Errors sample pretreatment

In frames of the present work the problems of elemental analysis of human bio-substrates (blood semm, hair and bones) are diseussed. Sample pretreatment proeedures using ash and mineral aeids digestion were developed. The main sourees of systematie errors were studied and their elimination ways were suggested. 

Error 1 CRMs completely or partly not identical with the matrix to be analyzed Ber-mejo-Barrera et al. (1999) studied enzymatic hydrolysis procedures using pronase E as sample pretreatment for multi-element - Cu, Fe, Mg, Zn, Ag, As, Cd, and Pb -determination in biological materials, mussel samples and human hair. 

In general, the calibration curve method is suitable for all samples where the test substance is not bound in complexes or when it can be liberated from complexes by suitable sample pretreatment. Otherwise, the compositions of the samples and of the standard solutions must be as similar as possible to obtain results with acceptable accuracy. In view of the ISE potential drift, the calibration must be repeated often (at least twice a day). As mentioned above, the precision of the determination is not particularly high with a common precision of the potential measureihent at a laboratory temperature of 1 mV the relative error is 4% for univalent and 8% for divalent ions [58], However, this often suffices for practical analytical purposes. An advantage is that the same precision... 

Interference is defined as an effect causing a systematic deviation in the measurement of the signal when a sample is nebulized, as compared with the measure that would be obtained for a solution of equal analyte concentration in the same solvent, but in the absence of concomitants. The interference may be due to a particular concomitant or to the combined effect of several concomitants. A concomitant causing an interference is called an interferent. Interference only causes an error if not adequately corrected for during an analysis. Uncorrected interferences may lead to either enhancements or depressions. Additionally, errors may arise in analytical methods in other ways, e g. in sample pretreatment via the... 

Several systematic errors were investigated, mainly related to the sample pretreatment steps (microwave acid digestion, ultrasound acid leaching and slurry sampling), calibration mode and number of repeats. Experimental designs and principal components were used... 

The strict regulations of the pharmaceutical industry have a significant effect on the quality control of final products, demanding the use of reliable and fast analytical methods. The capacity that the technique has for the simultaneous determination of several APIs with no need of, or with minimum sample pretreatment, has considerably increased its application in pharmaceutical analytical control. The main limitation of NIR is the relative reduced sensitivity that limits the determination of APIs in preparations when its concentration is smaller than 1%. Nevertheless, instrumental improvements allow the determination below this limit depending on the nature of the analyte and the matrix, with comparable errors to the ones obtained with other instrumental techniques. The reference list presents an ample variety of analytical methodologies, types of samples, nature of analyte and calibration models. A detailed treatment of each one eludes to the extension of this chapter. Many applications have been gathered in recent reviews.124-128 Table 10.2 summarizes the most recent reported uses of NIR in this context. 

The analytical error can be split into suberrors according to the various steps of sample pretreatment and the analytical procedure. A qualitative discussion of the different contributions to the sampling error is given by WEGSCHEIDER [1994]. 

Accuracy can also be demonstrated through participation in properly conducted interlaboratory studies, which are also useful to detect systematic errors (Gtinzler 1996) related to, e.g. sample pretreatment (e.g. extraction, clean-up), final measurement (e.g. calibration error, spectral interference) and laboratory competence. As described below, interlaboratory studies are organised in such a way that several laboratories analyse a common material which is distributed by a central laboratory responsible for the data collection and evaluation. 

There are two basic approaches off-line and on-line. The off-line method, as discussed in the chapters on sample pretreatment, are most often used because they involve either manually or automatically collecting a fraction from a sample cleanup sorbent. The appropriate fraction is transferred and then assayed by a second chromatographic method. The manual steps are time-consuming and potentially introduce significant error to the j precision and accuracy of the method. The on-line method, when fully automated, would have the chromatography system perform sample pre- j treatment by column switching between two or more columns. j... 

Use of Internal Standards The use of internal standards envisages different possibilities. The procedure described here is based on two internal standards. Once thawed, fish sample were dissolved in TMAH, ethylated with NaBEt4, extracted into iso-octane and subjected to GC-ICP-MS for the identification and quantification of Me-Hg and inorganic Hg2+. For the correction of procedural errors two internal standards were used. The sample pretreatment was corrected by the recovery factor of the spiked dibutyl-dipentyl-Sn (DBT-pe), while the GC-ICP-MS measurements were controlled by the signal stability of Xe added to the GC carrier gas [47], In another application propyl-Hg was used as an internal standard to correct for matrix-induced ion signal variation and instrumental drift [65]. 

