Estimating cooking degree of food e.g. beef steak by acquiring reflectance spectrum of food, performing normalization operation, and determining indicator of cooking degree of food by application of statistical prediction model/spectrum
The process comprises acquiring a reflectance spectrum of the food, performing a normalization operation, and determining an indicator such as sensory and water loss indicator of the cooking degree of the food by the application of a statistical prediction model or the reflectance spectrum. The reflectance spectrum is acquired in a spectral region comprising an absorption peak (400-600 nm) of myoglobin. The statistical prediction model consists of principal component regression model, partial least square model, or projection on latent structures. The process comprises acquiring a reflectance spectrum of the food, performing a normalization operation, and determining an indicator such as sensory and water loss indicator of the cooking degree of the food by the application of a statistical prediction model or the reflectance spectrum. The reflectance spectrum is acquired in a spectral region comprising an absorption peak (400-600 nm) of myoglobin. The statistical prediction model consists of principal component regression model, partial least square model, or projection on latent structures. The acquiring step is carried out by contacting the food with a hot surface during the cooking of the food. The reflectance spectrum is a spectrum of reflectance of a surface of the food that is not contact with the hot surface. An independent claim is included for an apparatus for estimating a cooking degree of a food.Procédé d'estimation du degré de cuisson d'un aliment comportant : (a) l'acquisition d'au moins un spectre de réflectance dudit aliment ； et (b) l'application d'un modèle statistique de prédiction audit ou à chaque spectre pour déterminer un indicateur du degré de cuisson de l'aliment. Appareil pour la mise en œuvre d'un tel procédé.
