Assessment of quality performance parameters for straight line calibration curves related to the spread of the abscissa values around their mean

In validation of quantitative analysis methods, knowledge of the response function is essential as it describes, within the range of application, the existing relationship between the response (the measurement signal) and the concentration or quantity of the analyte in the sample. The most common response function used is obtained by simple linear regression, estimating the regression parameters slope and intercept by the least squares method as general fitting method. The assumption in this fitting is that the response variance is a constant, whatever the concentrations within the range examined. The straight calibration line may perform unacceptably due to the presence of outliers or unexpected curvature of the line. Checking the suitability of calibration lines might be performed by calculation of a well-defined quality coefficient based on a constant standard deviation. The concentration value for a test sample calculated by interpolation from the least squares line is of little value unless it is accompanied by an estimate of its random variation expressed by a confidence interval. This confidence interval results from the uncertainty in the measurement signal, combined with the confidence interval for the regression line at that measurement signal and is characterized by a standard deviation s(x0) calculated by an approximate equation. This approximate equation is only valid when the mathematical function, calculating a characteristic value g from specific regression line parameters as the slope, the standard error of the estimate and the spread of the abscissa values around their mean, is below a critical value as described in literature. It is mathematically demonstrated that with respect to this critical limit value for g, the proposed value for the quality coefficient applied as a suitability check for the linear regression line as calibration function, depends only on the number of calibration points and the spread of the abscissa values around their mean

Biogeochemical behaviour of Cd, Cu, Pb and Zn in the Scheldt estuary during the period 1981–1983.

Abstract Cu, Cd, Zn and Pb concentrations in both dissolved and particulate phase were assessed during 1995. Data Quality Assurance was an integral part of this study and involved all major steps of the analysis procedure such as sampling, sample handling, preconcentration and determination. Desorption and redox processes clearly control the dissolved Cu and Cd profiles. Mobilisation of dissolved Zn is small and essentially restricted to the low salinity area and the late spring survey. Dissolved Pb shows the clearest dilution pattern. The parameters representative of these processes (dissolved oxygen and salinity) also correlate very well with the particulate metal profiles. In addition, the plankton activity (expressed by the chlorophyll-a levels) may influence the dissolved and particulate metal profiles. In combination with desorption and redox processes, seasonal variations were induced

Average daily nitrate and nitrite intake in the Belgian population older than 15 years

The aim of this study was to assess the dietary intake of nitrate and nitrite in Belgium. The nitrate content of processed vegetables, cheeses and meat products was analysed. These data were completed by data from non-targeted official control and from the literature. In addition, the nitrite content of meat products was measured. Concentration data for nitrate and nitrite were linked to food consumption data of the Belgian Food Consumption Survey. This study included 3245 respondents, aged 15 years and older. Food intakes were estimated by a repeated 24-h recall using EPIC-SOFT. Only respondents with two completed 24-h recalls (n = 3083) were included in the analysis. For the intake assessment, average concentration data and individual consumption data were combined. Usual intake of nitrate/nitrite was calculated using the Nusser method. The mean usual daily intake of nitrate was 1.38 mg kg(-1) bodyweight (bw) day(-1) and the usual daily intake at the 97.5 percentile was 2.76 mg kg(-1) bw day(-1). Exposure of the Belgian population to nitrate at a mean intake corresponded to 38% of the ADI (while 76% at the 97.5 percentile). For the average consumer, half of the intake was derived from vegetables (especially lettuce) and 20% from water and water-based drinks. The average daily intake of nitrate and nitrite from cheese and meat products was low (0.2% and 6% of the ADI at average intake, respectively). Scenario analyses with a higher consumption of vegetables or a higher nitrate concentration in tap water showed a significant higher intake of nitrate. Whether this is beneficial or harmful must be further assessed