-Trends in the texture and structure as a function of temperature were determined for 2 hard cheeses (Comté and Emmental) and 1 semi-hard cheese (Raclette) using dynamic testing rheology and front-face fluorescence spectroscopy. The storage modulus (G'), the loss modulus (G'') and the complex viscosity (h*) decreased while strain and tan d increased as the temperature increased from 5 °C to 60 °C. Protein tryptophan emission spectra and vitamin A excitation spectra were recorded on cheese samples at 5,10,15,20,25,30,35, 40, 50 and 60 °C. For each cheese, the data sets containing fluorescence spectra and rheology data were evaluated using principal component analysis and factorial discriminant analysis. It was shown that the maps defined by principal components 1 and 2 discriminated cheese samples as a function of temperature whatever the data (dynamic testing rheology data or fluorescence spectra). In addition, the melting temperature of fats for the three cheeses determined from the dynamic rheology data and the vitamin A fluorescence spectra gave similar results, i.e., 30, 32 and 31 °C for Emmental, Comté and Raclette cheeses, respectively. Canonical correlation analysis was applied to cheese dynamic rheological measurements and tryptophan and vitamin A fluorescence spectral collections in order to measure the link between the groups of variables measured on the same samples. The rheology and fluorescence groups of variables were found to be highly correlated since the squared canonical coefficients for canonical variables 1 and 2 were higher than 0.94 and 0.49, respectively.Cheese / structure / texture / melting / fluorescence / rheology Résumé -La spectroscopie de fluorescence frontale : un outil pour l'étude de la fonte des fromages -Corrélations avec les données rhéologiques. L'évolution de la texture et de la structure de deux fromages à pâte pressée cuite (Comté et Emmental) et un fromage à pâte pressée non cuite (Raclette) en fonction de la température a été déterminée par des mesures rhéologiques (test d'oscillation) et par spectroscopie de fluorescence frontale. Le module d'élasticité (G'), le module de perte (G'') et la viscosité complexe (h*) diminuent lorsqu'on fait varier la température entre 5 et 60 °C. Cependant, on note un accroissement de la déformation et de la tangente de l'angle de perte, tan d, dans la même gamme de température. Les spectres d'émission des tryptophanes de protéines et les spectres d'excitation de la vitamine A ont également été enregistrés sur des échantillons de fromages à 5, 10, 15, 20, 25, 30, 35, 40, 50 et
This study aims to evaluate the impact of incorporating pear, date, and apple by-products on pasta properties. Pasta properties including cooking quality, texture, color, rheology, thermal gelling, and microstructural characteristics were evaluated. Common wheat flour was substituted by 0, 2.5, 5, 7, and 10 g/100 g of by-products. To choose the best-suited substitute of flour for the preparation of pasta, the sensorial properties of pasta were investigated. Interrelationships between all the physicochemical parameters were investigated using multiple factor analysis. We also studied the impact of storage (7, 15, and 30 days) on the physicochemical proprieties of pasta. The results revealed that the chemical composition of pasta elaborated with by-products was characterized by higher energy (~386 Kcal) and fiber content (~13%) than the control pasta. Generally, materials added to the durum wheat pasta reduce optimum cooking time, adhesiveness, and extensibility, and enhance the swelling index, cooking loss, cooking water absorption, water activity, firmness, and tenacity of pasta. Cooked pasta samples were significantly (p < 0.05) darker (L*) and greener (-a*) than the control pasta. Increasing the rate of by-products from 2.5% to 10% principally altered the texture and structure of pasta. Scanning electron microscopy analysis showed that the inclusion of by-products into pasta leads to a disruption of the protein matrix. A practical formulation (2.5% of by-products) can be selected, since a significant difference was detected between overall acceptability scores. Grouping the variables in the principal component analysis plot showed that pasta samples can be divided into three groups. Each group was correlated by a specific variable. A significant modification of the physical parameters of pasta was observed after 30 days of storage.
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