Correlation between porosity of cork planks before and after boiling using near infrared spectroscopy

The aim of this study was to evaluate the potential of near infrared spectroscopy (NIRS) in predicting the coefficient of porosity of raw and boiled cork samples used mainly for producing cork stoppers for wine bottling. The classification of cork planks is currently performed visually in the last stage of preprocessing after boiling in water. In this study, calibration models have been developed on 279 cork samples before and after boiling. Three models were obtained: one which predicts the coefficient of porosity of unprocessed samples, a second one that predicts porosity in boiled samples and finally a model that predicts the coefficient of porosity of boiled samples from spectra of raw samples. The models obtained showed a coefficient of determination of 0.58, 0.59 and 0.52, respectively. These results show that the modified partial least squares models based on NIRS technology can be used for screening cork porosity, not only at the two stages of processing, but also to predict boiled porosity. This suggests that NIRS technology could be used for determining the coefficient of porosity in boiled cork planks, and could also provide a useful tree selection tool.