Reference standard material Regression model

Preparation of Standards and Curves In the absence of a true blank control matrix, standards can be prepared in a protein buffer at multiple (generally 9 11) concentrations for the initial test of assay range. For method validation and sample assay, 6 8 nonzero concentrations of standards plus anchor points should be used to define a curvilinear standard curve. If a commercial kit is to be used, it is preferred that the standards be prepared from a bulk reference material to assure the consistencies of the standard as well as adding enough standard points to properly define the regression model. Before replacing the kit standards with those prepared... 

This expression has been used as the model equation for the regression model in the past. As pointed out by Baxter et aJ.[36], however, this is equivalent to assuming fip =fk/i- The pitfall of this approach is that the resultant value of the regression intercept is not used, rather its value is assumed from Eq. (5.35). To avoid the errors of Eq. (5.39), Baxter et al. proposed a revised regression model that combines two regressions one for the reference material of the analyte and internal standard, and the other that combines the sample and the internal standard [36]. Reliance on the reference material for the measurand, however, is unnecessary, provided that the isotope amount ratio of the internal standard is known [Eq. (5.39)]. However, it is a viable option nevertheless. 

Calibration Most process analyzers are designed to monitor concentration and/or composition. This requires a calibration of the analyzer with a set of prepared standards or from well-characterized reference materials. The simple approach must always be adopted first. For relatively simple systems the standard approach is to use a simple linear relationship between the instrument response and the analyte/ standard concentration [27]. In more complex chemical systems, it is necessary to adopt either a matrix approach to the calibration (still relying on the linearity of the Beer-Lambert law) using simple regression techniques, or to model the concentration and/or composition with one or more multivariate methods, an approach known as chemometrics [28-30]. 

Twenty-five mixtures were used for calibration development, with nicotinamide concentrations ranging from 0 to 6% of the pre-mix formulation. Spectra were collected in duplicate on a Pacific Scientific Mk 16350 at 2 nm intervals between 1200 and 2400 nm. The spectra were reference corrected using a standard ceramic reference. Second derivative spectra were calculated and the calibration obtained by regressing nicotinamide concentration against the ratio of the second derivative values at 2138 nm (a nicotinamide absorbance peak) and 2070 nm (a spectral minimum in the pre-mixes). The validity of the calibration was determined in two ways first, 25 more samples were prepared in the laboratory and used to validate the model second, 25 commercially prepared pre-mix samples with different batches of raw materials were analyzed by the NIR method and by the HPLC reference method. 

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