Identification and classification of polymer e-waste using laser-induced breakdown spectroscopy (LIBS) and chemometric tools

In the recycling of polymer e-waste, there is a pressing need for rapid measurement technologies for the simple identification and classification of these materials. The goal of this work was to instantly identify e-waste polymers by laser-induced breakdown spectrometry (LIBS). The studied polymers were acrylonitrile-butadiene-styrene (ABS), polystyrene (PS), polyethylene (PE), polycarbonate (PC), polypropylene (PP), and polyamide (PA). Emission lines were selected for C (247), H (656), N (742 + 744 + 747), and O (777), as well as the molecular band of C2 (516), and the ratios of the emission lines and molecular band were utilized. Classification models, k-nearest neighbors (KNN) and soft independent modeling of class analogy (SIMCA), were used to rank the polymers. Both constructed models gave satisfactory results for the validation samples, with average accuracies of 98% for KNN and 92% for SIMCA. These results prove the predictive analytical capabilities of the LIBS technique for plastic identification and classification.     

Association and discrimination of diesel fuels using chemometric procedures

Five neat diesel samples were analyzed by gas chromatography-mass spectrometry and total ion chromatograms as well as extracted ion profiles of the alkane and aromatic compound classes were generated. A retention time alignment algorithm was employed to align chromatograms prior to peak area normalization. Pearson product moment correlation coefficients and principal components analysis were then employed to investigate association and discrimination among the diesel samples. The same procedures were also used to investigate the association of a diesel residue to its neat counterpart. Current limitations in the retention time alignment algorithm and the subsequent effect on the association and discrimination of the diesel samples are discussed. An understanding of these issues is crucial to ensure the accuracy of data interpretation based on such chemometric procedures. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Quality assessment of Fructus Ligustri Lucidi by the simultaneous determination of six compounds and chemometric analysis

A comprehensive strategy was designed for the quality assessment of Fructus Ligustri Lucidi, a well‐known and commonly used herbal medicine in clinical practice in China. First, a simple and stable method of high‐performance liquid chromatography was developed for the simultaneous quantitative analysis of six compounds, namely, salidroside, nuzhenide, specnuezhenide, oleanic acid, ursolic acid, and acetyl oleanic acid in Fructus Ligustri Lucidi. The separation of analytes was conducted on a C₁₈ column (200 mm × 4.6 mm, 5 μm) at 30°C, and the wavelength of UV detector was set at 210 nm. In quantitative analysis, all of the calibration curves showed good linear regression (R² > 0.9994) within the tested ranges, and the mean recoveries of three different concentrations ranged from 95.21–102.34%. The described method was applied to determine 11 batches of samples collected from different stores in China. Then multiple chemometrics analysis including hierarchical cluster analysis and principal component analysis were performed to classify samples and search significant compounds. Three notable compounds, specnuezhenide, oleanic acid, and acetyl oleanic acid, were discovered for better quality control compared with those stated in the China pharmacopeia. The results demonstrated that this strategy could be readily utilized for the comprehensive quality control of Fructus Ligustri Lucidi.     

Ecotoxicity and chemical sediment data classification by the use of self-organising maps

The present paper deals with the presentation in a new interpretation of sediment quality assessment. This original approach studies the relationship between ecotoxicity parameters (acute and chronic toxicity) and chemical components (polluting species like polychlorinated biphenyls (PCBs), pesticides, polycyclic aromatic hydrocarbons (PAH), heavy metals) of lake sediments samples from Turawa Lake, Poland by an application of self-organising maps (SOMs) to the monitoring dataset (59 samples × 44 parameters) in order to obtain visual images of the components distributed at each sampling site when all components are included in the classification and data projection procedure. From the SOMs obtained, it is possible to select groups of similar ecotoxicity (either acute or chronic) and to analyse within each one of them the relationship of the other chemicals to the toxicity determining parameters (EC₅₀ and mortality). Studies have shown, convincingly, that different regions from the Turawa Lake bottom indicate different patterns of ecotoxicity related to various chemical pollutants, such as the “heptachlor-B” pattern, “pesticide and PAH” pattern, “structural” pattern or “PCB congeners” pattern. Thus, an easy way of multivariate analysis of small datasets with ecotoxicity parameters involved becomes possible. Additionally, a distinction between the effects of pollution on acute and chronic toxicity seems reasonable.     

