Applicability of Confocal Raman Microscopy to Observe Microstructural Modifications of Cream Cheeses as Influenced by Freezing

Confocal Raman microscopy is a promising technique to derive information about microstructure, with minimal sample disruption. Raman emission bands are highly specific to molecular structure and with Raman spectroscopy it is thus possible to observe different classes of molecules in situ, in complex food matrices, without employing fluorescent dyes. In this work confocal Raman microscopy was employed to observe microstructural changes occurring after freezing and thawing in high-moisture cheeses, and the observations were compared to those obtained with confocal laser scanning microscopy. Two commercially available cream cheese products were imaged with both microscopy techniques. The lower resolution (1 µm/pixel) of confocal Raman microscopy prevented the observation of particles smaller than 1 µm that may be part of the structure (e.g., sugars). With confocal Raman microscopy it was possible to identify and map the large water domains formed during freezing and thawing in high-moisture cream cheese. The results were supported also by low resolution NMR analysis. NMR and Raman microscopy are complementary techniques that can be employed to distinguish between the two different commercial formulations, and different destabilization levels

The microbiota of Mozzarella di Bufala Campana PDO cheese: a study across the manufacturing process

IntroductionMozzarella di Bufala Campana PDO cheese (MBC) is a globally esteemed Italian cheese. The traditional cheesemaking process of MBC relies on natural whey starter culture, water buffalo's milk, and the local agroecosystem.MethodsIn this study, the microbial ecology of intermediate samples of MBC production, coming from two dairies with slightly different cheesemaking technology (dairy M large producer, and dairy C medium-small), was investigated using 16S rRNA amplicon sequencing. This research aimed to provide insights into the dynamics of microbial consortia involved in various cheesemaking steps.Results and discussionAll samples, except for raw buffalo milk, exhibited a core microbiome predominantly composed of Streptococcus spp. and Lactobacillus spp., albeit with different ratios between the two genera across the two MBC producers. Notably, the microbiota of the brine from both dairies, analyzed using 16S amplicon sequencing for the first time, was dominated by the Lactobacillus and Streptococcus genera, while only dairy C showed the presence of minor genera such as Pediococcus and Lentilactobacillus. Intriguingly, the final mozzarella samples from both producers displayed an inversion in the dominance of Lactobacillus spp. over Streptococcus spp. in the microbiota compared to curd samples, possibly attributable to the alleviation of thermal stress following the curd stretching step. In conclusion, the different samples from the two production facilities did not exhibit significant differences in terms of the species involved in MBC cheesemaking. This finding confirms that the key role in the MBC cheesemaking process lies with a small-sized microbiome primarily composed of Streptococcus and Lactobacillus spp

A coupled photogrammetric–finite element method approach to model irregular shape product freezing: Mozzarella cheese case

The freezing process can be industrially performed to extend shelf life and to improve exportability of Italian high-moisture Mozzarella cheese. This cheese is usually characterized by a non-regular spheroidal shape that may be responsible for local differences of temperature on the surface and that can influence the overall freezing time. In this work, Mozzarella freezing was modelled by coupling the finite element method and a photogrammetric procedure that permitted to reconstruct the three-dimensional domain of the product. Computational models were validated by performing experimental trials, and results were accurate (root mean square error<1.47°C). With the photogrammetric technique it was possible to estimate volume, surface area, shape and size of the cheeses, and to study temperature–surface distribution that was found to be non-homogeneous. Freezing models highlighted that the surface area-to-volume ratio of the product, that ranged between 1.09 and 1.15cm−1, is one of the most critical parameters that define the freezing time of the cheese. A geometrical approximation of the cheese based on the surface area-to-volume ratio, showed good accuracy in terms of freezing times. These models can be valuable for Mozzarella cheese freezing optimization and design, to recover efficiency and to improve quality