique. Water content above 50% does not deliver good results for a calibration set to determine the dampness of fibers. But to measure residual moisture from ≈0.05 up to 50%, the NIR technique is particularly good. Furthermore, the examination shows that the NIR method and chemometric methods can be used in quality- and product-control during the industrial production of upholstery fabrics. With this technique it will be possible to identify nylon flocks and to measure the residual moisture of the flocks and fabric, too.     

The transfer between instruments of a reflectance near-infrared assay for paracetamol in intact tablets

This study compares several correction methods to facilitate the transfer of a validated near-infrared (NIR) assay for paracetamol in intact tablets between two reflectance NIR instruments of the same type. Transfer was defined as the ability to accurately predict the true assay value of a sample measured on a NIR system using an assay developed on a different system, and was assessed using a comprehensive set of statistical tests. Direct electronic transfer of the calibration models, representing the NIR assay, was not possible as a result of a definite residual spectrum between instruments. The use of a correction method based on the standardisation of the material used to record the reference spectrum also proved ineffective. Two methods investigated did succeed, the first employed a response surface calculated between the reflectance values of a set of six certified photometric standards measured on both instruments, with all full range partial least square (PLS) regression models subsequently transferred. The next was correction of the spectra from the second instrument utilising the residual spectrum between the mean sample of the validation set measured on both instruments. Through this approach all PLS regression models and also a single multiple linear regression (MLR) model were transferred. As an outcome of this study guidelines are suggested for the transfer of NIR assays along with the criteria deemed necessary to conclusively prove transfer and justify any correction method utilised. The significant criteria were determined to be the paired t-test with both the UV reference assay data and the original NIR assay data, and comparison of the coefficient of multiple determinations.     

NIR analysis of pharmaceutical samples without reference data: improving the calibration

Using an appropriate set of samples to construct the calibration set is crucial with a view to ensuring accurate multivariate calibration of NIR spectroscopic data. In this work, we developed and optimized a new methodology for incorporating physical variability in pharmaceutical production based on the NIR spectrum for the process. Such a spectrum contains the spectral changes caused by each treatment applied to the component mixture during the production process. The proposed methodology involves adding a set of process spectra (viz. difference spectra between those for production tablets and a laboratory mixture of identical nominal composition) to the set of laboratory samples, which span the wanted concentration range, in order to construct a calibration set incorporating all physical changes undergone by the samples in each step of the production process. The best calibration model among those tested was selected by establishing the influence of spectral pretreatments used to obtain the process spectrum and construct the calibration models, and also by determining the multiplying factor m to be applied to the process spectra in order to ensure incorporation of all variability sources into the calibration model. The specific samples to be included in the calibration set were selected by principal component analysis (PCA). To this end, the new methodology for constructing calibration sets for determining the Active Principle Ingredients (API) and excipients was applied to Irbesartan tablets and validated by application to the API and excipients of paracetamol tablets. The proposed methodology provides simple, robust calibration models for determining the different components of a pharmaceutical formulation.     

Near-infrared spectroscopy and multivariate calibration for the quantitative determination of certain properties in the petrochemical industry

Near-infrared (NIR) spectroscopy in conjunction with chemometric techniques allows on-line monitoring in real time, which can be of considerable use in industry. If it is to be correctly used in industrial applications, generally some basic considerations need to be taken into account, although this does not always apply. This study discusses some of the considerations that would help evaluate the possibility of applying multivariate calibration in combination with NIR to properties of industrial interest. Examples of these considerations are whether there is a relation between the NIR spectrum and the property of interest, what the calibration constraints are and how a sample-specific error of prediction can be quantified. Various strategies for maintaining a multivariate model after it has been installed are also presented and discussed.     

