Partial least squares-near infrared determination of pesticides in commercial formulations

A solvent free, fast and environmentally friendly near infrared-based methodology (NIR) was developed for pesticide determination in commercially available formulations. This methodology was based on the direct measurement of the diffuse reflectance spectra of solid samples and a multivariate calibration model (partial least squares, PLS) to determine the active principle concentration in commercial formulations. The PLS calibration set was built on using the spiked samples by mixing different amounts of pesticide standards and powdered samples. Buprofezin, Diuron and Daminozide were used as test analytes. Concentration of Buprofezin in the samples was calculated employing a 4-factors PLS calibration using the spectral information in the range between 2231–2430 and 1657–1784 nm. For Diuron determination a 1-factor PLS calibration model using the spectral range 1110–2497 nm, after a linear removed correction. Daminozide determination was carried out employing a 4-factors PLS model using the spectral information in the ranges 1644–1772 and 2014–2607 nm without baseline correction. The root mean square errors of prediction (RMSEP) found were 1.1, 1.7 and 0.7% (w/w) for Buprofezin, Diuron and Daminozide determination, respectively. The developed PLS-NIR procedure allows the determination of 120 samples/h, does not require any sample pre-treatment and avoids waste generation.     

Determination of captopril in pharmaceutical preparation and biological fluids using two- and three-way chemometrics methods

Spectrophotometric method has been developed for the direct quantitative determination of captopril in pharmaceuticalpreparation and biological fluids(human plasma and urine)samples.The method was accomplished based on parallel factoranalysis(PARAFAC)and partial least squares(PLS).The study was carried out in the pH range from 2.0 to 12.8 and with aconcentration from 0.70 to 61.50 μg mL~(-1)of captopril.Multivariate calibration models such as PLS at various pH and PARAFACwere elaborated from ultraviolet spectra deconvolution and captopril determination.The best models for this system were obtainedwith PARAFAC and PLS at pH 2.0.The applications of the method for determination of real samples were evaluated by analysis ofcaptopril in pharmaceutical preparations and biological fluids with satisfactory results.The accuracy of the method,evaluatedthrough the RMSEP,was 0.5801 for captopril with best calibration curve by PARAFAC and 0.6168 for captopril with PLS at pH 2.0model.     

The decontamination of industrial casein and milk powder by irradiation

The efficacy of gamma radiation decontamination of industrial casein, a milk protein utilized as a component of many food and non-food products has been studied. Low-fat milk powder was also included with a purpose to study the microflora survival in protein-rich materials. Microbial analysis of the samples prior to irradiation showed that the initial total viable count was higher than 6.0 log cfu g⁻¹ in both casein and milk powders. The contamination of casein with moulds and yeasts was found to be equal to 3.56 log cfu g⁻¹. The counts of coliforms have not exceeded the value of 2.48 log cfu g⁻¹. Radiation processing of casein and milk powder has substantially reduced the microbial population of all samples. The dose of 5 kGy was sufficient to reduce the total microflora and coliforms counts to the level permitted for food products. Survivals of microorganisms were analyzed by the generalized exponential equation, SF=exp[−D/D_o)^α]. Values of an exponent, α, standing for the dispersion parameter, were equal to 0.65 and 0.70 for microorganisms contaminating casein and milk powders, respectively. The numerical value of the dispersion parameter α<1 indicates the concave dependence of a logarithm of surviving fraction versus radiation dose. No difference in microflora survival in irradiated samples tested immediately and in samples stored for 1-month after irradiation has been noticed.     

Robust absorbance computations in the analysis of glucose by near-infrared spectroscopy

Procedures for data acquisition and data processing are evaluated for the optimal computation of absorbance values based on Fourier transform near-infrared transmission spectra. Samples consisting of physiological levels (1–20 mM) of glucose in an aqueous matrix of variable levels of bovine serum albumin and triacetin are studied in the combination spectral region (5000–4000 cm⁻¹). The weak glucose signals in this region define a challenging analysis that is extremely sensitive to the effects of instrumental drift. The impact of different procedures for obtaining absorbance estimates is evaluated in the context of multivariate calibration models based on partial least-squares (PLS) regression. Replicate calibration and prediction data acquired over 6 months are used to study the robustness of PLS models with respect to time. The recommended protocol for the absorbance calculations is based on the collection of a large group of individual background spectra during the instrumental warm-up period. Seven procedures are tested for obtaining optimal backgrounds for use with either the calibration or prediction data sets. When the developed methodology is employed, standard errors of prediction are maintained in the range of 1.0 mM for spectra acquired up to 6 months after the collection of the calibration data. This level of performance compares favorably to daily internal cross-validation errors of 0.5–0.9 mM.     

