Authentication of retail cheeses based on fatty acid composition and multivariate data analysis

How Chemometrics Can Fight Milk Adulteration

Adulteration and fraud are amongst the wrong practices followed nowadays due to the attitude of some people to gain more money or their tendency to mislead consumers. Obviously, the industry follows stringent controls and methodologies in order to protect consumers as well as the origin of the food products, and investment in these technologies is highly critical. In this context, chemometric techniques proved to be very efficient in detecting and even quantifying the number of substances used as adulterants. The extraction of relevant information from different kinds of data is a crucial feature to achieve this aim. However, these techniques are not always used properly. In fact, training is important along with investment in these technologies in order to cope effectively and not only reduce fraud but also advertise the geographical origin of the various food and drink products. The aim of this paper is to present an overview of the different chemometric techniques (from clustering to classification and regression applied to several analytical data) along with spectroscopy, chromatography, electrochemical sensors, and other on-site detection devices in the battle against milk adulteration. Moreover, the steps which should be followed to develop a chemometric model to face adulteration issues are carefully presented with the required critical discussion.

Chemical and fatty acid composition of Manchego type and Panela cheeses manufactured from either hair sheep milk or cow milk

This study compared the chemical composition and fatty acid (FA) profile of Manchego type cheese and Panela cheese made from hair sheep milk and compared these with both types of cheese manufactured with cow milk as a reference. In addition, this study aimed to determine differences in sensory characteristics between Manchego type cheeses manufactured with either hair sheep milk or cow milk. A total of 25 and 14 Manchego type cheeses from hair sheep milk and cow milk were manufactured, respectively. In addition, 30 and 15 Panela cheeses from hair sheep milk and cow milk were manufactured, respectively. The chemical composition and FA profile were determined in all cheeses. In addition, a sensory analysis was performed in Manchego type cheeses manufactured from either hair sheep milk or cow milk. Moisture content was lower in Manchego type cheeses (37.5 ± 1.26 and 37.5 ± 1.26 g/100 g in cheeses manufactured from hair sheep milk and cow milk, respectively) than in Panela cheeses (54.0 ± 1.26 and 56.1 ± 1.26 g/100 g in cheeses manufactured from hair sheep milk and cow milk, respectively). Ash, protein, and sodium contents were higher in Manchego type cheeses than in Panela cheeses. Manchego type cheese manufactured from hair sheep milk contained more C4:0, C6:0, C8:0, C10:0, C12:0, C14:0, C18:2 cis-9,cis-12, total saturated FA, total short-chain FA, total medium-chain FA, total polyunsaturated FA, and de novo FA than Manchego type cheeses from cow milk. Total content of short-chain FA was higher in hair sheep cheeses (24.4 ± 1.30 and 19.6 ± 1.30 g/100 g in Manchego type and Panela cheeses, respectively) than in cow cheeses (8.89 ± 1.30 and 8.26 ± 1.30 g/100 g in Manchego type and Panela cheeses, respectively). Manchego type cheeses from hair sheep milk obtained higher scores for odor (7.05), texture (6.82), flavor (7.16), and overall acceptance (7.16) compared with those made from cow milk (6.37, 6.12, 6.17, and 6.83, respectively). In conclusion, both Manchego type cheese and Panela cheese manufactured with hair sheep milk had a similar chemical composition and contained higher levels of short-chain FA, total polyunsaturated FA, and de novo FA than those manufactured with cow milk.

Geographical Discrimination of Croatian Wines by Stable Isotope Ratios and Multielemental Composition Analysis

The δ¹⁸O and δ¹³C (analyzed by isotope ratio mass spectrometry, IRMS) and concentration of 22 selected elements (analyzed by inductively coupled plasma—optical emission spectrometry, ICP-OES) in 190 Croatian microvinified and commercial wine samples from continental and coastal winegrowing areas and from three viticultural zones (B, CI, and CII) were measured to investigate whether multivariate statistical methods could provide the fingerprint for geographical origin determination. The highest power for discrimination of wines produced in Croatian winegrowing areas was achieved by general discriminant analysis (GDA) showing correct classification of 97.9% of all investigated samples, 100.0% of microvinified samples and 84.8% of commercial samples in the cross-validation matrix. The most significant markers for discrimination of coastal and continental areas found by GDA were δ¹⁸O and Co, followed by K, Rb, Sn, Li, and δ¹³C in descending order. GDA showed higher levels of correctly classified samples from three viticultural zones in Croatia if only microvinified samples were employed in the analysis (94.9%) than for all samples together (86.3%) or for commercial samples (66.1%) in the cross-validation matrix. The discrimination of viticultural zones B, CI, and CII in Croatia was achieved by δ¹⁸O, Co, Rb, Li, K, and Sn. The results obtained showed that the relationships between the isotopic ratios and concentrations of different considered elements combined with appropriate statistical model represent a powerful tool in discrimination of wines produced in different Croatian winegrowing areas.

Physicochemical, Spectroscopic, and Chromatographic Analyses in Combination with Chemometrics for the Discrimination of the Geographical Origin of Greek Graviera Cheeses

Seventy-eight graviera cheese samples produced in five different regions of Greece were characterized and discriminated according to geographical origin. For the above purpose, pH, titratable acidity (TA), NaCl, proteins, fat on a dry weight basis, ash, fatty acid composition, volatile compounds, and minerals were determined. Both multivariate analysis of variance (MANOVA) and linear discriminant analysis (LDA) were applied to experimental data to achieve sample geographical discrimination. The results showed that the combination of fatty acid composition plus minerals provided a correct classification rate of 89.7%. The value for the combination of fatty acid compositions plus conventional quality parameters was 94.9% and for the combination of minerals plus conventional quality parameters was 97.4%. When cheeses of the above five geographical origins were combined with previously studied graviera cheeses from six other geographical origins collected during the same seasons in Greece, the respective values for the discrimination of geographical origin of all eleven origins were 89.3% for conventional quality parameters plus minerals; 94.0% for conventional quality parameters plus fatty acids; 94.1% for minerals plus fatty acids; and 95.2% for conventional quality parameters plus minerals plus fatty acids. Such high correct classification rates demonstrate the robustness of the developed statistical model.

Chemometric Analysis of Fatty Acids Profile of Ripening Chesses

The number of different types of cheese worldwide exceeds 4000 and dairy fat, composed of about 400 fatty acids (FA), is one of the most complex dietary fats. Cheeses are valuable sources of different bioactive FA, i.e., conjugated FA (CFA). The aim of present study was to determine FA profile of commercially available ripening cheeses, with the special emphasis on CFA profile. Multivariate analyses (cluster analysis (CA), principal component Analysis (PCA), and linear discriminant analysis (LDA)) of chromatographic data have been proposed as an objective approach for evaluation and data interpretation. CA enabled the differentiation of ripening cheeses from fresh cheeses and processed cheeses. PCA allowed to differentiate some types of ripening cheese whereas proposed LDA model, based on 22 analyzed FA, enabled assessing cheeses type with average predictive sensitivities of 86.5%. Results of present study clearly demonstrated that FA and CFA content may not only contribute to overall nutritional characteristics of cheese but also, when coupled with chemometric techniques, may be used as chemical biomarkers for assessing the origin and/or the type of ripening cheeses and the confirmation of their authenticity, which is of utmost importance for consumers.