Authenticity and Typicity of Traditional Cheeses: A Review on Geographical Origin Authentication Methods

Recent insights on the multifaceted roles of wooden tools in cheese-making: A review of their impacts on safety and final traits of traditional cheeses

The present review provides an overview of the role of wooden tools in cheese-making production, with a particular focus on their impact on the authenticity and biodiversity of typical and traditional cheeses. Specifically, wooden tools (such as vats, shelves, or tables) are thought to be important in the production of traditional cheese and cannot be replaced with substitute materials like plastic or stainless steel without changing the final characteristics of the cheeses. Despite the rigorous hygienic regulations, wooden tools are still indispensable in many areas and required for some Protected Designation of Origin (PDO) cheeses. These wooden tools promote the growth of biofilms, which are primarily made up of pro-technological microorganisms and add to the unique sensory qualities of traditional cheeses. They also improve product safety by acting as a natural barrier against pathogenic microorganisms. Such wooden tools facilitate the growth of biofilms mainly constituted by pro-technological microorganisms that contribute to the distinctive sensory traits of traditional cheeses and enhance the safety of final products by providing a natural barrier against pathogenic microorganisms. Recently, several studies have focused on wooden-associated biofilms with the final aim to optimize their structure, enhance their robustness, and explore the dynamics of microbial communities between wood and cheese in the most relevant production steps to further improve both the safety and quality of traditional-type cheeses.

Constructing an origin discrimination model of japonica rice in Heilongjiang Province based on confocal microscopy Raman spectroscopy technology

An origin discrimination model for rice from five production regions in Heilongjiang Province was constructed based on the combination of confocal microscopy Raman spectroscopy and chemometrics. A total of 150 field rice samples were collected from the Fangzheng, Chahayang, Jiansanjiang, Xiangshui, and Wuchang production areas. The optimal sample processing conditions, instrument parameter settings, and spectrum acquisition techniques were identified by investigating the influencing factor. The Raman spectra of milled rice within the range of 100-3200 cm-1 were selected as the raw data, and the optimal preprocessing method combination consisting of normalization, Savitzky-Golay smoothing, and multivariate scatter correction was identified. Subsequently, the competitive adaptive reweighted sampling and discrete binary particle swarm optimization algorithms were employed to optimize the feature wavelength selection, resulting in the screening of 226 and 1899 feature wavelength variables, respectively. Using the full Raman spectrum data and feature wavelength data as inputs, partial least squares discriminant analysis, support vector machine and extreme learning machine origin discrimination models were constructed. The results indicated that the BPSO-GA-SVM model exhibited the best predictive ability, achieving a testing set accuracy of 86.67%.

Rapid authenticity assessment of PGI Hongyuan yak milk based on SICRIT-QTOF MS

Hongyuan (HY) yaks live in a pollution-free environment, making HY yak milk a green food, but their short milk production period and low milk yield make yak milk precious and expensive. The phenomenon of counterfeiting HY yak milk with ordinary milk from other origins has already occurred, so the authenticity assessment of HY yak milk is necessary. This study developed a rapid soft ionisation by chemical reaction in transfer quadrupole time-of-flight mass spectrometry (SICRIT-QTOF MS) for HY yak milk differences assessment. Principal component analysis and orthogonal least squares discriminant analysis showed differences between HY milk and the other three origins. Twenty-eight differential compounds were screened out by variable importance in projection, fold change, P-value, and database matching. Furthermore, six characteristic compounds (proline, 2-hydroxy-3-methylbutyric acid, and l-isoleucine, etc.) of HY samples were putatively identified. The study demonstrated that SICRIT-QTOF MS has great potential for rapidly distinguishing the milk origin.

Ecological diversity and associated volatilome of typical mountain Caciotta cheese from Italy

Traditional products are particularly appreciated by consumers and among these products, cheese is a major contributor to the Italian mountainous area economics. In this study, shotgun metagenomics and volatilomics were used to understand the biotic and abiotic factors contributing to mountain Caciotta cheese typicity and diversity. Results showed that the origin of cheese played a significant role; however, curd cooking temperature, pH, salt concentration and water activity also had an impact. Viral communities exhibited higher biodiversity and discriminated cheese origins in terms of production farms. Among the most dominant bacteria, Streptococcus thermophilus showed higher intraspecific diversity and closer relationship to production farm when compared to Lactobacillus delbrueckii. However, despite a few cases in which the starter culture was phylogenetically separated from the most dominant strains sequenced in the cheese, starter cultures and dominant cheese strains clustered together suggesting substantial starter colonization in mountain Caciotta cheese. The Caciotta cheese volatilome contained prominent levels of alcohols and ketones, accompanied by lower proportions of terpenes. Volatile profile not only demonstrated a noticeable association with production farm but also significant differences in the relative abundances of enzymes connected to flavor development. Moreover, correlations of different non-homologous isofunctional enzymes highlighted specific contributions to the typical flavor of mountain Caciotta cheese. Overall, this study provides a deeper understanding of the factors shaping typical mountain Caciotta cheese, and the potential of metagenomics for characterizing and potentially authenticating food products.