A quality control method for geranium oil based on vibrational spectroscopy and chemometric data analysis

Rose-scented geranium, a commercially important cultivar originating from Pelargonium graveolens L’Her. ex Ait., is a high value essential oil extensively used in flavour and fragrance formulations. The oil is variable in composition with ‘Bourbon geranium’ (from Reunion Island) regarded as the highest quality geranium oil. Quality assessment of geranium oil involves profiling seven major volatile constituents (geraniol, citronellol, geranyl formate, citronellyl formate, linalool, isomenthone and guaia-6,9-diene) using gas chromatography (GC). The aim of this study was to explore the feasibility of vibrational spectroscopy in tandem with chemometric methods as a rapid and low-cost alternative quality control method. Geranium oil samples (n = 70) were obtained from different suppliers representing cultivation sites in South Africa, Egypt, India, Reunion Island, China and Madagascar. Reference analysis was performed using gas chromatography coupled to mass spectrometry (GC–MS). The mid-infrared (MIR) and near-infrared (NIR) spectra of the oils were recorded with a total of 32 scans accumulated for each sample. Partial least squares (PLS) multivariate calibration models were developed. The calibration models obtained for both MIR and NIR data produced good correlation coefficients (R² > 0.90) between the predicted and reference values for all seven marker molecules. Generally, the error parameters (RMSEE and RMSEP) after external validation were low (<1.0%) for all compounds guaranteeing reliable predictions. The results show convincingly the potential of both MIRS and NIRS as alternative methods that can be used in quality assessment of geranium oil providing sufficiently accurate results.     

Determination of phenylephrine hydrochloride and chlorpheniramine maleate in binary mixture using chemometric-assisted spectrophotometric and high-performance liquid chromatographic-UV methods

Four methods have been developed for the simultaneous determination of phenylephrine hydrochloride and chlorpheniramine maleate without previous separation. In the first method both drugs are determined using first derivative UV spectrophotometry, with zero-crossing measurement. The second method depends on first derivative of the ratios spectra. The third method describes the use of multivariate spectrophotometric calibration for the simultaneous determination of the analyzed binary mixture where the resolution is accomplished by using partial least squares (PLS) regression analysis. In the fourth method (HPLC), a reversed-phase column and a mobile phase of methanol:water:acetonitrile (80:12:8 v/v/v/) at 0.9 ml/min flow rate have been used to separate both drugs with a UV detection at 270 nm. All the proposed methods are extensively validated. They have the advantage to be economic and time saving. All the described methods can be readily utilized for analysis of pharmaceutical formulations. The results obtained using the proposed methods are statistically analyzed and compared with some reported methods.     

Effect of Rutile on Modulus of Rupture in Ceramic Glaze

The study was focused on the performance of rutile addition in glaze composition for antibacterial application. Rutile powder in micro size (ξηзm) were added in the glaze composition at different weight percentage (5 wt%, 7 wt%, 9 wt%, 10 wt% and 15 wt%). Glazing was performed by dipping technique for 10 seconds. Glazed tile was then sintered at 1200 °C for 1 hour. Characterizations used to observe the properties of produced tiles were physical observation, scanning electron microscopy (SEM) and modulus of rupture. Results show that cracking occurred in glazed tile which could be related to the viscosity of the glaze mixture during dipping. The relation between viscosity and the occurrence of crack depend on the amount of rutile The amount of crack appearance increases with increasing glaze viscosity. However, modulus of rupture increased when the tile was glazed.     

