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Simultaneous Determination of Clarithromycin, Tinidazole and Omeprazole in Helicure Tablets Using Reflectance Near-Infrared Spectroscopy with the Aid of Chemometry
摘要： A near infrared spectroscopic method for the simultaneous determination of the active principles clarithromycin, tinidazole and omeprazole in a pharmaceutical preparation was developed. The three active principles are quantified using partial least-squares regression methods. The proposed method is applicable over a wide analyte concentration range (80–120%) of labeled content, so it requires careful selection of the calibration set and to ensure thorough homogenization of the product. The method was validated in accordance with the ICH standard validation guidelines for NIR spectroscopy by determining its selectivity, linearity, accuracy, precision and stability. Based on the results, it is an effective alternative to the existing choice (HPLC) for the same purpose.
关键词： Partial least squares,Clarithromycin,Helicure,Near Infrared Spectroscopy,Preprocessing,Genetic algorithm,Multivariate calibration
更新于2025-09-23 15:23:52
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Classification of pre-dyed textile fibers exposed to weathering and photodegradation by non-destructive excitation-emission fluorescence spectroscopy paired with discriminant unfolded-partial least squares
摘要： Undyed textile fabrics such as Acrylic 864, Nylon 361 and Cotton 400 were pre-dyed with Basic Green 4 (BG4), Acid Yellow 17 (AY17) and Direct Blue 1 (DB1) dyes, respectively; and then exposed to two extremely diverse weather conditions in the United States: desert and humid environmental settings in Arizona (AZ) and Florida (FL) respectively, for different time intervals of exposure, which included 0, 3, 6, 9 and 12 months. After every interval of a 3 months period, ten fibers were uniformly sampled from each cloth piece, and fluorescence microscopy was employed to collect two-dimensional excitation and fluorescence spectra (2-D spectra) and three-dimensional (3D) excitation-emission matrices (EEMs). A significant loss of fluorescence intensity was observed upon fiber exposure to outdoor weathering conditions. For a comprehensive statistical data analysis and to be able to discriminate between any two single fibers weathered under different conditions, a multiway calibration algorithm known as discriminant unfolded partial least-squares (DU-PLS) method was applied to the exposed fibers. Results indicate that fluorescence spectroscopy combined with DU-PLS has the ability to appropriately classify and differentiate between any two pairs of dyed cotton or nylon fibers (acrylic in some cases) exposed to dry versus humid weather environments under different time intervals of exposure. These results provide the foundation for future studies towards a non-destructive approach capable to provide information on the weathering history of the fiber.
关键词： Discriminant unfolded partial least squares,Fiber analysis,Photodegradation,Excitation emission matrices,Weathering,Fluorescence spectroscopy
更新于2025-09-23 15:23:52
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Green method by diffuse reflectance infrared spectroscopy and spectral region selection for the quantification of sulphamethoxazole and trimethoprim in pharmaceutical formulations
摘要： An alternative method for the quantification of sulphametoxazole (SMZ) and trimethoprim (TMP) using diffuse reflectance infrared Fourier-transform spectroscopy (DRIFTS) and partial least square regression (PLS) was developed. Interval Partial Least Square (iPLS) and Synergy Partial Least Square (siPLS) were applied to select a spectral range that provided the lowest prediction error in comparison to the full-spectrum model. Fifteen commercial tablet formulations and forty-nine synthetic samples were used. The ranges of concentration considered were 400 to 900 mg g-1 SMZ and 80 to 240 mg g-1 TMP. Spectral data were recorded between 600 and 4000 cm-1 with a 4 cm-1 resolution by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS). The proposed procedure was compared to high performance liquid chromatography (HPLC). The results obtained from the root mean square error of prediction (RMSEP), during the validation of the models for samples of sulphamethoxazole (SMZ) and trimethoprim (TMP) using siPLS, demonstrate that this approach is a valid technique for use in quantitative analysis of pharmaceutical formulations. The selected interval algorithm allowed building regression models with minor errors when compared to the full spectrum PLS model. A RMSEP of 13.03 mg g-1 for SMZ and 4.88 mg g-1 for TMP was obtained after the selection the best spectral regions by siPLS.