Rapid determination of the glucose content of molasses using a biosensor

A knowledge of the sugar content of molasses is of commercial importance to a number of industrial fermentations. Hence the feasibility of using a glucose oxidase biosensor to determine the glucose content of molasses samples was investigated. This method was compared with standard high-performance liquid chromatographic (HPLC) and gas-liquid chromatographic (GLC) procedures and with the use of a commercially available glucose analyser. A good correlation was obtained between the standard acetic anhydride GLC and glucose oxidase biosensor results (correlation coefficient = 0.98). Rapid and accurate measurements could be carried out using the biosensor without the need to employ the sample preparation step required in standard GLC methods. It was concluded that the use of the biosensor technique for the determination of glucose in molasses samples has distinct advantages over conventional methods.     

Comparison of near infrared and microwave resonance sensors for at-line moisture determination in powders and tablets

In this paper we demonstrate the feasibility of replacing KF for water content testing in bulk powders and tablets with at-line near infrared (NIR) or microwave resonance (MR) methods. Accurate NIR and MR prediction models were developed with a minimalistic approach to calibration. The NIR method can accurately predict water content in bulk powders in the range of 0.5-5% w/w. Results from this method were compared to a MR method. We demonstrated excellent agreement of both NIR and MR methods for powders vs. the reference KF method. These methods are applicable to in-process control or quality control environments. One of the aims of this study was to determine if a calibration developed for a particular product could be used to predict the water content of another product (with related composition) but containing a different active pharmaceutical ingredient (API). We demonstrated that, contrary to the NIR method, a general MR method can be used to predict water content in two different types of blends. Finally, we demonstrated that a MR method can be developed for at-line moisture determination in tablets.     

Monitoring and control of industrial downstream processing of sugar beet molasses

In present work the determination of several amino acids during the industrial chromatographic desugarisation of molasses is presented. The use of innovative biosensor systems for highly specific detection of serine is described. Using two-dimensional fluorescence spectrometry, a non-invasive method for the determination of several product fractions could be established in an industrial chromatographic procedure.     

A rapid quantitative assay of intact paracetamol tablets by reflectance near-infrared spectroscopy

Near-infrared (NIR) reflectance spectroscopy was used to determine rapidly and non-destructively the content of paracetamol in bulk batches of intact Sterwin 500 mg tablets by collecting NIR spectra in the range 1100-2500 nm and using a multiple linear regression calibration method. The developed NIR method gave results comparable to the British Pharmacopoeia 1993 UV assay procedure, the standard errors of calibration and prediction being 0.48% and 0.71% m/m, respectively. The method showed good repeatability, the standard deviation and coefficient of variation for six NIR assays on the same batch on the same day being 0.14 and 0.16% m/m, respectively, while measurements over six consecutive days gave 0.31 and 0.36% m/m, respectively. Applying the calibration to a parallel test set gave a mean bias of -0.22% and a mean accuracy of 0.45%. The developed method illustrates how the full potential of NIR can be utilised and how the ICH guidelines which recommend the validation of linearity, range, accuracy and precision for pharmaceutical registration purposes can be applied. Duplicate determinations on bulk batches could be performed in under 2 min, allowing the potential use of the method on-line for real time monitoring of a running production process.     

Orthogonal signal correction applied to the classification of wine and molasses vinegar samples by near-infrared spectroscopy. Feasibility study for the detection and quantification of adulterated vinegar samples

The most common fraudulent practice in the vinegar industry is the addition of alcohol of different origins to the base wine used to produce wine vinegar with the objective of reducing manufacturing costs. The mixture is then sold commercially as genuine wine vinegar, thus constituting a fraud to consumers and an unfair practice with respect to the rest of the vinegar sector. A method based on near-infrared spectroscopy has been developed to discriminate between white wine vinegar and alcohol or molasses vinegar. Orthogonal signal correction (OSC) was applied to a set of 96 vinegar NIR spectra from both original and artificial blends made in the laboratory, to remove information unrelated to a specific response. The specific response used to correct the spectra was the extent of adulteration of the vinegar samples. Both raw and corrected NIR spectra were used to develop separate classification models using the potential functions method as a class-modeling technique. The previous models were compared to evaluate the suitability of near-infrared spectroscopy as a rapid method for discrimination between vinegar origin. The transformation of vinegar NIR spectra by means of an orthogonal signal-correction method resulted in notable improvement of the specificity of the constructed classification models. The same orthogonal correction approach was also used to perform a calibration model able to detect and quantify the amount of exogenous alcohol added to the commercial product. This regression model can be used to quantify the extent of adulteration of new vinegar samples.     

