A method is proposed for the simultaneous determination of albumin and immunoglobulin G (IgG1) with fluorescence spectroscopy and multivariate calibration with partial least squares regression (PLS).
Multivariate calibration with experimental design (ED) and artificial neural networks (ANN) modeling can be used to estimate equilibria constants from any kind of protonation or metal ligand equilibrium data like potentiometry, polarography, spectrophotometry, extraction, etc.
In multivariate calibration with the spectral dataset, variable selection is often applied to identify relevant subset of variables, leading to improved prediction accuracy and easy interpretation of the selected fingerprint regions.
Elman recurrent network was applied for non-linear multivariate calibration and together with the whole voltammogram to improve predictive ability.
The predictability of multivariate calibration models, calculated with offline near-infrared spectroscopy (NIRS), assessing impact of magnesium stearate (MgSt) fraction, blending time, and compression force on the tablet breaking force (TBF) of SPRESS® B820 was statistically compared.
The bases of multivariate calibration are presented with special attention to some points usually not considered or underevaluated, i.e., the sampling design, the number of samples necessary to obtain a reliable regression model, the effect of noisy predictors, the significance of the parameters used to evaluate the performance ability of the regression model.
A comparative study of the use of MCR and ILS methods for the resolution of five-component mixture of PA, MP, PP, CH and PS has been accomplished showing that the two multivariate calibration methods provide, with adequate software support, a clear example of the high resolving power of these techniques.
We show how a multivariate calibration can be achieved with the use of two weeks long on-field data recording and neural regression systems.
Infrared spectroscopic (IRS) techniques combined with multivariate calibration methods are primarily used for on-line analysis, in situ sensors or automatic sampling.
Therefore, the objective of this study was to develop and validate a multivariate calibration model in association with the near infrared spectroscopy technique (NIR) for the simultaneous determination of rifampicin, isoniazid, pyrazinamide and ethambutol.
The whole chemiluminescence-time profiles, acquired using the stopped-flow technique in a continuous-flow system, allowed the use of the time-resolved chemiluminescence (CL) data in combination with multivariate calibration techniques, as partial least squares (PLS), for the quantitative determination of both opiate narcotics in binary mixtures.
