Electronic tongues in flow analysis

This review presents the evolution of recent flow-based analytical systems, characterized by the use of arrays of sensors as a detection scheme. For the proper processing of the complex responses generated, the systems require the use of advanced chemometric treatment, in which received the term “electronic tongue”. Applications employing the flow injection analysis (FIA) and sequential injection analysis (SIA) are described. Chronologically, the progresses made by different research groups are shown, emphasizing their final applications in real problem solving.     

The Process Analytical Technology initiative and multivariate process analysis, monitoring and control

Process analytical technology is an essential step forward in pharmaceutical industry. Real-time analyzers will provide timely data on quality properties. This information combined with process data (temperatures, flow rates, pressure readings) collected in real time can become a powerful tool for this industry, for process understanding, process and quality monitoring, abnormal situation detection and for improving product quality and process reliability. A very important tool for this achievement is the multivariate analysis. Dr. Theodora Kourti is Research Manager in the McMaster Advanced Control Consortium (MACC) and Adjunct Professor in the Chemical Engineering Department at McMaster University. She is the co-recipient of the 2003 University – Industry Synergy Award for Innovation, given by the Natural Science & Engineering Research Council of Canada. Dr. Kourti has been working on Multivariate Statistical Methods for Process and Product Improvement and Abnormal Situation Detection in Process Industries since 1992 and has been involved in more than 80 major industrial applications in North America and Europe. These are either off-line or real-time applications for batch and continuous processes, in diverse industries such as Chemicals, Pharmaceuticals, Semiconductor, Mining, Pulp and Paper, Petrochemicals, Photographic and Steel Industry. She has published extensively in this area and has provided training for numerous industrial practitioners.     

NMR spectroscopy evaluation of direct relationship between soils and molecular composition of red wines from Aglianico grapes

¹H NMR spectroscopy was employed to investigate the molecular quality of Aglianico red wines from the Campania region of Italy. The wines were obtained from three different Aglianico vineyards characterized by different microclimatic and pedological properties. In order to reach an objective evaluation of “terroir” influence on wine quality, grapes were subjected to the same winemaking procedures. The careful subtraction of water and ethanol signals from NMR spectra allowed to statistically recognize the metabolites to be employed in multivariate statistical methods: Principal Component Analysis (PCA), Discriminant Analysis (DA) and Hierarchical Clustering Analysis (HCA). The three wines were differentiated from each other by six metabolites: α-hydroxyisobutyrate, lactic acid, succinic acid, glycerol, α-fructose and β-d-glucuronic acid. All multivariate analyses confirmed that the differentiation among the wines were related to micro-climate, and carbonate, clay, and organic matter content of soils. Additionally, the wine discrimination ability of NMR spectroscopy combined with chemometric methods, was proved when commercial Aglianico wines, deriving from different soils, were shown to be statistically different from the studied wines. Our findings indicate that multivariate statistical elaboration of NMR spectra of wines is a fast and accurate method to evaluate the molecular quality of wines, underlining the objective relation with terroir.     

Simultaneous determination of penicillin and ampicillin by spectral fibre-optical enzyme optodes and multivariate data analysis based on transient signals obtained by flow injection analysis

A multicomponent detection system using optical biosensors and flow injection analysis is described. The analysis of mixtures containing penicillin and ampicillin was realised by evaluating dynamic measurements of Phenol Red spectra in penicillinase optodes in combination with a diode array spectrometer. A variety of optodes has been produced by changing the composition of the receptor gel and the working pH. A set of characteristic quantities (describing dynamic and static features) could be obtained for each optode. These were used to compare the predictivity of classical multivariate calibration methods as well as of an artificial neural network. In addition, different algorithms were applied for the evaluation of the spectral data in order to select the most appropriate method for feature extraction. In consequence, the information obtained from the multivariate calibration models was used to set up an optimal sensor array consisting of four optodes with different types of penicillinase at different working pH.     

Study of the influence of NaOH treatment on the pyrolysis of different leather tanned using thermogravimetric analysis and Py/GC-MS system

This paper presents a study of the influence of a NaOH treatment on leather samples tanned using different tanning agents. Thermogravimetric analysis (TG/DTG) and flash pyrolysis (Py/GC-MS) was carried out on treated samples, and the results were compared with those obtained with the untreated samples. Treatment with sodium hydroxide seemed to decrease the temperature of maximum leather decomposition rate between 4 and 27 °C, depending on the tanning agent, and increased the range of temperatures where leather degradation occurs. From flash pyrolysis experiments, it was found that the volatile products obtained from NaOH-treated samples contain higher amounts of nitrogen compounds than those obtained from untreated samples. The results of a multivariate analysis applied to pyrolytic products obtained in the flash pyrolysis of samples showed greater similarity between the results obtained in all treated samples than between treated and untreated samples produced with the same tanning process.     

