Near infrared reflectance spectroscopy as a tool for the in-line determination of the moisture concentration in extruded semolina pasta

After extrusion, the optimal moisture content of pasta is attained through drying, taking into account energetic and bio-physical concerns. Monitoring the moisture content of the pasta after the extrusion process, but before the drying process, is useful as the moisture content is variable and may be used to adapt the air characteristics during drying. In this paper, near-infrared (NIR) reflectance spectroscopy is proposed for in-line determination of moisture concentrations in semolina pasta immediately after the extrusion process. Several pasta samples with different moisture concentrations were extruded while the reflectance spectra between 308 and 1704 nm were measured at the extrusion die. An adequate prediction model for the in-line moisture concentration was developed based on the Partial Least Squares (PLS) method using leave-one-out cross-validation. Best cross-validation results were obtained for non-transformed data, confirming the ability to predict excellently the moisture concentration of the extruded pasta (coefficient of determination rCV2=0.956; root-mean-square error of cross-validation RMSECV=0.024 kg/kg). Comparable cross-validation results were obtained based on the most important wavelengths (when at least two different wavelengths were used). This creates opportunities for measuring the moisture content with a low-cost sensor.