According to Stoeppler et al. [15], severe errors up to a factor of two may result from ETA—AAS analysis of biological materials without some form of sample pretreatment. The approaches that will be discussed here are (a) the use of diluent solutions to minimise matrix and molecular absorption interferences (b) partial decomposition techniques in which metals are extracted from proteins with acids (c) dissolution of tissue samples without complete oxidation (d) complete oxidation procedures such as dry ashing, wet digestion at ambient and elevated pressures, and low temperature ashing with reactive gases at low pressures. 

The internal standard (I.S.) method is a more accurate method. The I.S. technique can compensate for both instrumental and sample preparation errors and variations (e.g., dilution and extraction) [45, 46], Sample pretreatment steps such as extraction often result in sample losses, and a proper I.S. standard should be chosen to mimic the variations in these steps. Thus, both the accuracy and precision of quantitative data increase if an I.S. is included in the procedure. The I.S. should be similar but not identical to the analyte, and the two should be well resolved in the chromatographic step. The standard curves are obtained from standards of blank samples spiked with different known concentrations of the analyte of interest and addition of an I.S. at constant concentration. Also to the unknown samples the same constant concentration of the I.S. is added. The standard samples are processed in parallel with the unknown samples. In the calibration curve, the ratios of analyte to I.S. peak area (or height) are plotted versus the concentration of the analyte. A proper I.S. in a bioanalytical chromatographic method should fulfill the following requirements [44] ... 

Data received from three laboratories were excluded from the statistical analysis because all three reported low enzymatic activity (< 50% of the expected values), due to procedural errors. For example, laboratory J performed sample pretreatment over a period of 4 days and assayed for activity during the fifth day, this caused significant loss of enzymatic activity. Two laboratories did not return results. Statistical analyses were conducted using the data produced by the remaining participants results are shown in Table 16.6. 

In chemical analysis, the substances to be determined are rarely directly measurable and sample pretreatment is in most cases necessary to convert or separate the analyte in a form that is compatible with the measurement system. This may imply that the initial physical or chemical composition of the sample is changed without loosing control of this change so that the traceability to a determined reference (e.g. fundamental units) is maintained. Typical pretreatment steps are e.g. digestion, extraction, purification these are frequently followed by intermediate steps such as derivatisation or separation, calibration and final detection. Each action undertaken in one of these steps represents a possible source of error, which adds to the total uncertainty of the final determination. 

It must be taken into account that usually several sample pretreatment steps are necessary between sampling and placing the prepared sample into the chromatograph. However, the fewer the sample preparation techniques before injection, the better. A clear and optimized sample preparation strategy is necessary to minimize the number of steps because each step represents additional time and is a potential source of errors (contamination, loss of analytes and changes in actual composition). 

Analyses of soil require stronger sample pretreatments, such as, SFE, FMASE, and ultrasonic LEE, owing to the increased complexity of the matrix. These operations are prone to error, so they detract somehow from precision and accuracy. 

Sample pretreatment is still currently the weakest link, the time-determining step in the whole analytical procedure and the primary source of errors. The increasing need for the determination of numerous analytes at lower and lower levels and in increasingly complex matrixes makes sample pretreatment, especially trace enrichment, an indispensable step in many analytical procedures. 

Sample preparation is the most general application of both workstations and robotic stations as the tasks involved in this step of the analytical process are the most time-consuming, error prone, and difficult to develop by unskilled operators in addition, safety restrictions apply when toxic materials are to be handled. The use of a specific approach depends on the number of steps involved and their complexity. Table 1 summarizes the features of selected general and specific sample pretreatment procedures used in the environmental and clinical fields. Whereas most environmental samples subjected to a robotic treatment are solid, those dealt with by clinical... 

As in many such problems, some form of pretreatment of the data is warranted. In all applications discussed here, the analytical data either have been untreated or have been normalized to relative concentration of each peak in the sample. Quality Assurance. Principal components analysis can be used to detect large sample differences that may be due to instrument error, noise, etc. This is illustrated by using samples 17-20 in Appendix I (Figure 6). These samples are replicate assays of a 1 1 1 1 mixture of the standard Aroclors. Fitting these data for the four samples to a 2-component model and plotting the two first principal components (Theta 1 and Theta 2 [scores] in... 

An increase from 5 to 10 in the number of factors representing the original data results in a substantial reduction in the error. Because of the data pretreatment used, the spectral error cannot be directly compared to the experimental error determined from the data set. When five factors were used, two different lignite samples were flagged as possible outliers based on their spectral variances relative to the rest of the data set. With ten factors, one of the lignites was accommodated within the factor model (although ten factors may not have been required to accommodate it). With thirteen factors, both lignites were accommodated. 

A complication in the study of biological materials is that the species of an element which are either formed and/or take part in physiological reactions in different compartments may vary. It is therefore necessary, especially during the sampling and pretreatment steps, that the constituents from different compartments are very carefully separated. For example, in the study of the speciation of an element in blood serum contaminants originating from the erythrocytes could lead to errors in the results. 

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