Evaluation of the effect of salts on chemical, structural, textural, sensory and heating properties of cheese: Contribution of conventional methods and spectral ones.

Chemical composition, sensory characteristics, textural and functional properties are among the most important characteristics, which directly relates to the global quality of cheese and to consumer acceptability. A number of factors including milk composition, processing conditions and salt content, influences these properties. The past decades many investigations were performed on the possibilities to reduce salt content of cheese due to its adverse health effects, the current lifestyle and the awareness of the consumers for nutrition quality products. Due to the multiple potential effects of reducing NaCl (simple reduction or substitution) on cheese attributes, it is of utmost importance to identify and understand those effects in order to control the global quality and safety of the final product. In the present review a collection of the different results and conclusions drawn after studying the effect of salts by conventional (e.g. wet chemistry) and instrumental (e.g. spectral) methods on chemical, structural, textural, sensory and heating properties of cheese are presented.

ComDim for explorative multi-block data analysis of Cantal-type cheeses: Effects of salts, gentle heating and ripening.

Common Dimension (ComDim) chemometrics method for multi-block data analysis was employed to evaluate the impact of different added salts and ripening times on physicochemical, color, dynamic low amplitude oscillatory rheology, texture profile, and molecular structure (fluorescence and MIR spectroscopies) of five Cantal-type cheeses. Firstly, Independent Components Analysis (ICA) was applied separately on fluorescence and MIR spectra in order to extract the relevant signal source and the associated proportions related to molecular structure characteristics. ComDim was then applied on the 31 data tables corresponding to the proportion of ICA signals obtained for spectral methods and the global analysis of cheeses by the other techniques. The ComDim results indicated that generally cheeses made with 50% NaCl or with 75:25% NaCl/KCl exhibit the equivalent characteristics in structural, textural, meltability and color properties. The proposed methodology demonstrates the applicability of ComDim for the characterization of samples when different techniques describe the same samples.

Delineation of salts, ripening and gentle heating effects on molecular structure of Cantal-type cheese by Mid-infrared spectroscopy.

In this study, five Cantal-type cheeses with different salts (NaCl and KCl) and two ripening times (5 and 15days) were analyzed for their physicochemical characteristics, their structure at a molecular level and their rheological properties during heating (20 to 60°C). The analysis of the molecular structure of cheeses was investigated by MIR spectroscopy coupled with ICA (Independent Components Analysis) and rheological properties by small-amplitude oscillatory rheology. ICA on physicochemical characteristics showed a good discrimination of the cheeses as a function of their chemical characteristics and ripening time. ICA applied to MIR spectra gave Independent Components (ICs) that were attributed to the molecular characteristics of protein, water and fat. Signal proportions of each IC depicted information regarding changes in those ICs with salts, heating and ripening. In addition, similar fat melting temperatures were obtained, regardless the technique used (oscillatory rheology and MIR) for all cheeses. This study demonstrated that MIR spectroscopy coupled with ICA is a promising tool to monitor and characterize modification of cheeses at a molecular level depending on temperature, salt content, and ripening time.

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).

Potential of fluorescence spectroscopy to predict fatty acid composition of beef.

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.