scholarly journals SPECTROMETRIC DETERMINATION OF ROSUVASTATIN AND EZETIMIBE IN TABLETS BY MULTIVARIATE CALIBRATION APPROACH

2018 ◽  
Vol 2 (2) ◽  
pp. 1-12
Author(s):  
Hakan AKTAŞ ◽  
Ümit UÇAR
Keyword(s):  
Multivariate Calibration ◽  
Calibration Approach

scholarly journals A multivariate calibration approach for determination of petroleum hydrocarbons in water by means of IR spectroscopy

2010 ◽  
Vol 24 (7-8) ◽  
pp. 444-447 ◽  
Author(s):  
María Dolores Ruiz ◽  
Isneri Talavera Bustamante ◽  
Angel Dago ◽  
Noslen Hernández ◽  
Ana C. Núñez ◽  
...  
Keyword(s):  
Ir Spectroscopy ◽  
Petroleum Hydrocarbons ◽  
Multivariate Calibration ◽  
Calibration Approach

Determination of total sulfur in diesel fuel employing NIR spectroscopy and multivariate calibration

The Analyst ◽  
2003 ◽  
Vol 128 (9) ◽  
pp. 1204-1207 ◽  
Author(s):  
Márcia C. Breitkreitz ◽  
Ivo M. Raimundo, Jr ◽  
Jarbas J. R. Rohwedder ◽  
Celio Pasquini ◽  
Heronides A. Dantas Filho ◽  
...  
Keyword(s):  
Diesel Fuel ◽  
Multivariate Calibration ◽  
Nir Spectroscopy ◽  
Total Sulfur

Nondestructive NIR and NIT Determination of Protein, Fat, and Water in Plastic-Wrapped, Homogenized Meat

1992 ◽  
Vol 46 (11) ◽  
pp. 1685-1694 ◽  
Author(s):  
Tomas Isaksson ◽  
Charles E. Miller ◽  
Tormod Næs
Keyword(s):  
Diffuse Reflectance ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Principal Component Regression ◽  
Principal Component ◽  
Prediction Errors ◽  
Optimal Test ◽  
Meat Samples ◽  
Water Contents

In this work, the abilities of near-infrared diffuse reflectance (NIR) and transmittance (NIT) spectroscopy to noninvasively determine the protein, fat, and water contents of plastic-wrapped homogenized meat are evaluated. One hundred homogenized beef samples, ranging from 1 to 23% fat, wrapped in polyamide/polyethylene laminates, were used. Results of multivariate calibration and prediction for protein, fat, and water contents are presented. The optimal test set prediction errors (root mean square error of prediction, RMSEP), obtained with the use of the principal component regression method with NIR data, were 0.45, 0.29 and 0.50 weight % for protein, fat, and water, respectively, for plastic-wrapped meat (compared to 0.40, 0.28 and 0.45 wt % for unwrapped meat). The optimal prediction errors for the NIT method were 0.31, 0.52 and 0.42 wt % for protein, fat, and water, respectively, for plastic-wrapped meat samples (compared to 0.27, 0.38, and 0.37 wt % for unwrapped meat). We can conclude that the addition of the laminate only slightly reduced the abilities of the NIR and NIT method to predict protein, fat, and water contents in homogenized meat.

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