关键词： green analytical method,diffuse reflectance infrared Fourier transform spectroscopy,interval partial least squares (iPLS),chemometrics,synergy partial least squares (siPLS),high performance liquid chromatography
更新于2025-09-23 15:22:29
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Predicting Apple Firmness and Soluble Solids Content Based on Hyperspectral Scattering Imaging Using Fourier Series Expansion
摘要： This article reports on using a Fourier series expansion method to extract features from hyperspectral scattering profiles for apple fruit firmness and soluble solids content (SSC) prediction. Hyperspectral scattering images of ‘Golden Delicious’ (GD), ‘Jonagold’ (JG), and ‘Delicious’ (RD) apples, harvested in 2009 and 2010, were acquired using an online hyperspectral imaging system over the wavelength region of 500 to 1000 nm. The moment method and Fourier series expansion method were used to analyze the scattering profiles of apples. The zeroth-first order moment (Z-FOM) spectra and Fourier coefficients were extracted from each apple, which were then used for developing fruit firmness and SSC prediction models using partial least squares (PLS) and least squares support vector machine (LSSVM). The PLS models based on the Fourier coefficients improved the standard errors of prediction (SEP) by 4.8% to 19.9% for firmness and by 2.4% to 13.5% for SSC, compared with the PLS models using the Z-FOM spectra. The LSSVM models for the prediction set of Fourier coefficients achieved better SEP results, with improvements of 4.4% to 11.3% for firmness and 2.8% to 16.5% for SSC over the LSSVM models for the Z-FOM spectra data and 3.7% to 12.6% for firmness and 5.4% to 8.6% for SSC over the PLS models for the Fourier coefficients. Experiments showed that Fourier series expansion provides a simple, fast, and effective means for improving hyperspectral scattering prediction of fruit internal quality when used with either PLS or LSSVM.
关键词： Partial least squares,Soluble solids content,Apples,Least squares support vector machine,Fourier series expansion,Hyperspectral scattering imaging,Firmness
更新于2025-09-23 15:22:29
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Rapid Quantitative Analysis of Forest Biomass Using Fourier Transform Infrared Spectroscopy and Partial Least Squares Regression
摘要： Fourier transform infrared reflectance (FTIR) spectroscopy has been used to predict properties of forest logging residue, a very heterogeneous feedstock material. Properties studied included the chemical composition, thermal reactivity, and energy content. The ability to rapidly determine these properties is vital in the optimization of conversion technologies for the successful commercialization of biobased products. Partial least squares regression of first derivative treated FTIR spectra had good correlations with the conventionally measured properties. For the chemical composition, constructed models generally did a better job of predicting the extractives and lignin content than the carbohydrates. In predicting the thermochemical properties, models for volatile matter and fixed carbon performed very well (i.e., R2 > 0.80, RPD > 2.0). The effect of reducing the wavenumber range to the fingerprint region for PLS modeling and the relationship between the chemical composition and higher heating value of logging residue were also explored. This study is new and different in that it is the first to use FTIR spectroscopy to quantitatively analyze forest logging residue, an abundant resource that can be used as a feedstock in the emerging low carbon economy. Furthermore, it provides a complete and systematic characterization of this heterogeneous raw material.
关键词： FTIR spectroscopy,forest logging residue,energy content,partial least squares regression,thermal reactivity,chemical composition
更新于2025-09-23 15:22:29
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Use of A Portable Camera for Proximal Soil Sensing with Hyperspectral Image Data
摘要： In soil proximal sensing with visible and near-infrared spectroscopy, the currently available hyperspectral snapshot camera technique allows a rapid image data acquisition in a portable mode. This study describes how readings of a hyperspectral camera in the 450–950 nm region could be utilised for estimating soil parameters, which were soil organic carbon (OC), hot-water extractable-C, total nitrogen and clay content; readings were performed in the lab for raw samples without any crushing. As multivariate methods, we used PLSR with full spectra (FS) and also combined with two conceptually different methods of spectral variable selection (CARS, “competitive adaptive reweighted sampling” and IRIV, “iteratively retaining informative variables”). For the accuracy of obtained estimates, it was beneficial to use segmented images instead of image mean spectra, for which we applied a regular decomposing in sub-images all of the same size and k-means clustering. Based on FS-PLSR with image mean spectra, obtained estimates were not useful with RPD values less than 1.50 and R2 values being 0.51 in the best case. With segmented images, improvements were marked for all soil properties; RPD reached values ≥ 1.68 and R2 ≥ 0.66. For all image data and variables, IRIV-PLSR slightly outperformed CARS-PLSR.
