Raman spectroscopy as a tool for reagent free estimation

TL;DR

This study demonstrates that near-infrared Raman spectroscopy combined with multivariate analysis can accurately quantify urinary urea levels without reagents, offering a rapid and non-invasive diagnostic tool.

Contribution

The paper introduces a novel application of Raman spectroscopy with PLS regression for reagent-free urinary urea estimation, achieving over 90% accuracy.

Findings

Raman spectroscopy can detect urinary urea with high accuracy.

Multivariate PLS regression effectively predicts urea concentration.

The method is reagent-free and rapid.

Abstract

We present results of Raman spectroscopic studies of urine to determine the suitability of near-infrared Raman spectroscopy for quantitative estimation of urinary urea. The Raman spectra were acquired from the urine samples with an inbuilt Raman spectroscopy setup that employs a 785-nm diode laser as the Raman excitation source. A multivariate algorithm based on partial least square (PLS) regression was developed to predict the concentration of urea depending on the measured sets of Raman spectra and the reference urea concentration. The computed results shows that Raman spectroscopy in amalgamation with PLS-based multivariate chemometric algorithm can detect urea in urine samples with an accuracy of >90 %