Development of a rapid process monitoring method for dry-coated tableting process by using near-infrared spectroscopy

A nondestructive transmittance near-infrared (NIR) method for detecting off-centered cores in dry-coated (DC) tablets was developed as a monitoring system in the DC tableting process. Caffeine anhydrate was used as a core active pharmaceutical ingredient (API), and DC tablets were made by the direct compression method. NIR spectra were obtained from these intact DC tablets using the transmittance method. The reference assay was performed with HPLC. Calibration models were generated by partial least squares (PLS) regression and principal component regression (PCR) utilizing external validations. Hierarchical cluster analysis (HCA) of the results confirmed that NIR spectroscopy correctly detected off-centered cores in DC tablets. We formulated and used the Centering Index (CI) to evaluate the precision of core alignment and generated an NIR calibration model that could correctly predict this index. The principal component (PC) 1 loading vector of the final calibration model indicated that it could specifically detect the misalignment of tablet cores. The model also had good linearity and accuracy. The CIs of unknown sample tablets predicted by the final calibration model and those calculated through the HPLC analysis were closely parallel with each other. These results demonstrate the validity of the final calibration model and the utility of the transmittance NIR spectroscopic method developed in this study as a monitoring system in DC tableting process.     

Comparison of near-infrared and mid-infrared spectroscopy for the determination of distillation property of kerosene

Near-infrared (NIR) and mid-infrared (MIR) spectroscopy have been compared and evaluated for the determination of the distillation property of kerosene with the use of partial least squares (PLS) regression. Since kerosene is a complex mixture of similar hydrocarbons, both spectroscopic methods will be best evaluated with this complex sample matrix. PLS calibration models for each percent recovery temperature have been developed by using both NIR and MIR spectra without spectral pretreatment. Both methods have shown good correlation with the corresponding reference method, however NIR provided better calibration performance over MIR. To rationalize the improved calibration performance of NIR, spectra of the same kerosene sample were continuously collected and the corresponding spectral reproducibility was evaluated. The greater spectral reproducibility including signal-to-noise ratio of NIR led to the improved calibration performance, even though MIR spectroscopy provided more qualitative spectral information. The reproducibility of measurement, signal-to-noise ratio, and richness of qualitative information should be simultaneously considered for proper selection of a spectroscopic method for quantitative analysis.     

Quality control of pharmaceuticals with NIR: From lab to process line

This work describes a general framework for assessing the active pharmaceutical ingredient (API) and excipient concentrations simultaneously in pharmaceutical dosage forms based on laboratory-scale measurements. The work explores the comprehensive development of a near infrared (NIR) analytical protocol for the quantification of the API and excipients of a pharmaceutical formulation. The samples were based on a paracetamol (API) formulation with three excipients: microcrystalline cellulose, talc, and magnesium stearate. The developed method was based on laboratory-scale samples as calibration samples and pilot-scale samples (powders and tablets) as model test samples. Both types of samples were produced according to an experimental design. The samples were measured in reflectance mode in a Fourier-transform NIR spectrometer. Additionally, a new method for determining the minimum number of calibration samples was proposed. It was concluded that the use of laboratory-scale samples to construct the calibration set is an effective way to ensure the concentration variability in the development of calibration models for industrial applications. With this method, both API and excipients can be determined in high-throughput applications in the pharmaceutical industry.     

How to overcome matrix effects in the determination of pesticides in fruit by HPLC-ESI-MS-MS

A high-performance liquid chromatographic method, with electrospray ionisation tandem mass spectrometry (HPLC-ESI-MS-MS) for detection, has been developed for the determination of thiabendazole, carbendazime, and phenylurea pesticides in fruit matrices. During the validation process the method was tested for matrix effects, blanks, and the stability of the system. Considerable unspecific matrix effects in the ESI (+) process were detected by comparing standard calibration, and matrix calibration, although blank values were very low and the specific calibration functions showed only small standard deviations. This effect was overcome by using a more complex clean-up, i.e. an additional size-exclusion step.     

