Cheese is a dairy product with potential health benefits. Cheese consumption has increased due to the significant diversity of varieties, versatility of product presentation, and changes in consumers’ lifestyles. Spoilage of hard and semi-hard cheeses can be promoted by their maturation period and/or by their long shelf-life. Therefore, preservation studies play a fundamental role in maintaining and/or increasing their shelf-life, and are of significant importance for the dairy sector. The aim of this review is to discuss the most effective methods to ensure the safety and sensory quality of ripened cheeses. We review traditional methods, such as freezing, and modern and innovative technologies, such as high hydrostatic pressures, chemical and natural vegetable origin preservatives, vacuum and modified atmosphere packaging, edible coatings and films, and other technologies applied at the end of storage and marketing stages, including light pulses and irradiation. For each technology, the main advantages and limitations for industrial application in the dairy sector are discussed. Each type of cheese requires a specific preservation treatment and optimal application conditions to ensure cheese quality and safety during storage. The environmental impact of the preservation technologies and their contribution to the sustainability of the food chain are discussed.

A handheld near infrared (NIR) spectrometer was used for on-site determination of the fatty acids (FAs) composition of industrial fish oils from fish by-products. Partial least square regression (PLSR) models were developed to correlate NIR spectra with the percentage of saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), polyunsaturated fatty acids (PUFAs) and, among them, omega-3 (ω-3) and omega-6 (ω-6) FAs. In a first step, the data were divided into calibration validation datasets, obtaining good results regarding R² values, root mean square error of prediction (RMSEP) and bias. In a second step, all these data were used to create a new calibration, which was uploaded to the handheld device and tested with an external validation set in real time. Evaluation of the external test set for SFAs, MUFAs, PUFAs and ω-3 models showed promising results, with R² values of 0.98, 0.97, 0.97 and 0.99; RMSEP (%) of 0.94, 1.71, 1.11 and 0.98; and bias (%) values of −0.78, −0.12, −0.80 and −0.67, respectively. However, although ω-6 models achieved a good R² value (0.95), the obtained RMSEP was considered high (2.08%), and the bias was not acceptable (−1.76%). This was corrected by applying bias and slope correction (BSC), obtaining acceptable values of R² (0.95), RMSEP (1.09%) and bias (−0.05%). This work goes a step further in the technology readiness level (TRL) of handheld NIR sensor solutions for the fish by-product recovery industry.

The performances of three non-destructive sensors, based on different principles, bioelectrical impedance analysis (BIA), near-infrared spectroscopy (NIR) and time domain reflectometry (TDR), were studied to discriminate between unfrozen and frozen-thawed fish. Bigeye tuna (Thunnus obesus) was selected as a model to evaluate these technologies. The addition of water and additives is usual in the fish industry, thus, in order to have a wide range of possible commercial conditions, some samples were injected with different water solutions (based on different concentrations of salt, polyphosphates and a protein hydrolysate solution). Three different models, based on partial least squares discriminant analysis (PLS-DA), were developed for each technology. This is a linear classification method that combines the properties of partial least squares (PLS) regression with the classification power of a discriminant technique. The results obtained in the evaluation of the test set were satisfactory for all the sensors, giving NIR the best performance (accuracy = 0.91, error rate = 0.10). Nevertheless, the classification accomplished with BIA and TDR data resulted also satisfactory and almost equally as good, with accuracies of 0.88 and 0.86 and error rates of 0.14 and 0.15, respectively. This work opens new possibilities to discriminate between unfrozen and frozen-thawed fish samples with different non-destructive alternatives, regardless of whether or not they have added water.

Modified atmosphere packaging (MAP) has become a good potential strategy to retain quality throughout the shelf life of perishable foods. The aim of this work was to evaluate different packaging atmospheres on semi-hard protected designation of origin Idiazabal cheese wedges. Six different packaging treatments (air, vacuum, and CO₂/N₂ gas mixtures in the ratio of 20/80, 50/50, 80/20, and 100/0% v/v, respectively) were studied. Changes in gas headspace composition, cheese gross composition, weight loss, pH, acidity, colour, and textural and sensory properties were investigated during 56 days of refrigerated storage at 5 ± 1 °C. MAP was the most effective preserving technique compared to air- and vacuum-packaging treatments. The cheese characteristics with the greatest discriminating weight in the preservation techniques were paste appearance, holes, flavour, a* (redness) and b* (yellowness) colour parameters, and slope to hardness. Air-packaged cheeses, on 35 day, presented a mouldy flavour. Vacuum packaging affected paste appearance (greasy, plastic marks, and non-homogeneous colour) and holes (occluded and unnatural appearance) starting after 14 packaging days. MAP mixtures with CO₂ concentration between 50/50 and 80/20% CO₂/N₂ (v/v) are recommended to ensure sensory quality and stability in the distribution of these raw sheep-milk cheese wedges.