Free sulphite determination in wine using screen-printed carbon electrodes with prior gas-diffusion microextraction

Gas-diffusion microextraction was employed in the extraction of sulphites in wines aiming their electrochemical determination, which was achieved by square-wave voltammetry using screen-printed carbon electrodes. Sulphites are additives commonly used in many produced goods, particularly food products. The developed methodology showed good limits of detection (0.4 mg L^− 1) and quantification (1.3 mg L^− 1). The proposed method was also compared with the reference methodology used by the wine industry (the Ripper method, an iodometry) showing no significant differences in the obtained results. Therefore, a simple, cheap and portable alternative for the determination of sulphites in wine is presented.     

Study of products yield of bagasse and sawdust via slow pyrolysis and iron-catalyze

In this paper, the via slow pyrolysis behavior of the bagasse and sawdust were studied at the different heating rates, the different iron-containing blend pyrolysis and the treatment temperature, the further understood for the pyrolysis of agricultural residues. The distribution of the products yield of the slow pyrolysis process, it is typically performed at temperature between 200 and 600 °C, the pyrolysis temperature increased, the bio-liquids and gas yields tended to increase, which at 400 °C was able to achieve maximum bio-liquids yields, the biochar yields tended to downward. For different heating rate, in the heating rate ranges for 80–100 W, the bio-liquids products yield curve increased from 44.5 wt% to 46.5 wt% for bagasse; the sawdust products yield increased from 41 wt% to 42.75 wt%. Iron-catalysts blend pyrolysis (0, 10, 25, 40 and 50 wt%), the bagasse bio-liquid yields respectively 56.25 wt% in the presence 50% iron-catalysts blend pyrolysis; the sawdust bio-liquid yields respectively 52.5 wt% in the presence 40% iron-catalysts blend. The pyrolysis process were calculated according to the kinetic mechanism were examined, the pyrolysis activation energy was between 6.55 and 7.49 kcal/mol for bagasse. Sawdust the pyrolysis activation energy was between 11.52 and 11.76 kcal/mol. Therefore, in this study a pyrolysis model of bagasse and sawdust thermal treatment may provide both agricultural and forestry transformation importance of resources.     

Preparation,characterization and catalytic activity of MoO3/CeO2–ZrO2 solid heterogeneous catalyst for the synthesis of β-enaminones

A series of CeO₂–ZrO₂ with different molybdenum (8–20 wt% MoO₃) loaded materials were prepared by homogeneous co-precipitation followed by impregnation method. The prepared materials were tested for their catalytic activity performance in the synthesis of β-enaminones by condensation of various anilines with dimedone under solvent-free conditions in microwave providing excellent yields within short reaction time. An obtained result reveals that, catalytic activity increases with increase in Mo wt% loading. The particle size of prepared materials was estimated using Debye–Scherrer equation. Particle size increases with increase in Mo wt% loading providing nanosized particle ranging from 7.11 to 42.09 nm. The synthesized materials were characterized by means of X-ray powder diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) techniques.     

Experimental methodology for precise determination of density of RTILs as a function of temperature and pressure using vibrating tube densimeters

A specific calibration procedure that allows the accurate determination of densities of room temperature ionic liquids, RTILs, as a function of temperature and pressure using vibrating tube densimeters is presented. This methodology overcomes the problems of common calibration methods when they are used to determine the densities of high density and high viscosity fluids such as RTILs. The methodology is applied for the precise density determination of RTILs 1-ethyl-3-methylimidazolium tetrafluoroborate [Emim][BF₄], 1-butyl-3-methylimidazolium tetrafluoroborate [Bmim][BF₄], 1-hexyl-3-methylimidazolium tetrafluoroborate [Hmim][BF₄], and 1-octyl-3-methylimidazolium tetrafluoroborate [Omim][BF₄] in the temperature and pressure intervals (283.15 to 323.15) K and (0.1 to 60) MPa, respectively. The viscosities of these substances, needed for the estimation of the viscosity-induced errors, were estimated at the same conditions from the experimental measurements in the intervals (283.15 to 323.15) K and (0.1 to 14) MPa and from a specific extrapolation procedure. The uncertainty in the density measurements was estimated in ±0.30 kg · m^?3 which is an excellent value in the working intervals. The results of these RTILs have demonstrated that viscosity-induced errors are relevant and they must be taken into account for a precise density determination. Finally, an alternative tool for a simpler application of this procedure is presented.     