Complete quality analysis of commercial surface-active products by Fourier-transform near infrared spectroscopy

Using proper calibration data Fourier-transform near infrared spectroscopy is used for developing multivariate calibrations for different analytical determinations routinely used in the surfactants industry. Four products were studied: oleyl-cetyl alcohol polyethoxylated, cocamidopropyl betaine (CAPB), sodium lauryl sulfate (SLS) and nonylphenol polyethoxylated (NPEO). Calibrations for major as well as very low concentrated compounds were achieved and every model was validated through linearity, bias, accuracy and precision tests, showing good results and the viability of NIR spectroscopy as a full quality control method for this products. Duplicate and complete analysis on a single sample takes at most 3 min, requiring neither sample preparation nor the use of reagents. The analytical reference procedures involved in this work represent the typical ones used in the industry and the NIR method shows good results in the analysis of components with weight concentrations less than 1%.     

Determination of chlorogenic acid in plant samples by using near-infrared spectrum with wavelet transform preprocessing.

By theoretical analysis, it is found that wavelet transform (WT) with a wavelet function can be regarded as a smoothing and a differentiation process, and that the order of differentiation is determined by the vanishing moment, which is an important property of a wavelet function. Therefore, a method based on the continuous wavelet transform (CWT) for removing the background in the near-infrared (NIR) spectrum is proposed, and it is used in the determination of the chlorogenic acid in plant samples as a preprocessing tool for partial least square (PLS) modeling. It is shown that the benefit of the proposed method lies not only in its performance to improve the quality of PLS model and the prediction precision, but also in its simplicity and practicability. It may become a convenient and efficient tool for preprocessing NIR spectral data sets in multivariate calibration.     

Near infrared reflectance spectroscopy as a tool for the control of sheep leather defatting

The fat content is one of the variables to be controlled by the tanning industry with a view to obtaining leather for various commercial purposes. Ensuring the production of quality leather products frequently entails using some defatting treatment, particularly when the raw skin is rich in natural fat. The official method for determining fat in leather, IUC 4, is rather slow; also, it uses polluting reagents and involves powdering samples for Soxhlet extraction with low-polarity solvents. The combination of NIR diffuse reflectance spectroscopy as implemented with a fibre-optic probe and multivariate calibration is probably the best choice for the direct determination of fat in leather and the monitoring of leather defatting.In this work, a method for the determination of fat in leather and the control of the defatting process in an expeditious manner and with no sample treatment was developed. Defatting tests were conducted on leather specimens from lambs of various breeds and origins in order to span as wide as possible a range of variability in their properties and natural fat content. The NIR spectra used to construct the calibration matrices were recorded directly on the leather samples prior to and after defatting. Fat contents were determined by partial least-squares regression (PLSR), using the values obtained with the official method as references. Notwithstanding the complex nature of leather, the calibration models used provided good external predictions: the largest overall relative error, obtained by using a single calibration matrix for natural and defatted specimens, was 10%. The proposed method is therefore an advantageous alternative to the official method.     

Near infrared and Raman spectroscopy as Process Analytical Technology tools for the manufacturing of silicone-based drug reservoirs

