Water and oil signal assignment in low-moisture mozzarella as determined by time-domain NMR T2 relaxometry

Ice crystallization and structural changes in cheese during freezing and frozen storage: implications for functional properties

Temperature-mediated preservation techniques offer a simple, scalable, effective, and fairly efficient method of long-term storage of food products. In order to ensure the uninterrupted availability of cheese across the globe, a critical understanding of its techno-functional properties as affected by freezing and frozen storage is essential. Detailed studies of temperature-mediated molecular dynamics are available for relatively simpler and homogeneous systems like pure water, proteins, and carbohydrates. However, for heterogeneous systems like cheese, inter-component interactions at sub-zero temperatures have not been extensively covered. Ice crystallization during freezing causes dehydration of caseins and the formation of concentration gradients within the cheese matrix, causing undesirable changes in texture-functional attributes, but findings vary due to experimental conditions. A suitable combination of sample size, freezing rate, aging, and tempering can extend the shelf life of high- and low-moisture Mozzarella cheese. However, limited studies on other cheeses suggest that effects and suitability differ by cheese type, in most cases adversely affecting texture and functional attributes. This review presents an overview of the understanding of the effects of refrigeration, freezing techniques, and frozen storage on structural components of cheese, most prominently Mozzarella cheese, and the corresponding impact on microstructure and functionality. Also included are the mechanism of ice formation and relevant mathematical models for estimation of the thermophysical properties of cheese to assist in designing optimized schemes for their frozen storage. The review also highlights the lack of unanimity in critical understanding concerning the effect of freezing on the long-term storage of Mozzarella cheese with respect to its functionality.

Investigating Structural Defects in Extra Hard Cheese Produced from Low-Temperature Centrifugation of Milk

The present study investigated some physico-chemical and microbiological traits of 20-month ripened hard cheeses produced from low-temperature high-speed centrifuged raw milk that developed a structural defect consisting of eyes or slits in the paste. Cheeses obtained using the same process and that did not develop the defect were used as controls. The colour, texture, moisture, water activity, proton molecular mobility, microstructure, extent of proteolysis, and viable microorganisms have been evaluated in all the cheese samples, and the significant differences between the defective and non-defective cheeses have been critically discussed. At a microstructural level, the defects caused fat coalescence and an unevenly organised protein matrix with small cracks in the proximity of the openings. The different fat organisation was correlated to a different transverse relaxation time of 1H population relaxing at higher times. The textural and colour features were not different from those of the control cheeses and were comparable with those reported in the literature for other long-ripened hard cheeses. On the other hand, the defective cheeses showed a higher moisture level and lower lactobacilli and total mesophilic bacteria concentrations, but the microbial origin of the defect remains an open hypothesis that deserves further investigation.

Rapid Identification of Adulteration in Edible Vegetable Oils Based on Low-Field Nuclear Magnetic Resonance Relaxation Fingerprints

Most current approaches applied for the essential identification of adulteration in edible vegetable oils are of limited practical benefit because they require long analysis times, professional training, and costly instrumentation. The present work addresses this issue by developing a novel simple, accurate, and rapid identification approach based on the magnetic resonance relaxation fingerprints obtained from low-field nuclear magnetic resonance spectroscopy measurements of edible vegetable oils. The relaxation fingerprints obtained for six types of edible vegetable oil, including flaxseed oil, olive oil, soybean oil, corn oil, peanut oil, and sunflower oil, are demonstrated to have sufficiently unique characteristics to enable the identification of the individual types of oil in a sample. By using principal component analysis, three characteristic regions in the fingerprints were screened out to create a novel three-dimensional characteristic coordination system for oil discrimination and adulteration identification. Univariate analysis and partial least squares regression were used to successfully quantify the oil adulteration in adulterated binary oil samples, indicating the great potential of the present approach on both identification and quantification of edible oil adulteration.

Spotting Frozen Curd in PDO Buffalo Mozzarella Cheese Through Insights on Its Supramolecular Structure Acquired by 1H TD-NMR Relaxation Experiments

The addition of frozen curd (FC) during the production process of “Mozzarella di Bufala Campana”, an Italian cheese with Protected Designation of Origin (PDO), is a common fraud not involving modifications of the chemical composition in the final product. Its detection cannot thus be easily obtained by common analytical methods, which are targeted at changes in concentrations of diagnostic chemical species. In this work, the possibility of spotting this fraud by focusing on the modifications of the supramolecular structure of the food matrix, detected by time domain nuclear magnetic resonance (TD-NMR) experiments, was investigated. Cheese samples were manufactured in triplicate, according to the PDO disciplinary of production, except for using variable amounts of FC (i.e., 0, 15, 30, and 50% w/w). Relaxation data were analysed through different approaches: (i) Discrete multi-exponential fitting, (ii) continuous Laplace inverse fitting, and (iii) chemometrics approach. The strategy that lead to best detection results was the chemometrics analysis of raw Carr-Purcell-Meiboom-Gill (CPMG) decays, allowing to discriminate between compliant and adulterated samples, with as low as 15% of FC addition. The strategy is based on the use of machine learning for projection on latent structures of raw CPMG data and classification tasks for fraud detection, using quadratic discriminant analysis. By coupling TD-NMR raw decays with machine learning, this work opens the way to set up a system for detecting common food frauds modifying the matrix structure, for which no official authentication methods are yet available.

Seasonal variations in the functional performance of industrial low-moisture part-skim mozzarella over a 1.5-year period

Seventy-five blocks of low-moisture part-skim mozzarella cheese were procured from an industrial cheese plant, and the relationships between the physicochemical and functional properties were evaluated during refrigerated storage. In total, cheeses were obtained from 1 cheese vat on 7 different production dates, at 2 to 4 monthly intervals, over a 1.5-yr period; all cheeses were made using a standard recipe. The cheeses were held at 4°C for 0, 1, 2, 4, 8, 16, or 32 d and assayed for composition, primary proteolysis, serum distribution, texture profile analysis, heat-induced changes in viscoelastic behavior, cheese extensibility, and melt characteristics. The results demonstrated a substantial increase in serum uptake by the calcium-phosphate para-casein matrix between 1 and 16 d of storage with a concomitant improvement in the functional performance of the cheese. Extending the storage time to 32 d resulted in further changes in the functional quality, concurrent with ongoing increases in protein hydration and primary proteolysis. Differences in the measured characteristics between the cheeses obtained on different sampling occasions were evident. Principal component analysis separated the cheeses based on their variance in functional performance, which was found to be correlated mainly with the calcium content of the cheese. The results indicate that the manufacturing process should be tightly controlled to minimize variation in calcium content and enhance the quality consistency of the cheese.