Trace chemometrics

The Analysis of Extraterrestrial Materials. By Isidore Adler Chemometrics. By Muhammad A. Sharaf, Deborah L. Illman, and Bruce R. Kowalski Fourier Transform Infrared Spectrometry. By Peter R. Griffiths and James A. de Haseth Trace Analysis Spectroscopic Methods for Molecules. Edited by Gary Christian and James B. Callis... 

A total of 185 emission lines for both major and trace elements were attributed from each LIBS broadband spectrum. Then background-corrected, summed, and normalized intensities were calculated for 18 selected emission lines and 153 emission line ratios were generated. Finally, the summed intensities and ratios were used as input variables to multivariate statistical chemometric models. A total of 3100 spectra were used to generate Partial Least Squares Discriminant Analysis (PLS-DA) models and test sets. 

Criminalistics and trace evidence are both terms that apply to all types of physical material that may be circumstantial evidence in the trial of a case. Most often experts who are identified as criminalists, microanalysts, or trace evidence examiners analyze a variety of types of trace evidence. They carry out three types of identification. First is to determine the nature of small items of trace evidence. After this forensic experts compare the trace evidence with known materials for the purpose of determining the origin of the evidence. The third type of criminahstics investigations is performed in order to identify an individual to whom the trace belongs. For this purpose population studies using statistics (especially the probabilistic approach of Bayesian theory) and chemometrics methods are utilized. 

However, society likes to have decisions made in a black and white manner and to know whether something is there or not. This situation suggests that the analytical error should drop to zero. While this result is the goal of all analytical work, it is simply not realistic. Our basic need, then, is to simplify error determinations and explanations and to educate the public both for the reasons and for the interpretations of error. The goal of this volume is to further the use of mathematical and statistical tools—the field of chemometrics—for chemical and, specifically, trace chemical analyses of pesticides and environmental contaminants. 

In this review, an in-depth overview is presented, tracing an outline of the chemometric techniques most widely applied in the relatively brief history of artificial tongues, highlighting benefits and drawbacks of each one. Furthermore, some chemometric methods recently introduced and particularly suitable for artificial tongue data processing are discussed. 

R. J. H. Waddell, N. NicDaeid and D. Littlejohn, Classification of ecstasy tablets using trace metal analysis with the application of chemometric procedures and artificial neural networks algorithms. Analyst, 129(3), 2004, 235-240. 

J.-P. Perez-Trujillo, M. Barbaste and B. Medina, Chemometric study of bottled wines with denomination of origin from the Canary Islands (Spain) based on ultra-trace elemental content determined by ICP-MS, Anal. Lett., 36(3), 2003, 679-697. 

SNIF-NMR and/or IRMS techniques were often combined with trace element analyses (ICP-MS, ICP-OES, FAAS, ETAAS, GFFA) and chemometrics for the geographical characterization of wines. In a relatively old paper, Day et ah (1995) analyzed 165 grape samples collected in 1990 in four different production areas of France (Alsace, Beaujolais, Burgundy, and the Loire Valley). The combined use of isotopic and trace element data allowed an excellent classification of wine samples corresponding to... 

Antecedents of the treated topic can be traced to the building of response models for arrays of ISEs, which considers the case of crossresponse terms. This has been historically addressed by the application of different chemometric tools. The first attempt was by Otto and Thomas [40] in the 1980s, who employed an eight-sensor array and... 

A third and often neglected reason for the need for care fill application of chemometric methods is the problem of the type of distribution of environmental data. Most basic and advanced statistical methods are based on the assumption of normally distributed data. But in the case of environmental data, this assumption is often not valid. Figs. 1-7 and 1-8 demonstrate two different types of experimentally found empirical data distribution. Particularly for trace amounts in the environment, a log-normal distribution, as demonstrated for the frequency distribution of N02 in ambient air (Fig. 1-7), is typical. 

The following examples demonstrate the contribution of chemometric methods to the differentiated evaluation of element trace analyses in rivers [EINAX and GEISS, 1994],... 