Influence of FCC catalyst steaming on HDPE pyrolysis product distribution

A commercial FCC catalyst based on a zeolite active phase has been used in the catalytic pyrolysis of HDPE. The experimental runs have been carried out in a conical spouted bed reactor provided with a feeding system for continuous operation. Different treatments have been applied to the catalyst to improve its behaviour. This paper deals with the optimization of catalyst steaming and pyrolysis temperature in order to maximize the production of diesel-oil fraction. The performance of the fresh catalyst has been firstly studied at 500 °C. This catalyst gives way to 52 wt% gas yield, 35 wt% light liquid fraction and a low yield of C₁₀⁺ fraction (13 wt%). After mild steaming (5 h at 760 °C) the results show a significant improvement in product distribution. Thus, gas yield decreases to 22 wt%, the yield of light liquid is similar to that of the fresh one (38 wt%), whereas the yield of the desired C₁₀⁺ fraction increases to 38 wt%. Nevertheless, the best results have been obtained when a severe steaming is applied to the catalyst (8 h at 816 °C) and pyrolysis temperature is reduced to 475 °C. There is a significant reduction in the gaseous fraction (8 wt%). The light liquid fraction has also been reduced to 22 wt%, but the yield of diesel fraction increases to 69 wt%. Moreover, the deactivation of the catalyst has also been studied under the optimum conditions.     

Synthesis and characterization of TiO2 powders by the double-nozzle electrospray pyrolysis method. Part 1. Refinement and monodispersion of sprayed droplets

By using the droplet-fixation method, quantitative analyses of the size and dispersion state of electrosprayed droplets were conducted. At first, titanium(IV) bis (ammonium lactate) dihydroxide (TALH) aqueous solution (2 wt%), as a precursor of TiO₂, was electrosprayed using single-nozzle setting, and the electrospray parameters were optimized. Fine and monodispersed droplets (5.00 μm with the geometrical standard deviation of 1.16) were successfully obtained. Then, applying the single-nozzle conditions, we tried to prepare the double-nozzle electrospray, where positively and negatively charged sprays were superimposed to neutralize the charges of droplets. As for the double-nozzle electrospray, relatively fine and monodispersed droplets (7.58 μm with the geometrical standard deviation of 1.37) were obtained. By using the double-nozzle electrospray, the final TiO₂ powder yield after pyrolysis can be much improved.     

The effect of storage duration on bio-oil properties

Bio-oil produced by fluidized fast pyrolysis of yellow poplar wood (Liriodendron tulipifera) was stored in sealed glass bottles at 23 °C for 2, 4, 6, 8, or 10 weeks to investigate the effect of storage time on bio-oil properties. Bio-oil viscosity increased with increasing storage duration, while pH, water content and heating value remained unchanged. Thirty-three components were identified in the bio-oils and were classified into five sub-groups: aldehydes and ketones from carbohydrates, aliphatic phenols, phenolic aldehydes, and phenolic ketones from lignin. The concentrations of the sub-groups, especially the carbohydrate-derived ketones and lignin-derived compounds, gradually decreased with prolonged storage. In contrast, the yield of pyrolytic lignin extracted from bio-oils increased with storage duration from 13.2 wt% (fresh bio-oil; control) to 24.3 wt% (10 weeks). The average molecular weight of pyrolytic lignin also increased from 872 (control) to 1161 g mol⁻¹ (10 weeks). The amounts of phenolic hydroxyl and methoxyl groups decreased from 11.2 wt% (control) to 8.0 wt% (10 weeks) and 11.9 wt% (control) to 8.6 wt% (10 weeks), respectively. The observations strongly indicate that the low molecular weight components could participate in the re-polymerization with pyrolytic lignin, and the plausible polymerization reactions could be predicted to esterification, oxidation, hemiacetal/acetal formation and olefinic condensation.     

