Journal Article

Transfer of multivariate calibration model for simultaneous electrochemical determination of ascorbic acid and uric acid

Khoshkam, Maryam, Salehniya, Haneie, Amiri, Mandana, Sefid-Sefidehkhan, Yasaman

2021

Overview

Multivariate analysis is one of the most interesting analytical methods in the analysis of many electrochemical data from pharmaceutical and biological analytes. However, there are some challenges in the electrochemical analysis including potential shifts from sample to sample and alterations in the baselines. To minimise the effect of these alterations in baselines and potentials, one tries to do all experiments in one day. However, this is impossible when there are many samples. Calibration transfer is one of the most interesting methods to transfer calibration model between two conditions or two instruments. In this study, a calibration transfer strategy was used to transfer the multivariate calibration model of DPV data from a mixture of ascorbic acid (AA) and uric acid (UA) in the same experimental condition but two different times. The data were recorded from the unmodified electrode and the voltammetric peaks of target compounds are overlapped with each other, making it impossible to be estimated by conventional univariate electrochemical methods. In this study, it was shown that before calibration transfer the prediction results are not accurate and the per cent of relative error in predicted concentration from slave data was comparable to the per cent of relative error in a predicted concentration of UA and AA in the master data.Graphical abstractSynopsis: For the first time, calibration transfer strategy was applied to reuse the multivariate calibration model of DPV data for prediction of samples which acquired after one month. Reusing the calibration model is economic and time saving approach for prediction of data which are acquired in different time with the same experimental condition.

• Publisher: Springer Nature B.V
• Subject: Algorithms / Ascorbic acid / Calibration / Carbon / Data acquisition / Electrochemical analysis / Electrodes / Electrolytes / Methods / Multivariate analysis / Nanoparticles / Neural networks / NMR / Nuclear magnetic resonance / Predictions / Reuse / Uric acid / Voltammetry / Wavelet transforms