Pseudo-univariate calibration based on independent component analysis for determination of the carbendazim concentration in orange juice

Abstract

This work shows the ICA application to pseudo-univariate calibration using near infrared spectroscopy (NIR) data to determine carbendazim concentration in orange juice. To this, the orange juice from safe sources (without carbendazim) was spiked with carbendazim in the concentration range from 0.5 to 2.0 (mgmL−1). The ICA was performed with JADE (Joint Approximate Diagonalization of Eigenmatrices) algorithm after first derivative to baseline correction of NIR spectra in the range from 900 to 1700nm. The ICA scores were plotted against carbendazim concentrations in a pseudo-univariate calibration model with correlation coefficient 0.9791. By using this model, the determination of carbendazim concentrations, in four independent samples, showed an absolute error lower than 0.2mgmL−1. The results allow to suggest that the combination of NIR measurements and ICA makes possible the direct quantification of carbendazim in matrices with unknown interferents, where the second order advantage with first order data can be achieved.