关键词： spectral variable selection,hyperspectral snapshot camera,partial least squares regression,multivariate calibration,hyperspectral imaging,proximal soil sensing
更新于2025-09-23 15:22:29
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Proximal VIS-NIR spectrometry to retrieve substance concentrations in surface waters using partial least squares modelling
摘要： Many water quality parameters such as concentrations of suspended matter, nutrients and algae directly or indirectly change the electromagnetic reflectance and transmission properties of surface water bodies. Optical measurement approaches have shown great potential to partially substitute water sampling and laboratory analyses, but are obstructed by limited flexibility or high maintenance demands. In order to overcome these problems and to bridge the gap between in situ and remote sensing measurements, the use of close-range, above-surface reflectance measurements in the VIS-NIR domain to measure water quality parameters in surface water bodies was investigated. Remote sensing reflectance in a 1 m3 water tank with increasing, known concentrations of suspended solids was measured. A partial least squares model was trained to predict concentrations from reflectance curves, which performed well, considering the wide range of concentrations and illumination conditions (R2cal ? 0.96, R2val ? 0.97). The approach was then transferred to the field and further parameters were tested. Using a semi-autonomous spectrometer mounted to a boom stand on a motor boat, we traced substance concentrations in close intervals along a longitudinal gradient from inflow to dam in a drinking water reservoir in Brazil. The method is suitable for parameters directly influencing the reflection properties of the water body (e.g. suspended solids (R2cal ? 0.93), chlorophyll-a (R2cal ? 0.74)), or for parameters closely related to those (e.g. total phosphorus (R2cal ? 0.97)). For chemical oxygen demand, the method is not well suited (R2cal ? 0.14, R2val ? 0.45). Once calibrated to the local conditions, the spectrometer can be used stationary or on moving platforms to map and monitor surface waters. The integration of the procedure into acoustic and imaging techniques is further investigated.
关键词： water quality,suspended solids,hyperspectral,reservoir,partial least squares,proximal sensing
更新于2025-09-23 15:22:29
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Hydrolysis kinetics of silane coupling agents studied by near-infrared spectroscopy plus partial least squares model
摘要： A method of Fourier transform near-infrared (FT-NIR) spectroscopy combined with partial least squares (PLS) model was successfully applied to investigate the hydrolysis kinetics of four kinds of silane coupling agents (phenyltriethoxysilane, vinyltriethoxysilane, 3-mercaptopropyltriethoxysilane, 3-chloropropyltriethoxysilane) in an acid-catalyzed EtOH system. The fast scanning speed and high sensitivity of the FT-NIR spectroscopy, and the powerful data processing ability of the PLS, enabled the method to quantitatively and accurately catch the fast changing H2O concentration during the hydrolysis processes without delay, realizing the study of the fast-paced hydrolysis reactions of the silane coupling agents. The results showed that electrophilic substitution occurred in the hydrolysis reactions, which followed second-order reactions and greatly depend on the catalyst concentration and reaction temperature. The hydrolysis rate constants, activation energy, and Arrhenius Frequency factors were gained. In conclusion, the FT-NIR PLS model is a powerful tool for hydrolysis kinetics researching of the silane coupling agents.
