Article ID Journal Published Year Pages File Type
4516107 Journal of Cereal Science 2011 6 Pages PDF
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.

► Semolina characteristics were determined by collecting FT-NIR spectra directly from durum wheat kernels. ► Protein, gluten quality and quantity indices were determined by reference methods and correlated with FT-NIR spectra. ► Protein content of semolina was highly correlated to spectral data. ► FT-NIR spectroscopy can be used as a rapid method for the prediction of semolina technological quality.

Related Topics
Life Sciences Agricultural and Biological Sciences Agronomy and Crop Science
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