Résumé
Vitreousness is an important grading factor for durum wheat kernel that is associated with protein content. The European Union (EU) regulations stipulate the use of a visual method to determine the vitreousness rate. However, some authors have been interested in the development of automatic and non-destructive methods based on near infrared spectroscopy or digital imaging technology. In this paper, we propose to couple spectroscopy and digital imaging technology and, thus, to analyse the potential of a near infrared hyperspectral imaging system to classify wheat kernels by their vitreousness. Hyperspectral reflectance images of wheat kernel at different vitreousness rates have been achieved (wavelength range: 650-1100 nm). A discrimination method using latent variables from partial least squares has enabled satisfactory discrimination results to be obtained: perfect separation between vitreous and non-vitreous kernels and a classification rate reaching up to 94% for the discrimination of total and partial starchy kernel classes