关键词： partial least squares,Hydrolysis kinetic,silane coupling agent,near infrared
更新于2025-09-23 15:22:29
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Surface-enhanced Raman scattering method for the identification of methicillin-resistant Staphylococcus aureus using positively charged silver nanoparticles
摘要： The article describes a SERS-based method for diagnosis of bacterial infections. Positively charged silver nanoparticles (AgNPs+) were employed for identification of methicillin-resistant Staphylococcus aureus (MRSA). It is found that AgNPs+ undergo self-assembly on the surface of bacteria via electrostatic aggregation. The assembled AgNPs+ are excellent SERS substrates. To prove the capability of SERS to differentiate between S. aureus and other microorganisms, six standard strains including S. aureus 29213, S. aureus 25923, C. albicans, B. cereus, E. coli, and P. aeruginosa were tested. To further demonstrate its applicability for the identification of MRSA in clinical samples, 52 methicillin-sensitive S. aureus (MSSA) isolates and 215 MRSA isolates were detected by SERS. The total measurement time (include incubation) is 45 min when using a 3 μL sample. The method gives a strongly enhanced Raman signal (at 730 cm?1 and 1325 cm?1) with good reproducibility and repeatability. It was successfully applied to the discrimination of the six strain microorganisms. The typical Raman peaks of S. aureus at 730, 1154, 1325, and 1457 cm?1 were observed, which were assigned to the bacterial cell wall components (730 cm?1- adenine, glycosidic ring mode, 1154 cm?1- unsaturated fatty acid, 1325 cm?1- adenine, polyadenine, and 1457 cm?1 for -COO- stretching). S. aureus was completely separated from other species by partial least squares discriminant analysis (PLS-DA). Moreover, 52 MSSA isolates and 215 MRSA isolates from clinical samples were identified by PLS-DA. The accuracy was almost 100% when compared to the standard broth microdilution method. A classification based on latent structure discriminant analysis provided spectral variability directly. Conceivably, the method offers a potent tool for the identification of bacteria and antibiotics resistance, and for studies on antibiotic-resistance in general.
关键词： S. aureus,Nanoparticles,Methicillin resistance,Antibiotics,Latent structure discriminant analysis classification (OPLS-DA),SERS,Partial least squares discriminant analysis (PLS-DA),AgNPs,Discriminant analysis,Raman spectroscopy
更新于2025-09-23 15:22:29
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Novel spectrophotometric and factor-based multivariate calibration-prediction techniques for determination of two inhibitors of hepatitis C-virus and hepatocellular carcinoma in pure, human urine, and human plasma
摘要： Novel univariate and multivariate factor-based calibration-prediction techniques were validated for simultaneous ultraviolet spectrophotometric determination of ribavirin (RIV), daclatasvir (DAV), sofosbuvir (SOV), and sorafenib (SON) which are co-administered for treatment of hepatocellular carcinoma (HCC) that results from Hepatitis C-virus (HCV) infection in their commercial products and in biological fluids. Determination of these compounds is essential owing to their pharmacotherapeutic benefits. Due to spectral overlapping of RIV, DAV, SOV, and SON, univariate extended derivative ratio (EDR) method and multivariate partial least-squares (PLS) and principal component regression (PCR) methods were used for constructing the calibration curves. The extended derivative ratio (EDR) absorption maxima at 215 nm and minima at 310.5 nm was used for determination of RIV and DAV, respectively and absorption maxima at 240.3 nm and minima at 284.5 nm for determination of SOV and SON, respectively. The linearity was established over the range of (6-42) μgmL-1, (4-16) μgmL-1, (10-70) μgmL-1, and (3-9) μgmL-1 for RIV, DAV, SOV and SON with correlation coefficient (r2) of 0.9997, 0.9997, 0.9999 and 0.9997, respectively. This method was effectively applied to pure, pharmaceutical preparations and to spiked human urine and plasma. PLS and PCR models were established for the determination of the studied drugs in the range of (6-42), (4-16), (10-70) and (3-9) μgmL-1 for RIV, DAV, SOV, and SON, respectively. Furthermore, updating the PLS model (PLS model update) were allowed for the determination of these drugs in spiked human urine, plasma and drug-dissolution test of their tablets. The obtained results were compared to official and reported method showing that there were no significant differences. The results of applying PLS and PCR models for evaluation of RIV, DAV, SOV, and SON in human urine samples as real samples were also encouraging. It is expected that the suitable features of the proposed method make it helpful for biological and clinical applications.
关键词： Partial least-squares,Extended derivative ratio,Chemometric,Spectrophotometric,Principal component regression
更新于2025-09-23 15:22:29