However, it is not just the presence or absence of an element that is useful (as most elements will be present at some concentration), but it is the relative variation in the trace element profile that is the parameter that provides the major discriminatory power. McHard et al. [16] were possibly some of the first researchers to apply a normalization procedure to multielement data in order to maximize the differences between two sets of samples. Their approach, which is now accepted as being a standard tool for use in chemometric investigations, was to identify an element whose concentration was constant, irrespective of the geographical origin of the samples, and then to normalize all other elemental data against it. In McHard s study on fruit juice, they used Zn. The authors of this chapter used Ca in an egg authenticity study, where eggshells were used as the sample matrix (unpublished data) and Mg was used in a study of Welsh onions [14]. 

In a related paper Herrador and Gonzalez [144] described the application of PCA and CA and of two supervised techniques, LDA and back-propagated ANN on Al, Ba, Ca, Cu, K, Mg, Mn, and Zn data obtained from commercial Spanish tea samples. A minitorch ICP-AES instrument was used for the determinations. The characterization of three classes of tea was achieved. In a paper that expands previous research described in reference [47], trace metal concentrations measured by ICP-AES and ICP-MS were employed by Moreda-Pineiro et al. [145] for a more elaborated chemometric treatment on 85 samples of tea of Asian, African, commercial, and unknown origin. Seventeen elements (Al, Ba, Ca, Cd, Co, Cr, Cu, Cs, Mg, Mn, Ni, Pb, Rb, Sr, Ti, V, and Zn) were determined. In addition to the techniques employed in the already mentioned papers (PCA, CA, LDA), soft independent modeling (SIM) of class analogy was also applied. The latter method resulted in the totally correct (100 percent) classification of Chinese teas. 

A. Marcos, A. Fisher, G. Rea, S. J. Hill, Preliminary study using trace element concentrations and a chemometric approach to determine the geographical origin of tea, J. Anal. Atom. Spectrom., 13 (1998), 521-525. 

Chemometric Techniques for Evaluating the Results of Trace Analysis... 

Different methods - for example titrimet-ric, complexometric, photometric, and spec-trophotometric - are available for the determination of hafnium. Recently, multivariate spectrofluorimetry of ultra trace hafni-um(IV) assisted by several chemometric... 

Wang ZP, Shi L and Chen GS (2000) Multivariate spectrofluorimetry of ultra trace zirconium(IV) and hafhium(IV) assisted by several chemometrics methods. Talanta-Oxford 51 315-326. 

In the 50 years since its introduction, the use of GC by the petroleum industry has helped foster many breakthroughs in GC instrumentation. Open-tubular GC columns and the theory that describes them were first introduced by Golay and Ettre in the mid-1950s. The further development of open-tubular capillary columns was done by Desty of British Petroleum, and, with subsequent refinement, this technique is now the standard method for most GC applications. The use of GC for sample analysis was also quickly adopted by the pharmaceutical and food industries and is used for fundamental studies of reaction kinetics and physiochemical measurements. Today the use of GC for the analysis of complex samples such as serum proteins, natural products, essential oils, and environmental samples has become a routine with multidimensional separation techniques and multivariate chemometric analysis providing identificatimi and quantification of trace analytes from complex samples in the sub-ppb range. A GC system usually consists of the following elements (Fig. 1) ... 

The combination of GC with olfactometry is another possibility for detection that has been used in essential oils analysis. " " " Olfactometry adapters are commercially available and should include humidity of the GC effluent at the nose adapter and provide auxiliary gas flow. The correlation among eluted peaks with specific odors allows accurate retention indices or retention times to be estabhshed for the essential oil components. Some of them can be detected in this way after applying chemometric techniques, such as cluster analysis and principal component analysis, to the data from the sensors. A limitation of GC with olfactometry is that peak coelution in complex samples makes identification of the compound(s) responsible for an odor difficult, particularly where trace odorants coelute with larger odor-inactive peaks. One possible solution for identifying character-impact odorants where coelution occurs is to use comprehensive two-dimensional GC (GC X GC). " ... 

In trace analysis it is not sufficient simply to report a level of reproducibility for the actual determination of an analyte. Evaluating the quality of an analysis requires a knowledge of the reproducibility and the uncertainty arising from systematic effects (- Chemometrics). Errors in sampling and/or sample preparation may be orders of magnitude greater than the standard deviation observed in several repetitions of a determination. 

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