Sequential (step-by-step) detection,identification and quantitation of extra virgin olive oil adulteration by chemometric treatment of chromatographic profiles

An analytical method for the sequential detection, identification and quantitation of extra virgin olive oil adulteration with four edible vegetable oils--sunflower, corn, peanut and coconut oils--is proposed. The only data required for this method are the results obtained from an analysis of the lipid fraction by gas chromatography-mass spectrometry. A total number of 566 samples (pure oils and samples of adulterated olive oil) were used to develop the chemometric models, which were designed to accomplish, step-by-step, the three aims of the method: to detect whether an olive oil sample is adulterated, to identify the type of adulterant used in the fraud, and to determine how much aldulterant is in the sample. Qualitative analysis was carried out via two chemometric approaches--soft independent modelling of class analogy (SIMCA) and K nearest neighbours (KNN)--both approaches exhibited prediction abilities that were always higher than 91% for adulterant detection and 88% for type of adulterant identification. Quantitative analysis was based on partial least squares regression (PLSR), which yielded R2 values of >0.90 for calibration and validation sets and thus made it possible to determine adulteration with excellent precision according to the Shenk criteria.     

A novel approach for honey pollen profile assessment using an electronic tongue and chemometric tools

Nowadays the main honey producing countries require accurate labeling of honey before commercialization, including floral classification. Traditionally, this classification is made by melissopalynology analysis, an accurate but time-consuming task requiring laborious sample pre-treatment and high-skilled technicians. In this work the potential use of a potentiometric electronic tongue for pollinic assessment is evaluated, using monofloral and polyfloral honeys. The results showed that after splitting honeys according to color (white, amber and dark), the novel methodology enabled quantifying the relative percentage of the main pollens (Castanea sp., Echium sp., Erica sp., Eucaliptus sp., Lavandula sp., Prunus sp., Rubus sp. and Trifolium sp.). Multiple linear regression models were established for each type of pollen, based on the best sensors' sub-sets selected using the simulated annealing algorithm. To minimize the overfitting risk, a repeated K-fold cross-validation procedure was implemented, ensuring that at least 10–20% of the honeys were used for internal validation. With this approach, a minimum average determination coefficient of 0.91 ± 0.15 was obtained. Also, the proposed technique enabled the correct classification of 92% and 100% of monofloral and polyfloral honeys, respectively. The quite satisfactory performance of the novel procedure for quantifying the relative pollen frequency may envisage its applicability for honey labeling and geographical origin identification. Nevertheless, this approach is not a full alternative to the traditional melissopalynologic analysis; it may be seen as a practical complementary tool for preliminary honey floral classification, leaving only problematic cases for pollinic evaluation.     

Improving the efficiency of ion mobility spectrometry analyses by using multivariate calibration

The simplicity, sensitivity and expeditiousness of ion mobility spectrometry (IMS) make it especially useful for the determination of active principal ingredients (APIs) present at low concentrations in pharmaceuticals. However, the poor resolution of this technique precludes the identification and/or determination of substances with similar molecular weights, which exhibit also similar drift times and give overlapped peaks as a result. Oral contraceptives are pharmaceutical formulations containing two APIs of similar molecular weights at very low concentrations which therefore give strongly overlapped peaks hindering their determination by IMS. In this work, we assessed the potential of IMS for detecting and quantifying the contraceptives ethinylestradiol (ETE) and desogestrel (DES) in commercial tablets. To this end, we used various chemometric techniques including a second-derivative (TN2D) algorithm and the more powerful choice Multivariate Curve Resolution (MCR) to improve the resolution of IMS and enable the determination of both APIs. Quantitation was based on PLS1 models for each API. The models constructed involve a single PLS factor with a Y-explained variance above 98.4%, obtaining a RMSEP of 0.34 and 0.63 for ETE and DES, respectively. The ensuing method, which was validated for use in routine analyses, is quite expeditious (analyses take less than 1 min) and uses very small amounts of sample (a few microliters). Based on the results, IMS has a great potential for the qualitative and quantitative determination of APIs in low doses.     

