Abstract
A method for basic nitrogen determination in residues of crude oil distillation using infrared spectroscopy and chemometrics algorithms was developed. Interval partial least squares, synergy interval partial least squares, and backward interval partial least squares were evaluated for calibration model construction. The samples were divided into a calibration and prediction set containing 40 and 15 samples, respectively. The first derivative with a Savitzky-Golay filter and the mean centered data showed the best results and were used in all calibration models. The backward interval partial least squares algorithm with spectra divided in 60 intervals and combinations of 4 intervals (1407 to 1372; 1117 to 1082; 971 to 936; 914 to 879 cm−1) showed the best root mean square error of prediction of 0.016 wt%. This calibration model displayed a suitable correlation coefficient between reference and predicted values.
Acknowledgments
The authors are grateful to INCT – Bioanalítica, CNPq, CAPES, and FAPERGS for supporting this study and also to CENPES/PETROBRAS S.A. for financial support.
Notes
a VN, total variables numbers.
b LVs, latent variables.
a VN, total variables numbers.
b LVs, latent variables.
a VN: total variables numbers.
b LVs: latent variables.