Catalytic effects of copper(II) chloride and aluminum chloride on the pyrolytic behavior of cellulose

The cellulose without and with catalyst (CuCl₂, AlCl₃) was subjected to pyrolysis at temperatures from 350 to 500 °C with different heating rate (10 °C/min, 100 °C/s) to produce bio-oil and selected chemicals with high yield. The pyrolytic oil yield was in the range of 37–84 wt% depending on the temperature, the heating rate and the amount of metal chloride. The non-catalytic fast pyrolysis at 500 °C gives the highest yield of bio-oil. The mixing cellulose with both metal chlorides results with a significant decrease of the liquid product. The non-catalytic pyrolysis of cellulose gives the highest mass yield of levoglucosan (up to 11.69 wt%). The great influence of metal chloride amount on the distribution of bio-oil components was observed. The copper(II) chloride and aluminum chloride addition to cellulose clearly promotes the formation of levoglucosenone (up to 3.61 wt%), 1,4:3,6-dianhydro-α-d-glucopyranose (up to 3.37 wt%) and unidentified dianhydrosugar (MW = 144; up to 1.64 wt%). Additionally, several other compounds have been identified but in minor quantities. Based on the results of the GC–MS, the effect of pyrolysis process conditions on the productivity of selected chemicals was discussed. These results allowed to create a general model of reactions during the catalytic pyrolysis of cellulose in the presence of copper(II) chloride and aluminum chloride.     

Assessment of soil quality of arable soils in Hungary using DRIFT spectroscopy and chemometrics

Nowadays, there is a great demand for precise, sensitive and adequate indicators for evaluating the quality of soils. In spite of recent developments in this field, a fast, non-destructive method for soil quality assessment has not yet been evaluated. The objective of this study was to investigate the possibility of using diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy to estimate soil quality in the form of soil quality index (SQI). A set of soil samples (n = 89) was scanned and regression was carried out using a combination of DRIFT spectroscopy and partial least-squares (PLS). The reliability of the DRIFT-PLS calibration model (n = 53) was acceptable (coefficient of determination, R² = 0.49; residual prediction deviation, RPD = 1.4) for the estimating of the SQI values. The validation of the calibration model using a validation set (n = 36) of unknown samples also resulted in good acceptability with R² = 0.68 and RPD = 1.85. The DRIFT-PLS based model could provide a rapid, cheap estimate of SQI values and subsequently of soil quality by taking into account the integrated effects of the mineralogical and organic components of the soil. This approach could be useful to monitor soil quality under conditions where the analysis of a large number of soil samples is required.     

Determination of the iodine value and the free fatty acid content of waste animal fat blends using FT-NIR

This study determined iodine value (IV) and free fatty acids (FFA) content of four different animal fat wastes and their blends using Fourier transform near-infrared spectroscopy (FT-NIR). Chemometric analysis by partial least squares (PLS) regression was used to correlate spectral data with IV and FFA reference values of the samples. The effects of four spectra pre-processing (first derivative (FD), second derivative (SD), multiplicative scatter correction (MSC) and vector normalization (VN)) methods were investigated to predict the reproducibility and robustness of the PLS-NIR model developed. A set of 70% of animal fat wastes and their blends were used for developing PLS calibration models for measuring IV and FFA content using the remaining 30% samples as an independent test set validation. The coefficient of determination (R²), the root mean square error estimation (RMSEE), and the residual prediction deviation (RPD) were used as indicators for the predictability of the PLS models. PLS-NIR models developed using first derivative and second derivative spectral preprocessing methods were the best for both IV and FFA content analysis (For IV, FD; R² = 0.9870, RMSEE = 1.40 gI₂/100 g, RPD = 8.76, SD; R² = 0.9892, RMSEE = 1.28 gI₂/100 g, RPD = 9.64 while For FFA, FD; R² = 0.9991, RMSEE = 0.195%, RPD = 34.00, SD; R² = 0.9993, RMSEE = 0.182%, RPD = 36.8). Overall, the results of this study demonstrate the suitability of FT-NIR spectroscopy for the quality control analysis of feedstocks for biodiesel production.     