Thermodynamic characterization of the dimerization equilibrium of an asymmetric dye by spectral titration and chemometric analysis

The monomer-dimer equilibrium of an asymmetric cyanine dye has been investigated by means of UV-Vis spectroscopy. The data have been processed by a recently developed chemometric method for quantitative analysis of undefined mixtures, that is based on simultaneous resolution of the overlapping bands in the whole set of absorption. In this work the dimerization constant of 1-carboxydecyl-4-{3-[3-methyl-3H-benzothiazol-2-ylidene]-propenyl}-quinolinium (TO-3) has been determined by studying the dependence of absorption spectrum on temperature in the range 25-72.5 °C at different total concentrations of dye (8.5×10⁻⁶ to 2.87×10⁻⁵ M). Utilizing the van’t Hoff relation, which describes the dependence of the equilibrium constant on temperature, as constraint we determine the spectral responses of the monomer and dimer species as well as the enthalpy and entropy of the dimerization equilibrium.     

Quantitative analysis of 17 amino acids in tobacco leaves using an amino acid analyzer and chemometric resolution

A method was developed for quantifying 17 amino acids in tobacco leaves by using an A300 amino acid analyzer and chemometric resolution. In the method, amino acids were eluted by the buffer solution on an ion‐exchange column. After reacting with ninhydrin, the derivatives of amino acids were detected by ultraviolet detection. Most amino acids are separated by the elution program. However, five peaks of the derivatives are still overlapping. A non‐negative immune algorithm was employed to extract the profiles of the derivatives from the overlapping signals, and then peak areas were adopted for quantitative analysis of the amino acids. The method was validated by the determination of amino acids in tobacco leaves. The relative standard deviations (n = 5) are all less than 2.54% and the recoveries of the spiked samples are in a range of 94.62–108.21%. The feasibility of the method was proved by analyzing the 17 amino acids in 30 tobacco leaf samples.     

Development of a comprehensive method for analyzing clerodane‐type diterpenes and phenolic compounds from Casearia sylvestris Swartz (Salicaceae) based on ultra high performance liquid chromatography combined with chemometric tools

This work describes the development and optimization of an analytical method utilizing liquid chromatography and chemometrics to evaluate and differentiate two varieties of Casearia sylvestris Swartz (Salicaceae) from São Paulo State (Brazil) based on their secondary metabolite profiles. Previously, analytical studies only concerned the analysis of clerodane‐type diterpenes. Therefore, considering the importance of including phenolic compounds in such analysis, we used design of experiments to simultaneously extract and detect the largest number of compounds from both chemical classes. This new strategy allowed a comprehensive chromatographic analysis of C. sylvestris, and the results for the two varieties exhibited an interesting distribution according to their original ecosystems, suggesting a strong correlation to the main metabolites found in each species group. Besides their inherent morphological differences, C. sylvestris variety lingua, mainly found in Cerrado areas, predominantly contains phenolic compounds, while C. sylvestris variety sylvestris, mainly found in Atlantic Forest areas, contains mostly clerodane‐type diterpenes. Finally, it was also possible to observe differences in the secondary metabolite composition within each group depending on the place where samples were collected.     