Using near infrared (NIR) and Raman spectroscopy as PAT tools, 3 critical quality attributes of a silicone-based drug reservoir were studied. First, the Active Pharmaceutical Ingredient (API) homogeneity in the reservoir was evaluated using Raman spectroscopy (mapping): the API distribution within the industrial drug reservoirs was found to be homogeneous while API aggregates were detected in laboratory scale samples manufactured with a non optimal mixing process. Second, the crosslinking process of the reservoirs was monitored at different temperatures with NIR spectroscopy. Conformity tests and Principal Component Analysis (PCA) were performed on the collected data to find out the relation between the temperature and the time necessary to reach the crosslinking endpoints. An agreement was found between the conformity test results and the PCA results. Compared to the conformity test method, PCA had the advantage to discriminate the heating effect from the crosslinking effect occurring together during the monitored process. Therefore the 2 approaches were found to be complementary. Third, based on the HPLC reference method, a NIR model able to quantify the API in the drug reservoir was developed and thoroughly validated. Partial Least Squares (PLS) regression on the calibration set was performed to build prediction models of which the ability to quantify accurately was tested with the external validation set. The 1.2% Root Mean Squared Error of Prediction (RMSEP) of the NIR model indicated the global accuracy of the model. The accuracy profile based on tolerance intervals was used to generate a complete validation report. The 95% tolerance interval calculated on the validation results indicated that each future result will have a relative error below ±5% with a probability of at least 95%. In conclusion, 3 critical quality attributes of silicone-based drug reservoirs were quickly and efficiently evaluated by NIR and Raman spectroscopy.     

宁夏枸杞甜菜碱提取物高效液相色谱指纹图谱研究

建立宁夏枸杞甜菜碱提取物高效液相色谱指纹图谱,为鉴别不同来源的宁夏枸杞提供依据。以10批宁夏不同产地的宁夏枸杞主栽品种"宁杞Ⅰ号"样品建立枸杞甜菜碱提取物指纹图谱共有模式,采用"中药色谱指纹图谱相似度评价系统"软件进行数据处理,对15批不同来源的枸杞样品进行了分析。结果表明:8个特征峰构成了宁夏枸杞甜菜碱提取物的色谱指纹图谱,不同产地、不同品种的枸杞样品甜菜碱提取物指纹图谱存在差异;建立的枸杞甜菜碱提取物高效液相色谱(HPLC)指纹图谱对不同产地、不同品种枸杞的鉴别有参考价值。     

近红外光谱法快速测定涂料固化剂中游离甲苯二异氰酸酯含量

用气相色谱分析值为参照,采用近红外透射光谱（NIR）技术采集相应样品的NIR光谱,研究了涂料固化剂中游离甲苯二异氰酸酯（TDI）含量的快速测定分析方法。 并从120个固化剂样品中挑选出109个代表性的样品建模,选择7320~7250 cm-1和8485~8370 cm-1波段区间,用偏最小二乘法(PLS)和完全交互验证方式建立TDI含量的预测模型。 结果表明,固化剂中游离甲苯二异氰酸酯含量和近红外光谱之间存在较好的相关性,其预测模型的校正集均方差（RMSEC）为0.0815,验证集均方差（RMSEP）为0.0715,模型性能良好。 近红外光谱法可快速准确测定游离甲苯二异氰酸酯（TDI）含量,用于固化剂样品快速分析。     

Qualitative and quantitative analysis of oxytetracycline by near-infrared spectroscopy

Near-infrared (NIR) spectroscopy, in combination with chemometrics, enable the analysis of raw materials without time-consuming sample preparation methods. The aim of our work was to estimate critical parameters in the analytical specification of oxytetracycline, and consequently the development of a method for quantification and qualification of these parameters by NIR spectroscopy. A Karl Fischer (K.F.) titration to determine the water content, a colorimetric assay method, and Fourier transform-infrared (FT-IR) spectroscopy to identify the oxytetracycline base, were used as reference methods, respectively. Multivariate calibration was performed on NIR spectral data using principal component analysis (PCA), partial least-squares (PLS 1) and principal component regression (PCR) chemometric methods. Multivariate calibration models for NIR spectroscopy have been developed. Using PCA and the Soft Independent Modelling of Class Analogy (SIMCA) approach, we established the cluster model for the determination of sample identity. PLS 1 and PCR regression methods were applied to develop the calibration models for the determination of water content and the assay of the oxytetracycline base. Comparing the PLS and PCR regression methods we found out that the PLS is better established by NIR, especially as the spectroscopic data (NIR spectra) are highly collinear and there are many wavelengths due to non-selective wavelengths. The calibration models for NIR spectroscopy are convenient alternatives to the colorimetric method and to the K.F. method, as well as to FT-IR spectroscopy, in the routine control of incoming material.