Preparation and properties of new flame retardant unsaturated polyester nanocomposites based on layered double hydroxides

The preparation of new layered double hydroxides/unsaturated polyester (LDH/UP) nanocomposites was performed and the effect of LDH on the resin properties was studied. Two different organo-LDHs have been prepared, adipate-LDH (A-LDH) and 2-methyl-2-propene-1-sulfonate-LDH (S-LDH); in order to evaluate the influence of these nanofillers, samples with two different concentrations were dispersed in the matrix. The physical, thermal, mechanical and fire reaction properties of nanocomposites were studied. Intercalated layered structures were observed for the different organo-LDH loadings (1 and 5 wt%). Mechanical properties studied under flexural tests show that incorporation of organo-LDH in the resin reduces the flexural strength of polyester resin while the flexural modulus is unchanged for the S-LDH/UP composites and increased with 1 wt% of A-LDH. Adding 1 wt% of A-LDH to the resin produces an important reduction on the flexural strength, but an increase of the flexural modulus. The study of fire reaction properties, using cone calorimeter, suggested a significant reduction in the UP flammability, by 46 and 32%, by incorporating 1 wt% of A-LDH and 5 wt% S-LDH, respectively. Mass loss curves show enhanced char formation with the different loads tested while the amount of evolved smoke remains quite unchanged.     

Determination of total sulfur in diesel fuel employing NIR spectroscopy and multivariate calibration

A method for sulfur determination in diesel fuel employing near infrared spectroscopy, variable selection and multivariate calibration is described. The performances of principal component regression (PCR) and partial least square (PLS) chemometric methods were compared with those shown by multiple linear regression (MLR), performed after variable selection based on the genetic algorithm (GA) or the successive projection algorithm (SPA). Ninety seven diesel samples were divided into three sets (41 for calibration, 30 for internal validation and 26 for external validation), each of them covering the full range of sulfur concentrations (from 0.07 to 0.33% w/w). Transflectance measurements were performed from 850 to 1800 nm. Although principal component analysis identified the presence of three groups, PLS, PCR and MLR provided models whose predicting capabilities were independent of the diesel type. Calibration with PLS and PCR employing all the 454 wavelengths provided root mean square errors of prediction (RMSEP) of 0.036% and 0.043% for the validation set, respectively. The use of GA and SPA for variable selection provided calibration models based on 19 and 9 wavelengths, with a RMSEP of 0.031% (PLS-GA), 0.022% (MLR-SPA) and 0.034% (MLR-GA). As the ASTM 4294 method allows a reproducibility of 0.05%, it can be concluded that a method based on NIR spectroscopy and multivariate calibration can be employed for the determination of sulfur in diesel fuels. Furthermore, the selection of variables can provide more robust calibration models and SPA provided more parsimonious models than GA.     

Partial least squares modeling of combined infrared, 1H NMR and 13C NMR spectra to predict long residue properties of crude oils

Research has been carried out to determine the potential of partial least squares (PLS) modeling of mid-infrared (IR) spectra of crude oils combined with the corresponding ¹H and ¹³C nuclear magnetic resonance (NMR) data, to predict the long residue (LR) properties of these substances. The study elaborates further on a recently developed and patented method to predict this type of information from only IR spectra. In the present study, PLS modeling was carried out for 7 different LR properties, i.e., yield long-on-crude (YLC), density (D_LR), viscosity (V_LR), sulfur content (S), pour point (PP), asphaltenes (Asph) and carbon residue (CR). Research was based on the spectra of 48 crude oil samples of which 28 were used to build the PLS models and the remaining 20 for validation. For each property, PLS modeling was carried out on single type IR, ¹³C NMR and ¹H NMR spectra and on 3 sets of merged spectra, i.e., IR + ¹H NMR, IR + ¹³C NMR and IR + ¹H NMR + ¹³C NMR. The merged spectra were created by considering the NMR data as a scaled extension of the IR spectral region. In addition, PLS modeling of coupled spectra was performed after a Principal Component Analysis (PCA) of the IR, ¹³C NMR and ¹H NMR calibration sets. For these models, the 10 most relevant PCA scores of each set were concatenated and scaled prior to PLS modeling. The validation results of the individual IR models, expressed as root-mean-square-error-of-prediction (RMSEP) values, turned out to be slightly better than those obtained for the models using single input ¹³C NMR or ¹H NMR data. For the models based on IR spectra combined with NMR data, a significant improvement of the RMSEP values was not observed neither for the models based on merged spectra nor for those based on the PCA scores. It implies, that the commonly accepted complementary character of NMR and IR is, at least for the crude oil and bitumen samples under study, not reflected in the results of PLS modeling. Regarding these results, the absence of sample preparation and the straightforward way of data acquisition, IR spectroscopy is preferred over NMR for the prediction of LR properties of crude oils at site.