Rapid and non-invasive estimation of total polyphenol content and antioxidant activity of natural corks by NIR spectroscopy and multivariate analysis

Abstract

The use of near infrared spectroscopy (NIRS) coupled with multivariate data analysis has been evaluated for the rapid and non-invasive estimation of total polyphenol content (TPC) and antioxidant activity of natural corks. A total of 132 samples were used, using two-thirds and one-third of spectra for calibration and external validation sets, respectively. Regression models were developed by partial least squares (PLS) regression analysis. The best models were achieved by different spectral preprocessing approaches with 7 latent variables for TPC and 9 for antioxidant activity, a variance explained by the models between 64.7 % and 72.0 %, and a standard error of calibration (SEC) between 3.6 and 6.8, respectively. Good relationships between chemical values measured by conventional assays and NIRS predicted values were obtained, with standard error of prediction (SEP) of 5.0 and 5.8 for ABTS and DPPH antioxidant activity, and 5.8 for TPC. Regression lines for calibration and external validation presented good correlation coefficients (r2) from 0.80 to 0.85, and from 0.62 to 0.76, respectively. The models obtained showed that it is possible to estimate rapidly and simultaneously, the TPC and antioxidant activity of natural corks by combining the NIRS with different multivariate analysis tools.