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Simultaneous spectrophotometric determination of phenanthridine, phenanthridinone and phenanthridine N-oxide using multivariate calibration methods

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Sorouraddin M.-H., Amini K., Naseri A., Rashidi M.-R.
Open Chemistry
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2010
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vol. 8
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issue 1
207-213
EN
The multivariate calibration methods, partial least squares (PLS) and principle component regression (PCR) have been used to determine phenanthridine, phenanthridinone and phenanthridine N-oxide in spiked human plasma samples. Resolution of binary and ternary mixtures of analytes with minimum sample pre-treatment and without analyte separation has been successfully achieved analyzing the UV spectral data. The net analyte signal (NAS) concept was also used to calculate multivariate analytical figures of merit such as limit of detection, selectivity and sensitivity. The simultaneous determination of three analytes was possible by PLS and PCR processing of sample absorbance in the 210–355 nm region. Good recoveries were obtained for both synthetic mixtures and spiked human plasma samples. [...]
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Prediction of properties of biodiesel-diesel blends using spectrofluorimetry and multivariate calibration

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Meira M., Quintella C., Pepe I., Costa Neto P., Santos Tanajura A., Silva H.
Open Chemistry
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2012
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vol. 10
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issue 4
1328-1337
EN
Regressions based on fluorescence spectroscopy were developed to provide relatively inexpensive and rapid measurements of the concentration, viscosity, and specific gravity of biodiesel-diesel blends. The methods involved obtaining a mathematical model from spectrofluorimetric data and data from a given property (concentration, dynamic viscosity, or specific gravity) using partial least squares (PLS) regression, which was then applied as a model for predicting properties of interest. The predicted concentrations, dynamic viscosities, and specific gravities of the biodiesel-diesel blends were compared with actual values and agreed reasonably well with the obtained results. The models showed high correlation between real and predicted values. The R-square values near 1 indicated excellent model accuracy for predicting concentrations, specific gravities, and dynamic viscosities of biodiesel-diesel blends. The residual distribution did not follow a trend with respect to the predicted variables, indicating an excellent fit to the data. [...]
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