Multivariate statistical analysis approach to assess groundwater quality in two selected mandals of Vizianagaram district,Andhra Pradesh,India

Groundwater quality is the major concern all over the world. Natural processes and manmade activities are the prime reasons for the contamination of available water resources. It is crucial to assess the quality of groundwater in areas surrounded by various industries. The present study was carried out to assess the groundwater quality during pre-monsoon and post monsoon seasons of 2016, in two mandals of Vizianagaram district of Andhra Pradesh via multivariate statistical analysis and water quality index method. The present work gains importance in light of the construction of proposed international airport at Bhohapuram and the existence of various industries in Pusapatirega mandal. A total of thirty-seven villages, eighteen from Bhogapuram mandal and seventeen from Pusapatirega mandal were selected for the present study. Factor analysis, linear regression analysis, correlation matrix analysis and cluster analysis tools were used to emphasize the parameters influencing quality of water in the chosen study area. From the analysis reports, it was found that the groundwater of the two mandals under investigation was strongly influenced by EC, TDS, total hardness(TH), Ca⁺², Mg⁺² and K⁺. During the two seasons under study, the water quality index value was found to be greater than 100 indicating that the water is unfit for human consumption. Concentration of Ca⁺², Mg⁺² and K⁺ were found to be beyond the permissible limits prescribed by BIS (2012). Dissolution of calcium and magnesium bearing minerals, mixing of industrial and household wastes may be the reasons for elevated concentration levels of these parameters.     

Characterization of the geographical origin of Italian red wines based on traditional and nuclear magnetic resonance spectrometric determinations

Chemical characterization of Italian red wines from different geographical locations in the Apulia, region of southern Italy, have been performed by means of chromatographic, analyses routine analyses (density, alcohol content, acidity, dry extract and ash content), inductively coupled plasma-atomic emission spectrometric measurements and nuclear magnetic resonance (¹H NMR) spectrometric determinations. Multivariate statistical methods were applied separately to the analytical and NMR data. The results showed that Apulian red wines are divided in three groups according to their geographical origin.     

大鼠体内复方清开灵代谢物的分析

建立了复方中药清开灵代谢物的液相色谱-质谱/质谱分析方法。采用Phenomenex Luna C18色谱柱,以0.1%甲酸(A)及V(甲醇)∶和V(乙腈)=4∶1混合液(B)作流动相,采用梯度洗脱(0 min,B为0%;33min,B为60%;66 min,B为88%;75 min,B为100%),流速:0.5 mL/min,离子阱质谱负离子模式进行检测。通过差谱方法对可能的代谢物进行快速搜索。对发现的重要的代谢物根据分子量以及多级质谱的碎片离子数据,结合体内代谢反应规律,进行指认和结构鉴定。共鉴定了3个主要的代谢物,其中一个为黄芩苷的代谢物,另两个为绿原酸的代谢物,后两个代谢物未见文献报道。本实验为研究复方中药复杂体系体内的代谢产物提供了一个有效而且快捷的模式。     

Sequential injection analysis with second-order treatment for the determination of dyes in the exhaustion process of tanning effluents

A sequential injection (SI)-DAD spectrophotometric method to control the exhaustion of dyes in a mixture of three dyes from a tanning industry process has been developed. It is based on an interdiffusion process of the sample and reagents which leads to a gradual fall in pH through the channel to the detector recording a data matrix. The aim of this paper is to develop a second-order calibration model that is unaffected by interferents by applying multivariate curve resolution with alternating least squares (MCR-ALS). We obtained a linear calibration in the 5-30 mg l⁻¹ range with a correlation coefficient of 0.999 for each dye with detection limits of 2.6, 3.9 and 2.1 mg l⁻¹ for Acid Red, Acid Brown and Acid Orange, respectively. The simultaneous determination of the three dyes from tanning samples showed a satisfactory precision for the three analytes. The method has been validated comparing the concentration of some spiked samples with the expected concentration using a t-paired test. When we used this method to study the exhaustion of dyes, we found that there were several stages in this process. These data may be the key to optimising the exhaustion process.     

Multi-syringe flow injection solid-phase extraction system for on-line simultaneous spectrophotometric determination of nitro-substituted phenol isomers

In this paper, a time-based multi-syringe flow injection (MSFI) approach is proposed for automated disk-based sorbent extraction of three nitro-substituted phenol isomers (2-, 3-, and 4-nitrophenol) followed by on-line simultaneous determination of individual species by diode-array spectrophotometry. The method involves the on-line enrichment of the targeted analytes from an acidic medium containing 0.1 mol L⁻¹ HCl onto a co-polymeric sorbent material, and the concurrent removal of potentially interfering matrix components. The nitrophenol isomers are subsequently eluted with an alkaline solution (0.7 mol L⁻¹ NaOH), whereupon the eluate is delivered to a diode-array spectrophotometer for recording of the spectral data in the UV-vis region. Deconvolution of strongly overlapped spectra was conducted with multivariate regression models based on multiple linear regression calibration. The analytical performance of the chemometric algorithm was characterized by relative prediction errors and recoveries.The MSFI manifold was coupled to a multiposition selection valve to set a rugged analyzer that ensures minimum operational maintenance via exploitation of membrane switching protocols. As compared with earlier methods for isolation/pre-concentration of nitro-substituted phenols based on liquid-liquid extraction, the proposed flow-through disk-based system should be regarded as an environmentally friendly approach because the use of harmful organic solvents is circumvented. Under the optimized chemical and physical variables, the 3σ_blank detection limits for 2-, 3-, and 4-nitrophenol were 1.2, 3.2 and 0.3 μmol L⁻¹ for a sample loading volume of 1.5 mL, and the relative standard deviations were ≤5.0%. The flowing system, which is able to handle up to 135 samples automatically, was proven suitable for monitoring trace levels of the target isomers in mineral, tap, and seawater.     

