Prediction of semolina technological quality by FT-NIR spectroscopy

Abstract

The feasibility of applying FT-NIR spectroscopy (a rapid and non-destructive method) to evaluate and predict semolina characteristics by means of spectra collected directly from the kernels was investigated. More than 500 samples of durum wheat grains and of the corresponding semolina, representative of the Italian production of 4 different crops (from 2002/2003 to 2005/2006) were analyzed. Pasta-making capability of each semolina sample was assessed by the reference methods, for protein, gluten content, gluten index and alveographic indices. The kernels were also evaluated by a FT-NIR spectrometer, fitted with an integration sphere working in diffuse reflectance. The processed spectra collected on the kernels were correlated with the chemical and rheological parameters obtained by the reference tests performed on semolina. The PLS algorithm was used to develop calibration models from the original spectra datasets. Protein content proved to be well correlated to kernel spectral data: high values for the RPD indicate efficient NIR reflectance predictions for protein content. The models obtained for gluten content, gluten index and alveographic W and P/L parameters were less successful. The results of this work highlighted the feasibility of applying FT-NIR spectroscopy to evaluate and predict the technological properties of semolina, in particular that of the protein content, by collecting the spectra directly from the kernels, without performing further grinding or milling operations.