Comparative analysis of the volatile components in cut tobacco from different locations with gas chromatography-mass spectrometry (GC-MS) and combined chemometric methods

A combined approach of subwindow factor analysis and orthogonal projection resolution was used to analyze the volatile components of cut tobacco samples from different sources. After extracted with simultaneous distillation and extraction method, the volatile components in cut tobacco from five different locations were detected by GC-MS. Then, the qualitative and quantitative analysis of the volatile components of cut tobacco from Changde area was completed with the help of subwindow factor analysis resolving two-dimensional original data into pure mass spectra and chromatograms. One hundred and two volatile components among 138 separated peaks were identified and quantified, accounting for about 88.90% of the total content. Finally, orthogonal projection method was used to extract the common peaks from different locations. Among the identified components, there were 74 components coexisting in five studied samples although the relative content of each component showed difference to some extent. The results showed a fair consistency in their GC-MS fingerprints. It was the first time to apply orthogonal projection method to compare different cut tobacco samples, and it reduced the burden of qualitative analysis as well as the subjectivity. The obtained results proved the combined approach powerful for the analysis of complex cut tobacco samples. The developed method can be used to compare the sameness and differences of cut tobacco from different sources and for quality control of cigarette production and materials.     

Resolution and identification of the acidic fraction of a petroleum ether extract ofRadix Rehmanniae Preparata by an evolving chemometric approach

Summary An evolving approach is described for analyzing the acidic components of a petroleum ether extract of Radix Rehmanniae Preparata. The latter was extracted, separated and derivatized. The subsequent separation of the individual components was characterized by GC-MS. The two-way data were resolved into a pure chromatogram and a mass spectrum of each chemical component. The reliability and accuracy of the qualitative results were greatly improved and the degree of the chromatographic separation could be enhanced to a certain extent. This enabled the analysis of complicated practical systems by hyphenated instruments and these advanced methods.     

Evaluation of chemometric techniques for the identification and quantification of solvent mixtures using a thin-film metal oxide sensor array

An evaluation was made of suitable chemometric techniques that can be used in both the selection of suitable sensors for a sensor array and the subsequent identification and quantification of analytes using such a device. Data fro a thin-film tin oxide-based gas sensor were obtained for a range of analytes, both pure and in mixtures and analysed using several chemometric techniques, including principal component analysis, cluster analysis and partial least squares. It was shown that the array produced a characteristic response pattern for the analytes, and this was then used for the identification of ethyl acetate, acetone, ethanol and pentane, and the determination of ethanol in various mixtures. The chemometric techniques were not only used to identify and quantify components in the solvent mixture but also indicated which of the array elements were acting independently and the level of interaction which was occurring. The results obtained describe a chemometric and fabrication protocol for sensor array design.     

Synergistic effect of the simultaneous chemometric analysis of H NMR spectroscopic and stable isotope (SNIF-NMR,O, C) data: Application to wine analysis

It is known that ¹H NMR spectroscopy represents a good tool for predicting the grape variety, the geographical origin, and the year of vintage of wine. In the present study we have shown that classification models can be improved when ¹H NMR profiles are fused with stable isotope (SNIF-NMR, ¹⁸O, ¹³C) data. Variable selection based on clustering of latent variables was performed on ¹H NMR data. Afterwards, the combined data of 718 wine samples from Germany were analyzed using linear discriminant analysis (LDA), partial least squares-discriminant analysis (PLS-DA), factorial discriminant analysis (FDA) and independent components analysis (ICA). Moreover, several specialized multiblock methods (common components and specific weights analysis (ComDim), consensus PCA and consensus PLS-DA) were applied to the data.     

