The present study was aimed to investigate the potential of multispectral images coupled with chemometric tools (PLSDA and PLS-R) for: (1.) discriminating different French blue veined cheeses belonging to four brand products (Fourme d'Ambert, Fourme de Montbrison, Bleu d'Auvergne, and Bleu des Causses) and (2.) predicting some of physicochemical (pH, ash, dry matter, total nitrogen, water soluble nitrogen, Ca 2+ , Na + , Cl − , and P) and rheological properties (softening and dropping points). The results obtained showed that multispectral imaging system applied to anisotropic blue cheeses succeeded to: (1.) discriminate cheeses based on their blue veins features in spite of the visual similarity of their structure and appearance with percentage of correct classification varying between 30 and 100%; and (2.) predict selected parameters (i.e., Ca 2+ , Cl − , WSN, dropping, and softening points) since R 2 cv ≥ 0.62 and RPD ≥ 1.62 were obtained. Moreover, the predictive results suggested that the image texture of cheese was strongly related to its physicochemical composition and rheological characteristics (softening and dropping points).
The aim of this study was to develop a white bread with improved nutrient contents and reduced levels of potentially harmful Maillard reaction products such as N(ε)-carboxymethyllysine (CML) and 5-hydroxymethylfurfural (HMF). Assays were carried out through a full factorial experimental design allowing the simultaneous analysis of four factors at two levels: (1) wheat flour extraction rates (ash content: 0.60%-0.72%), (2) leavening agents (bakers' yeast - bakers' yeast and sourdough), (3) prebaking and (4) baking conditions (different sets of time and temperature). The baking conditions affected HMF and CML as well as certain mineral contents. A reduced baking temperature along with a prolonged heat treatment was found to be favourable for reducing both the CML (up to 20%) and HMF concentrations (up to 96%). The presence of sourdough decreased the formation of CML (up to 28%), and increased the apparent amounts of calcium (up to 8%) and manganese (up to 17.5%) probably through acidification of the dough. The extraction rate of flours as well as interactions between multiple factors also affected certain mineral content. However, compounds like folate, thiamine, copper, zinc, iron and phytic acid were not affected by any of the factors studied.
The present study aimed to evaluate and compare the ability of front face (FFFS) and synchronous fluorescence spectroscopy (SFS) to predict total fat and FA composition of beef LT muscles coming from 36 animals of 3 breeds (Angus, Limousin and Blond d'Aquitaine). The regression models were performed by using Partial Least Square (PLS) method. In spite of the low number of samples used, the results of this preliminary study demonstrated the ability of fluorescence spectroscopy to predict meat lipids. Nonetheless, the results suggested that the fluorescence spectroscopy is more suited to measure SFA (R(2)p≥0.66; RPD≥2.29) and MUFA (R(2)p≥0.48; RPD≥1.49) than PUFA (R(2)p≤0.48; RPD≤1.63). Moreover, R(2) and RPD factors obtained with FFFS were greater compared to the ones obtained with SFS suggesting that FFFS is more adapted to measure lipid composition of beef meat.
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