Near-infrared hyperspectral image analysis for monitoring the cheese-ripening process

Ripening is the most crucial process step in cheese manufacturing and constitutes multiple biochemical alterations that describe the final cheese quality and its perceived sensory attributes. The assessment of the cheese-ripening process is challenging and requires the effective analysis of a multitude of biochemical changes occurring during the process. This study monitored the biochemical and sensory attribute changes of paraffin wax-covered long-ripening hard cheeses (n = 79) during ripening by collecting samples at different stages of ripening. Near-infrared hyperspectral (NIR-HS) imaging, together with free amino acid, chemical composition, and sensory attributes, was studied to monitor the biochemical changes during the ripening process. Orthogonal projection-based multivariate calibration methods were used to characterize ripening-related and orthogonal components as well as the distribution map of chemical components. The results approve the NIR-HS imaging as a rapid tool for monitoring cheese maturity during ripening. Moreover, the pixelwise evaluation of images shows the homogeneity of cheese maturation at different stages of ripening. Among the chemical compositions, fat content and moisture are the most important variables correlating to NIR-HS images during the ripening process.

Effects of Dietary Omega-3 Enrichment on the Chemical Composition and the Pathogenic Microbiota of Ovine Milk

The demand for ovine milk and ovine dairy products is constantly increasing due to their exceptional sensorial characteristics and their health benefits for consumers. However, dairy fat content and composition are of particular concern for consumers as well as the medical community, as there are risk factors for coronary disease, diabetes mellitus, cancer, and other serious diseases. For this reason, attempts have been made to control/regulate the fat composition of ovine milk by modifying sheep dietary intake of polyunsaturated fatty acids. In this experimental trial, a group of sheep were fed for 30 days a diet enriched in flaxseeds and lupines, feed ingredients rich in omega-3 fatty acids, aiming to investigate the effects on fat composition and the microbiota of ovine milk. Chemical analysis of the collected milk showed that the omega-3 and omega-6 content was increased. On the opposite, the atherogenic and thrombogenic indexes decreased. Of importance was the semi-protective effect on the udder by the increased omega-3 dietary intake, as depicted by its impact on the biodiversity of the pathogenic microbiota. These findings suggest that ovine milk could be modified under specific conditions to be more appropriate for the consumption by people belonging to high-risk groups for various diseases.

Impact of an Omega-3-Enriched Sheep Diet on the Microbiota and Chemical Composition of Kefalograviera Cheese

Kefalograviera is a well-known hard Greek cheese. The aim of this study was to determine how milk produced from ewes fed omega-3-enriched diets could influence the microbiota as well as the chemical composition of Kefalograviera cheese. At the start of the trial, 30 dairy ewes (Lesvos and Chios crossbreed) were selected and fed a conventional diet, based on alfalfa hay, straw and concentrate feed that contained soybean meal for a period of thirty days. Then, for a period of sixty days the same ewes were fed an omega-3-enriched concentrate feed with a lower level of soybean meal that contained 10% flaxseed and 10% lupins. Milk yield was collected individually on Days 30, 60 and 90 and used to produce three different batches of Kefalograviera cheeses, at the same cheese factory, by using a traditional recipe and identical preparation conditions (pasteurization of milk, salt, rennet and culture). Sample analysis was done after six months of Kefalograviera cheese ripening. MALDI-TOF-MS (matrix-assisted laser desorption/ionization time of flight mass spectrometry) identification was performed by contrasting the samples’ mass spectra with the corresponding reference database. The correlation between the different Kefalograviera cheeses revealed the predominant species being Lactococcus lactis, Lactobacillus rhamnosus, Lactobacillus plantarum, Lactobacillus brevis, Lactobacillus paracasei, Enterococcus faecium and Enterococcus faecalis, with significant quantitative differences between the experimental groups and the controls. Pediococcus spp. was isolated only from the experimental groups’ cheeses and Staphylococcus spp. only from the controls’ cheese, suggesting—among other differences—a bacterial microbiota distinction between the groups. Moreover, increased levels of alpha-linolenic acid and total polyunsaturated omega-3 fatty acids were noted in the enriched Kefalograviera cheeses. These promising findings suggest that enriched Kefalograviera cheese could be manufactured via enriching the ewes’ diets, with potential benefits for the consumers’ health.