Classification of commercial wines from the Canary Islands (Spain) by chemometric techniques using metallic contents

Eleven elements, K, Na, Ca, Mg, Fe, Cu, Zn, Mn, Sr, Li and Rb, were determined in dry and sweet wines bearing the denominations of origin of El Hierro, La Palma and Lanzarote islands (Canary Islands, Spain). Analyses were performed by flame atomic absorption spectrophotometry, with the exceptions of lithium and rubidium for which flame atomic emission spectrophotometry was used. Sweet wines from La Palma were elaborated as naturally sweet with over-ripe grapes and significant differences were found in all the analysed elements with the exceptions of sodium, iron and rubidium with regard to dry wines from the same island. Contrarily, sweet wines from Lanzarote elaborated with grapes in a similar ripening state to dry wines did not present significant differences between them with the exception of strontium, the content of which was greater in dry wines. Among the three islands, significant differences in mean content were found with the exceptions of iron and copper. Cluster analysis and principal component analysis show differences in wines according to the island of origin and the ripening state of the grapes. Linear discriminant analysis using rubidium, sodium, manganese and strontium, the four most discriminant elements, gave 100% recognition ability and 95.6% prediction ability. The sensitivity and specificity obtained using soft independent modelling of class analogy (SIMCA) as a modelling multivariate technique were both 100% for El Hierro and Lanzarote, and 100 and 95%, respectively, for La Palma. The modelling and discriminant capacities of the different metals were also studied.     

Quantitative analysis of Cistanches Herba using high‐performance liquid chromatography coupled with diode array detection and high‐resolution mass spectrometry combined with chemometric methods

We aim to determine the chemical constituents of three species of Cistanches Herba using HPLC coupled with diode array detection and high‐resolution MS. Ten phenylethanoid glycosides were identified and further quantified as marker substances by HPLC coupled with diode array detection method. The separation was conducted using an Agilent TC‐C18 column with 0.1% formic acid and methanol as the mobile phases under gradient elution. The analytical method was fully validated in terms of linearity, sensitivity, precision, repeatability as well as recovery, and subsequently applied to evaluate the quality of 36 batches of Cistanche plants. The chemometric procedures (i.e., hierarchical clustering analysis and principal component analysis) were used to compare different species of Cistanches Herba, leading to successful classification of the Cistanche samples in accordance with their origins. In conclusion, this study provides a chemical basis for quality control of Cistanches Herba.     

Discrimination of crude and processed rhubarb products using a chemometric approach based on ultra fast liquid chromatography with ion trap/time‐of‐flight mass spectrometry

Crude rhubarb subjected to different processing procedures will produce different therapeutic effects that are possibly due to processing‐induced variation in chemical composition. In this study, a chemometric approach based on ultra fast liquid chromatography with ion trap/time‐of‐flight mass spectrometry was established to systematically investigate the chemical variations of rhubarb induced by different processing methods. The approach was validated based on pooled quality‐control samples from two perspectives: the individual properties of variables and the bulk properties of samples. Orthogonal partial least squares discriminant analysis was introduced to compare the differences between crude and processed rhubarb products. A total of 20 significantly different markers were screened out and unambiguously/tentatively characterized. This research proved that a chemometric method based on ultra fast liquid chromatography with ion trap/time‐of‐flight mass spectrometry can comprehensively analyze the chemical variation of herbal medicine and provide evidence for a deeper understanding of the pharmacological activities of processed rhubarb products.     

Comprehensive description of the photodegradation of bromophenols using chromatographic monitoring and chemometric tools

A general procedure for the study of complex photodegradation processes of environmental pollutants based on chromatographic monitoring and chemometric method is proposed. The procedure consists of multiset data analysis of aliquots collected at different reaction times and injected in High-Performance Liquid Chromatography coupled to diode array detection and mass spectrometry (HPLC-DAD-MS). In this study, photodegradation of six bromophenols with different degrees of bromination has been investigated in order to find out their photodegradation pathways and kinetics and to show the potential of the procedure proposed. Multivariate curve resolution-alternating least squares (MCR-ALS) has been used to resolve chromatographic elution profiles and pure spectra of species involved in the photodegradation process and, hence, to elucidate the photodegradation mechanism and to propose the chemical structure of the main photoproducts. This study shows that chromatographic monitoring is the preferred option when photochemical systems with large number of components with similar spectra and kinetic evolution are analyzed. This work reveals the advantages of the double DAD and MS detection to provide mechanistic and structural information about these complex photodegradation processes.