Microbial screening of animal skin bags used in traditional cheesemaking

Bouhezza is a traditional Algerian cheese produced and ripened in goatskin bags called Djeld. The aim of this study was to characterize the microbial ecosystem from Djeld (fresh and dried Djeld for making Bouhezza cheese) and the changes introduced by Lben microflora during its preparation and to identify its role in cheesemaking and its safety. Two replicates of fresh and dried skin bags (FS and DS) were sampled and analyzed before and after contact with Lben. The microbiological results showed no pathogens. Skins observed before the addition of Lben were less populated 2.86 and 3.20 log CFU cm-2 than skins examined after the addition of Lben (approximately 6.0 log CFU cm-2), suggesting a potential role of Lben in releasing some microorganisms into the skin during its time in the Djeld. However, an increase in mesophilic lactic acid bacteria and yeasts was observed in Lben after different periods of interaction with the skin. PCR-TTGE revealed the predominance of lactic acid bacteria (Lactiplantibacillus plantarum, Limosilactobacillus fermentum, Staphylococcus equorum subsp. linens, Lactococcus cremoris, Streptococcus thermophilus) and a few high-GC-content bacteria (Lacticaseibacillus paracasei, Brevibacterium casei). Transfer of several microbial species was observed between the goatskin bag biofilm and Lben during the overnight interaction. Bands corresponding to Lacticaseibacillus paracasei, Brevibacterium casei, and Lactobacillus delbrueckii subsp. lactis were detected in the fresh skin profile and in Lben after contact with the fresh skin. Lacticaseibacillus paracasei was found in dried skin and Lben after contact with dry skin. Lactobacillus helveticus and Enterococcus faecalis appeared in the Lben profile and persisted in Lben and the biofilm-covered dry skin after interaction. These results demonstrate an exchange of specific microbial populations between goatskin bag biofilm and Lben during the traditional preparation method, suggesting that the diversity of goatskin biofilm contributes to the microbial diversity of Lben used in the production of Bouhezza cheese.

Discriminative power of DNA-based, volatilome, near infrared spectroscopy, elements and stable isotopes methods for the origin authentication of typical Italian mountain cheese using sPLS-DA modeling

Origin authentication methods are pivotal in counteracting frauds and provide evidence for certification systems. For these reasons, geographical origin authentication methods are used to ensure product origin. This study focused on the origin authentication (i.e. at the producer level) of a typical mountain cheese origin using various approaches, including shotgun metagenomics, volatilome, near infrared spectroscopy, stable isotopes, and elemental analyses. DNA-based analysis revealed that viral communities achieved a higher classification accuracy rate (97.4 ± 2.6 %) than bacterial communities (96.1 ± 4.0 %). Non-starter lactic acid bacteria and phages specific to each origin were identified. Volatile organic compounds exhibited potential clusters according to cheese origin, with a classification accuracy rate of 90.0 ± 11.1 %. Near-infrared spectroscopy showed lower discriminative power for cheese authentication, yielding only a 76.0 ± 31.6 % classification accuracy rate. Model performances were influenced by specific regions of the infrared spectrum, possibly associated with fat content, lipid profile and protein characteristics. Furthermore, we analyzed the elemental composition of mountain Caciotta cheese and identified significant differences in elements related to dairy equipment, macronutrients, and rare earth elements among different origins. The combination of elements and isotopes showed a decrease in authentication performance (97.0 ± 3.1 %) compared to the original element models, which were found to achieve the best classification accuracy rate (99.0 ± 0.01 %). Overall, our findings emphasize the potential of multi-omics techniques in cheese origin authentication and highlight the complexity of factors influencing cheese composition and hence typicity.

Proteomics Parameters for Assessing Authenticity of Grated Grana Padano PDO Cheese: Results from a Three-Year Survey

Assessing the authenticity of PDO cheeses is an important task because it allows consumer expectations to be fulfilled and guarantees fair competition for manufacturers. A 3-year survey was carried out, analyzing 271 samples of grated Grana Padano (GP) PDO cheese collected on the European market. Previously developed analytical methods based on proteomics approaches were adopted to evaluate the compliance of market samples with selected legal requirements provided by the specification for this cheese. Proteolysis follows highly repeatable pathways in GP cheese due to the usage of raw milk, natural whey starter, and consistent manufacturing and ripening conditions. From selected casein breakdown products, it is possible to calculate the actual cheese age (should be >9 months) and detect the presence of excess rind (should be <18%). Furthermore, due to the characteristic pattern of free amino acids established for GP, distinguishing it from closely related cheese varieties is feasible. Cheese age ranged from 9 to 25 months and was correctly claimed on the label. Based on the amino acid pattern, three samples probably contained defective cheese and there was only one imitation cheese. Few samples (9%) were proven to contain some excess rind. Overall, this survey highlighted that the adopted control parameters can assure the quality of grated GP.

