Maintaining the predictive abilities of multivariate calibration models by spectral space transformation

2011 ◽  
Vol 690 (1) ◽  
pp. 64-70 ◽  
Author(s):  
Wen Du ◽  
Zeng-Ping Chen ◽  
Li-Jing Zhong ◽  
Shu-Xia Wang ◽  
Ru-Qin Yu ◽  
...  
Keyword(s):  
Multivariate Calibration ◽  
Spectral Space ◽  
Space Transformation ◽  
Calibration Models

Strategy for constructing robust multivariate calibration models

1999 ◽  
Vol 49 (1) ◽  
pp. 1-17 ◽  
Author(s):  
H. Swierenga ◽  
A.P. de Weijer ◽  
R.J. van Wijk ◽  
L.M.C. Buydens
Keyword(s):  
Multivariate Calibration ◽  
Calibration Models

Linear transformations of multivariate calibration models in near infrared spectroscopy: A comparative study

2017 ◽  
Vol 25 (4) ◽  
pp. 223-230 ◽  
Author(s):  
Joseph Dubrovkin
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Cetane Number ◽  
Total Protein Content ◽  
Prediction Errors ◽  
Calibration Data ◽  
Linear Transformations ◽  
Calibration Models

It was shown that linear transformations are suitable for use in multivariate calibration in near infrared spectroscopy as data compression tools. Partial Least Squares calibration models were built using spectral data transformed by expansion in the series of classical orthogonal polynomials, Fourier and wavelet harmonics. These models allowed effective prediction of the cetane number of diesel fuels, Brix and pol parameters of syrup in sugar production and fat and total protein content in milk. Depending on the compression ratio, prediction errors were no larger than 30% of corresponding errors obtained by the use of the non-transformed models. Although selection of the most suitable transformation depends on the calibration data and on the cross-validation method, in many cases Fourier transform gave satisfactory results.

scholarly journals Different spectrophotometric and TLC-densitometric methods for determination of olmesartan medoxomil and hydrochlorothiazide and their degradation products

2018 ◽  
Vol 9 (4) ◽  
pp. 400-407 ◽  
Author(s):  
Selvia Maged Adly ◽  
Maha Mohamed Abdelrahman ◽  
Nada Sayed Abdelwahab ◽  
Nourudin Wageh Ali
Keyword(s):  
Multivariate Calibration ◽  
Degradation Products ◽  
External Validation ◽  
Olmesartan Medoxomil ◽  
Partial Least Square ◽  
Least Square ◽  
Pharmaceutical Dosage Form ◽  
Calibration Models ◽  
Significant Difference

In this work, multivariate calibration models and TLC-densitometric methods have been developed and validated for quantitative determination of olmesartan medoxomil (OLM) and hydrochlorothiazide (HCZ) in presence of their degradation products, olmesartan (OL) and salamide (SAL), respectively. In the first method, multivariate calibration models including principal component regression (PCR) and partial least square (PLS) were applied. The wavelength range 210-343 nm was used and data was auto-scaled and mean centered as pre-processing steps for PCR and PLS models, respectively. These models were tested by application to external validation set with mean percentage recoveries 99.78, 100.01, 100.41 and 100.46% for OLM, HCZ, OL and SAL, respectively, for PLS model and also, 100.22, 100.40, 102.25 and 100.13% for them, respectively, for PCR model. The second method is TLC-densitometry at which the chromatographic separation was carried out using silica gel 60F254 TLC plates and the developing system consisted of a mixture of ethyl acetate:chloroform:methanol: formic acid:tri-ethylamine (60:40:4:4:1, by volume) with UV-scanning at 254 nm. The developed methods were successfully applied for determination of OLM and HCZ in their pharmaceutical dosage form. Also, statistical comparison was made between the developed methods and the reported method using student’s-t test and F-test and results showed that there was no significant difference between them concerning both accuracy and precision.

Sign in / Sign up

Export Citation Format

Share Document