Near- and mid-infrared determination of some quality parameters of cheese manufactured from the mixture of different milk species

This study aimed to evaluate the performance of both near-infrared (NIR) diffuse reflectance and mid-infrared-attenuated total reflectance (MIR-ATR) in determining some quality parameters of a commercial white cheese made of unknown ratios of various milk species. For this purpose, 81 commercial Ezine cheese samples, a special ripened cheese produced in Turkey, containing unknown ratios of bovine, caprine, and ovine milk, were used. Reference analyses, including textural properties, protein content, nitrogen fractions, ripening index coefficients, fat, salt, dry matter-moisture, and ash contents as well as pH and titratable acidity levels, were conducted in the samples following the traditional gold standards. For NIR applications, the spectra of both intact cubes and hand-crushed cheese samples were collected, whereas the spectra of only hand-crushed cheese samples were collected for MIR-ATR. PLSR (Partial Least Squares Regression) calibration models were developed for each parameter (n = 61) and then validated using both cross-validation (leave-one-out approach) and an external validation set (n = 20). Overall, PLSR models developed for total protein, fat, salt, dry matter, moisture, and ash content, as well as pH and titratable acidity, yielded satisfactory performance statistics in the complementary use of NIR and MIR spectroscopy. However, PLSR models of the other parameters, including textural properties, nitrogen fractions, and the ripening index, could only separate high and low values and were not able to make accurate quantitative predictions. NIR spectroscopy was found to be more accurate than that of MIR-ATR spectroscopy for almost all the parameters except for pH and titratable acidity, for which MIR-ATR spectroscopy was superior.

An in-depth study of cheese ripening by means of NIR hyperspectral imaging: Spatial mapping of dehydration, proteolysis and lipolysis

Cheese represents one of the most complex food matrices, for the high number of factors contributing to the chemical composition, and so its evaluation represents an important analytical challenge. The present study describes an innovative and non-destructive analytical approach, based on hyperspectral imaging in the near-infrared region (HSI-NIR) and multivariate pattern recognition, to study and monitor the extent - spatial and temporal - of biochemical phenomena responsible for cheese ripening. NIR spectral bands characterising dehydration, proteolysis and lipolysis were individuated and studied by exploiting a representative sample set of characteristic cheeses. The information obtained was employed to develop score maps based on principal component analysis (PCA), which permitted to monitor and visualise the ripening of Formaggetta, a commercial semi-hard cheese typical of Liguria, an Italian region, providing a deep understanding of the evolution of dehydration, proteolysis and lipolysis during the maturation period that precedes the placing on the market.

The recent advances of near-infrared spectroscopy in dairy production-a review

One of the major issues confronting the dairy industry is the efficient evaluation of the quality of feed, milk and dairy products. Over the years, the use of rapid analytical methods in the dairy industry has become imperative. This is because of the documented evidence of adulteration, microbial contamination and the influence of feed on the quality of milk and dairy products. Because of the delays involved in the use of wet chemistry methods during the evaluation of these products, rapid analytical techniques such as near-infrared spectroscopy (NIRS) has gained prominence and proven to be an efficient tool, providing instant results. The technique is rapid, nondestructive, precise and cost-effective, compared with other laboratory techniques. Handheld NIRS devices are easily used on the farm to perform quality control measures on an incoming feed from suppliers, during feed preparation, milking and processing of cheese, butter and yoghurt. This ensures that quality feed, milk and other dairy products are obtained. This review considers research articles published in reputable journals which explored the possible application of NIRS in the dairy industry. Emphasis was on what quality parameters were easily measured with NIRS, and the limitations in some instances.