A research team from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has proposed a novel model optimization algorithm—External Calibration-Assisted Screening (ECA)— that ...

In addition to the two univariate calibration models described, two multivariate models were evaluated. In (III) MLR, three independent variables were used: i) the analyte line intensity (C I 193.03 ...

The spectra and concentration data were subjected to third-party chemometric software, developing a calibration model utilizing PLS regression methodology. For a more comprehensive discussion on PLS ...

Calibration model building is composed of suitable number of samples and multivariate regression techniques. The accuracy of prediction is determined by both factors (steps). In these two steps, the ...

The utility of near-infrared (NIR) spectroscopy for rapid characterization requires multivariate algorithms for building calibration models. The most prevalent algorithm used for building calibration ...

For both BRIX and POL goodness of fit showed correlation coefficients of 0.99. These results indicate that the models developed for BRIX and POL can be used as an alternative to standard procedures in ...

Finally, the obtained multivariate calibration model was applied in the determination of samples of three batches of a DIP pharmaceutical formulation produced by IQUEGO (Goiânia, Brazil). These ...

MT-PFCE is designed for the most general scenario where multiple instruments require calibration enhancement. This method can be used to simultaneously enhance the calibration of both the master and ...

Multivariate calibration involves a series of mathematical models for processing partially selective instrumental signals, particularly near-infrared (NIR) spectra, (1) to determine analyte ...

The quantitative analysis of surface-enhanced Raman spectra using scattering nanoparticles has shown the potential and promising applications in in vivo molecular imaging. The diverse approaches have ...