Increasing the scope and power of flow-injection analysis through chemometric approaches

The objective of this paper is to illustrate how chemometrics can enhance the scope and power of flow injection analysis (FIA) by considering a few simple but representative cases where the ability of chemometrics to improve performance is not readily apparent. In principle, there are two phases when chemometrics can be usefully combined with FIA: first when developing an FIA method and, second, when treating raw data acquired from an FIA detection system. The most obvious application of chemometrics for the FIA practitioner is to use experimental design to replace the obsolete, but too often used one-variable-at-a-time approach when optimising an FIA method. Therefore, methods for screening variables and system optimisation are discussed. Raw data acquired from most FIA systems are first-order data, containing information about the dispersed sample plug. However, the information that is extracted when using FIA for routine purposes is of zero-order: predominantly peak height values. It is shown by a simple example that a chemometric approach in such cases can again provide additional useful information about the sample. First-order spectral data and second-order data more or less require a chemometrics approach for successful analysis, and examples of such applications are briefly discussed.     

Simultaneous determination of fluorophores with overlapped spectra by sequential injection analysis coupled to variable angle scanning fluorescence spectrometry and multivariate linear regression algorithms

An automated and versatile sequential injection spectrofluorimetric procedure for the simultaneous determination of multicomponent mixtures in micellar medium without prior separation processes is reported. The methodology is based upon the segmentation of a sample slug between two different buffer zones in order to attain both an improvement of sensitivity and residual minimization for the whole species. Resolution of overlapping fluorescence profiles is achieved using a variable angle scanning technique coupled to multivariate least-squares regression (MLR) algorithms at both sample edges.The potentialities of the described methodology are illustrated with the spectrofluorimetric determination of four widespread pesticides with different acid-base properties; viz. carbaryl (CBL) (1-naphthyl-N-methylcarbamate), fuberidazole (FBZ) (2-(2′-furyl)benzimidazole), thiabendazole (TBZ) (2-(4′-thiazolyl)benzimidazole) and warfarin (W) (3-α-acetonylbenzyl)-4-hydroxycoumarin). Detection limits at the 3σ level were 3.9, 0.02, 0.03 and 10 μg l⁻¹ for CBL, FBZ, TBZ and W, respectively at the maximum sensitivity pH. Dynamic ranges of 13-720 μg l⁻¹ CBL, 0.10-14 μg l⁻¹ FBZ, 0.19-60 μg l⁻¹ TBZ and 0.05-5 mg l⁻¹ W were achieved. Relative standard deviations (n=10) were 0.2% for 100 μg l⁻¹ CBL and 2.4 μg l⁻¹ FBZ, 0.7% for 8 μg l⁻¹ TBZ and 1.0% for 1 mg l⁻¹ W. The proposed automated methodology, which handles 17 samples/h, was validated and applied to spiked real water samples with very satisfactory results.     

Integrated analysis of serum and liver metabonome in liver transplanted rats by gas chromatography coupled with mass spectrometry

In this paper, we present a metabonomic method for the investigation of abnormal metabolic process in both serum and liver tissue of liver transplanted rats. Syngeneic transplantation was performed on male Lewis rats. The serum and grafted liver on day 1, 3, and 7 post-transplant were collected to analyze endogenous metabolites using gas chromatography coupled with mass spectrometry (GC-MS). The method was validated with acceptable linearity, precision, and repeatability. Thirty-four metabolites in serum and 29 metabolites in liver were identified. Results of correlation analysis illustrated metabolites with similar function exhibited similar variations in liver and serum. The data processed by principle component analysis (PCA) showed time-dependent biochemical variations. As a consequence, the present study may offer specific putative pathways in the pathophysiological mechanism of orthotopic liver transplantation.     

最小二乘支持向量机算法与紫外光谱法用于鉴别清开灵注射液四混中间体

采用一阶导数数据预处理,最小二乘支持向量机(LS-SVM)紫外可见光谱建模,对清开灵注射液四混中间体进行质量评价。以二次网格法和十折交叉验证法优化建模参数,预测集的总正确率和接受器工作特性曲线(ROC)下面积分别可达98.0%和0.983。结果表明,与经典的支持向量机相比,LSSVM鉴别准确率更高,模型的泛化能力更强。可用于清开灵注射液生产过程中质量控制,为中药注射液生产过程的质量控制提供了一条有效的途径。