Hyperspectral imaging system to on-line monitoring the soy flour content in a functional pasta

, due to its content in nutraceutical compounds such asisoflavones, carotenoids, and other antioxidants. The quantifica-tion of the amount of a functional ingredient is an important stepin food authenticity. The availability of non-destructive techniquesfor quantitative and qualitative analyses of food is therefore desir-able. This research aimed to investigate the feasibility of hyper-spectral imaging in reflectance mode for the evaluation of the soyflour content, also to investigate the possibility of implementing afeed-back control system to precisely dose the soy flour during theindustrial production of pasta. Samples of pasta in shape ofspaghetti were produced with durum wheat semolina and soy flourat increasing percentages (0, to 50%, steps of 5%). A feature selec-tion algorithm was used to predict the amount of soy flour. Themost influent wavelengths were selected, and a six-term Gaussfunction was trained, validated, and tested. The identified transfer function was able to predict the percentage of soy flour with high Error of 1.31. The developed system could represent a feasible tool to control the process in a continuous mode.