Application of synchronous fluorescence spectroscopy for the determination of some chemical parameters in PDO French blue cheeses

2D-Cross Correlation Spectroscopy Coupled with Molecular Fluorescence Spectroscopy for Analysis of Molecular Structure Modification of Camel Milk and Cow Milk Mixtures during Coagulation

Synchronous fluorescence spectroscopy (SFS) coupled with two-dimensional correlation spectroscopy (2DCOS) was employed to monitor, at the molecular level, the coagulation of five mixture ratios of camel's milk (CaM) and cow's milk (CM) (100% CaM, 75% CaM:25% CM, 50% CaM:50% CM, 25% CaM:75% CM and 100% CM). The dissimilarities among the different formulations are highlighted on the synchronous 2DCOS-SFS. In addition, according to the cross-peak symbols in synchronous and asynchronous spectra, the rate of response modification in riboflavin, protein and vitamin A matched with common coagulation phenomena usually reported during chymosin coagulation (hydrolysis of κ-casein, destabilization of casein micelles and aggregation). This study demonstrated that 2DCOS-SFS is a successful strategy to discriminate milk mixtures and to monitor molecular structure modifications during coagulation process.

Performance of fluorescence spectroscopy for beef meat authentication: Effect of excitation mode and discriminant algorithms

This study evaluated the performance of classical front face (FFFS) and synchronous (SFS) fluorescence spectroscopy combined with Partial Least Square Discriminant Analysis (PLSDA), Support Vector Machine associated with PLS (PLS-SVM) and Principal Components Analysis (PCA-SVM) to discriminate three beef muscles (Longissimus thoracis, Rectus abdominis and Semitendinosus). For the FFFS, 5 excitation wavelengths were investigated, while 6 offsets were studied for SFS. Globally, the results showed a good discrimination between muscles with Recall and Precision between 47.82 and 94.34% and Error ranging from 6.03 to 32.39%. For the FFFS, the PLS-SVM with the 382nm excitation wavelength gave the best discrimination results (Recall, Precision and Error of 94.34%, 89.53% and 6.03% respectively). For SFS, when performing discrimination of the three muscles, the 120nm offset gave the highest Recall and Precision (from 57.66% to 94.99%) and the lowest Error values (from 6.78 to 8.66%) whatever the algorithm (PLSDA, PLS-SVM and PCA-SVM).

Methodologies for the Characterization of the Quality of Dairy Products

The growing interest of consumers in food quality and safety issues has contributed to the increasing demand for sensitive and rapid analytical technologies. Physicochemical, textural, sensory, etc., methods have been used to evaluate the quality and authenticity of milk and dairy products. Despite the importance of these standard methods, they are expensive and time consuming. Recently, spectroscopic methods have shown great potential due to speed of analysis, minimal sample preparation, high repeatability, low cost, and, most of all, the fact that these techniques are noninvasive and nondestructive and, therefore, could be applied to any on-line monitoring system. This chapter gave examples of the application of the most commonly traditional methods for the determination of the quality of milk and dairy products. A special focus is devoted to the use of infrared and fluorescence spectroscopies for the evaluation of the quality of dairy products.