Assessment of cheese frauds, and relevant detection methods: A systematic review

Dairy products are widely consumed in the world due to their nutritional and functional characteristics. This group of food products are consumed by all age groups due to their health-giving properties. One of these products is cheese which has a high price compared to other dairy products. Because of this, it can be prone to fraud all over the world. Fraud in food products threatens the world's food safety and can cause serious damage to human health. There are many concerns among food authorities in the world about the fraud of food products. FDA, WHO, and the European Commission provide different legislations and definitions for fraud. The purpose of this review is to identify the most susceptible cheese type for fraud and effective methods for evaluating fraud in all types of cheeses. For this, we examined the Web of Science, Scopus, PubMed, and ScienceDirect databases. Mozzarella cheese had the largest share among all cheeses in terms of adulteration due to its many uses. Also, the methods used to evaluate different types of cheese frauds were PCR, Spectrometry, stable isotope, image analysis, electrophoretic, ELISA, sensors, sensory analysis, near-infrared and NMR. The methods that were most used in detecting fraud were PCR and spectrometry methods. Also, the least used method was sensory evaluation.

Preliminary Feasibility of Near-Infrared Spectroscopy to Authenticate Grazing in Dairy Goats through Milk and Faeces Analysis

Consumers are increasingly prone to request information about the production systems of the food they buy. For this purpose, certification and authentication methodologies are necessary not only to protect the choices of consumers, but also to protect producers and production systems. The objective of this preliminary work was to authenticate the grazing system of dairy goats using Near-Infrared Spectroscopy (NIRS) analyses of milk and faeces of the animals. Spectral information and several mathematical pre-treatments were used for the development of six discriminant models based on different algorithms for milk and faeces samples. Results showed that the NIRS spectra of both types of samples had some differences when the two feeding regimes were compared. Therefore, good discrimination rates were obtained with both strategies (faeces and milk samples), with classification percentages of up to 100% effectiveness. Discrimination of feeding regime and grazing authentication based on NIRS analysis of milk samples and an alternative sample such as faeces is considered as a potential approach for dairy goats and small ruminant production.

A Comparative Analysis on the Environmental Impact of Selected Methods for Determining the Profile of Fatty Acids in Cheese

The fatty acid profile of cheese influences its sensory parameters, such as color, texture, or flavor. Examining the fatty acid profile also helps to assess the nutritional value of the cheese that is being tested. However, the determination of fatty acids in cheese samples is a multi-stage and time-consuming task. In addition, large amounts of toxic organic solvents are used to prepare samples for analysis purposes. This paper presents the results of a study to determine the fatty acid profile of yellow cheese samples. Six different methods of sample preparation were compared for analysis purposes. The profile of fatty acids was determined using gas chromatography with flame ionization detection (GC-FID). The study showed significant differences (p > 0.05) in the resulting fatty acid profile between the methods used. It was found that the most reliable fatty acid profile results were obtained using methods derived from the Folch method. In addition, tools such as the Analytical Eco-Scale tool and the Analytical Greenness Metric for Sample Preparation (AGREEprep) tool were used to assess the greenness of the methods used. In the case of the Analytical Eco-Scale tool, all six methods scored 'acceptable green analysis' with scores ranging from 61 to 73. However, an evaluation of methods using the AGREEprep metric showed that the results of the methods (0.13-0.27) did not show the "greenness" of the analytical methods.

Rapid Food Authentication Using a Portable Laser-Induced Breakdown Spectroscopy System

Laser-induced breakdown spectroscopy (LIBS) is an atomic-emission spectroscopy technique that employs a focused laser beam to produce microplasma. Although LIBS was designed for applications in the field of materials science, it has lately been proposed as a method for the compositional analysis of agricultural goods. We deployed commercial handheld LIBS equipment to illustrate the performance of this promising optical technology in the context of food authentication, as the growing incidence of food fraud necessitates the development of novel portable methods for detection. We focused on regional agricultural commodities such as European Alpine-style cheeses, coffee, spices, balsamic vinegar, and vanilla extracts. Liquid examples, including seven balsamic vinegar products and six representatives of vanilla extract, were measured on a nitrocellulose membrane. No sample preparation was required for solid foods, which consisted of seven brands of coffee beans, sixteen varieties of Alpine-style cheeses, and eight different spices. The pre-processed and standardized LIBS spectra were used to train and test the elastic net-regularized multinomial classifier. The performance of the portable and benchtop LIBS systems was compared and described. The results indicate that field-deployable, portable LIBS devices provide a robust, accurate, and simple-to-use platform for agricultural product verification that requires minimal sample preparation, if any.