Abstract

This paper presents the use of least-squares support vector machine (LS-SVM) for quantitative determination of hydroxyl value (OHV) of hydroxylated soybean oils by horizontal attenuated total reflection Fourier transform infrared (HATR/FT-IR) spectroscopy. A least-squares support vector machine (LS-SVM) calibration model for the prediction of hydroxyl value (OHV) was developed using the range 1805.1–649.9 cm −1. Validation of the method was carried out by comparing the OHV of a series of hydroxylated soybean oil predicted by the LS-SVM model to the values obtained by the AOCS standard method. A correlation coefficient equal to 0.989 and RMSEP = 4.96 mg of KOH/g was obtained. This study demonstrates a better prediction ability of the LS-SVM technique to determine OHV in hydroxylated soybean oil samples by HATR/FT-IR spectra.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.