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Element concentrations of 56 poultry meat and 53 dried beef samples were determined and statistically analyzed using analysis of variance and linear discriminant analysis (LDA) to identify the single or combination of elements with the highest potential to determine the geographic origin. In order to validate the applicability of this technique, the results were additionally combined with data from an earlier assessment including 25 poultry meat and 23 dried beef samples. Validation was performed by estimating the origin of the first samples based on the data of the second, larger, dataset. Elements significantly discriminating among countries were As, Na, Rb, Se, Sr, and Tl for poultry meat and As, B, Ba, Ca, Cd, Cu, Dy, Er, Fe, Li, Mn, Pd, Rb, Se, Sr, Te, Tl, U, and V for dried beef out of about 50 elements each. The LDA gave mean correct classification rates of 77 and 79% for poultry meat and dried beef, respectively. Validation allowed identifying some, but not all, origins. For a higher discriminative power, this method should be combined with other ways of authentication

In order to determine the geographic origin of poultry and dried beef, concentrations of a total of 72 different elements (occasionally represented with several isotopes) were analyzed by inductively coupled plasma high resolution mass spectrometry (ICP-HRMS). Additionally, gross chemical composition (GCC) was analyzed. The 25 poultry breast filets samples originated from Switzerland, France, Germany, Hungary, Brazil, and Thailand, and the 23 dried beef samples, made from M. biceps femoris and M. semitendinosus, were produced in Switzerland, Austria, Australia, United States, and Canada out of raw meat originating either from these or from other countries. A total of 66 and 46 of the elements and isotopes followed were detected in beef and poultry, respectively. For statistical analyses, only the most abundant isotopes per element were used. For both poultry meat and dried beef, a differentiation of the origins was possible using those elements, which were significantly different across countries (As, Na, Rb, and Tl in poultry; B, Ca, Cd, Cu, Dy, Eu, Ga, Li, Ni, Pd, Rb, Sr, Te, Tl, Tm, V, Yb, and Zn in beef). No sufficient differentiation between origins was possible with GCC. Further studies have to confirm the suitability of this approach for meat authentication with more samples

Fourier transform infrared spectroscopy (FT-IR) was used to determine 20 different measurands in honey. The reference values for 144 honey samples of different botanical origin were determined by classical physical and chemical methods. Partial least squares regression was used to develop the calibration models for the measurands studied. They were validated using independent samples and proved satisfying accuracies for the determination of water (R 2=0.99), glucose (0.94), fructose (0.84), sucrose (0.91), melezitose (0.98) and monosaccharide content (0.82) as well as fructose/glucose ratio (0.98), glucose/water ratio (0.94), electrical conductivity (0.98), pH-value (0.87) and free acidity (0.96). The prediction accuracy for hydroxymethylfurfural, proline and the minor sugars maltose, turanose, erlose, trehalose, isomaltose and kojibiose was rather poor. The results demonstrate that mid-infrared spectrometry is a valuable, rapid and non-destructive tool for the quantitative analysis of the most important measurands in honey

Emmentaler is a hard cheese produced and consumed in many countries. The authenticity of this cheese variety is becoming a matter of national importance with the imminent opening of the cheese market in Switzerland and the introduction of the PDO label for the Emmentaler Switzerland™. This paper is the first in a series reporting the search for parameters that make possible a geographic discrimination of Emmentalers. Twenty Emmentaler cheese samples from six regions in Europe (one from Switzerland, two from France, one from Austria, one from Germany and one from Finland) were considered. In this paper, chemical, biochemical, microbiological, colour and sensory parameters were investigated leading to the following preliminary results. The presence of Lb. helveticus seemed to be a good indicator of an origin other than Swiss. The concentration of enterococci, facultative and obligate heterofermentative lactobacilli and salt tolerant bacteria was significantly lower in Emmentaler Switzerland™ than in the foreign cheeses. Chemical parameters such as fat content and pH value as well as biochemical parameters such as L- and D-lactate and pyruvate allowed us to partially discriminate between the regions when these data were combined by principal component analysis. The colour of the body also showed significant differences.

Electronic noses produce data which are difficult to transfer between identical instruments because of differences in the characteristics of "identical" instruments and because of sensor drift. The transportability of data is, however, essential for the setting up of databanks. Results of the present investigation, using processed cheeses and evaporated milk as reference materials, show that data transfer between two electronic noses based on mass spectrometry is possible and simple.

The goal of this work was to classify European Emmental cheeses according to their geographic origin using analytical approaches. Twenty-five analytical parameters (factors) were measured in 183 samples. Results were combined by multivariate statistical analysis. Discriminant analysis (DA) and an artificial neural network (ANN) delivered similar results when all regions and factors were included; 95% and 91%, respectively, of the samples were correctly classified in the validation procedure. To reduce the analytical costs and the risk of overfitting, a DA based on a selection of only 11 factors was calculated. In this case, the Jackknifed validation delivered 95% correct assignments. Finally, a system was optimised to discriminate between the Swiss samples and cheeses from other regions. Building a new model for each of the six pairs, Switzerland vs. another region, 100% correct classification could be achieved for the Swiss samples.