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This study delves into the effectiveness of digital marketing strategies in promoting local agricultural and food products in Romania, certified with European Union quality schemes. By examining consumer profiles, preferences, and their awareness of EU quality labels, the research uncovers the motivations driving purchasing decisions and the influence of digital marketing on these choices. Utilizing quantitative methods, including a comprehensive survey across 903 respondents, the study identifies four distinct consumer segments: Eco-Advocates, Les Connaisseurs, Price-Sensitives, and Traditionalists. These segments exhibit unique behaviors and attitudes toward certified products. The research highlights the potential of digital marketing to significantly alter consumer behavior toward EU-certified products, underscoring the importance of tailored communication strategies. It contributes to the understanding of consumer segmentation in the context of European Union quality schemes, providing valuable insights for policymakers, marketers, and producers. The findings advocate for enhanced digital marketing efforts to increase awareness and appreciation of these certified products, thereby supporting the broader objectives of quality and certification in the European agricultural and food product sector.

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Hongyuan yak milk is a protected geographical indication (PGI) product of rich nutritional value, which is popular among consumers. Stable isotope ratio analysis (SIRA) is an effective way to protect the authenticity of the geographical origin of PGI products, and it is crucial to study the factors affecting stable isotopes. Firstly, we proved that the SIRA could be used to identify the geographical origin of Hongyuan yak milk, and that the identification accuracy in combination with δ13C and δ18O was 100 %. Secondly, we analyzed the effect of sampling selection on the stable isotopes of Hongyuan yak milk in practical applications, which showed that sampling time influenced the δ13C, δ2H, and δ18O, while the sampling locations did not. There were interactions between the effect of sampling time and location on δ2H and δ18O. These results provide a reliable method for identifying PGI products and also provide new guidance on sampling models.

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In August 2020, the Eruca sativa cultivar "Rucola della Piana del Sele" obtained from the European Union the prestigious PGI (protected geographical indication) label, which certifies the uniqueness of its characteristics and increases its prestige both nationally and, above all, internationally. This plant is recognized as a product of excellence, with a unique flavor and unmistakable aroma. Therefore, since there are no methods to characterize the PGI product, a metabolomic approach was applied to characterize E. sativa grown in the Piana del Sele and different geographical areas. As E. sativa has very wide cultivation, this study sought to compare the metabolite profiles of rocket grown in Piana del Sele, Bergamo, and Brescia, as well as in Switzerland, making a comparison also with the metabolite profile of E. sativa grown spontaneously. To determine the best procedure to distinguish "Rucola della Piana del Sele" from the others, different extraction procedures were carried out using different solvents and fresh or freeze-dried plant matrices. The different extracts were analyzed by liquid chromatography coupled with high-resolution mass spectrometry experiments, using chemometric analyses to identify biomarker metabolites that characterize the PGI product. The LC-ESI-Q-Exactive-MS/MS profiles of methanol and hydroalcoholic extracts of different cultivars of E. sativa were found to be rich in bioactive compounds such as glucosinolates, glycosylated flavonoids, fatty acids, and lipids. The LCMS data were analyzed by principal component analysis (PCA); the score scatter plot shows significant separation among Eruca samples grown in different geographical areas. In detail, loading the scatter plot revealed Eruca grown in Piana del Sele to be richer than other cultivars in glycosylated quercetin 3,3',4'-O-triglucoside (7), quercetin-3,4'-O-diglucoside-3'-O-(6-sinapoyl-glucoside) (10), and quercetin diglucoside (30). Finally, considering the biological interest in erucin, the myrosinase product of glucoerucin, the latter was quantified in the extracts by LC-ESI/QTrap/MS/MS using the multiple reaction monitoring (MRM) method; E. sativa from Piana del Sele showed the highest content of glucoerucin.

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This paper presents a method for the protected geographical indication discrimination of Ophiopogon japonicus from Zhejiang and elsewhere using near-infrared (NIR) spectroscopy combined with chemometrics. A total of 3657 Ophiopogon japonicus samples from five major production areas in China were analyzed by NIR spectroscopy, and divided into 2127 from Zhejiang and 1530 from other areas ('non-Zhejiang'). Principal component analysis (PCA) was selected to screen outliers and eliminate them. Monte Carlo cross validation (MCCV) was introduced to divide the training set and test set according to a ratio of 3:7. The raw spectra were preprocessed by nine single and partial combination methods such as the standard normal variable (SNV) and derivative, and then modeled by partial least squares regression (PLSR), a support vector machine (SVM), and soft independent modeling of class analogies (SIMCA). The effects of different pretreatment and chemometrics methods on the model are discussed. The results showed that the three pattern recognition methods were effective in geographical origin tracing, and selecting the appropriate preprocessing method could improve the traceability accuracy. The accuracy of PLSR after the standard normal variable was better, with R2 reaching 0.9979, while that of the second derivative was the lowest with an R2 of 0.9656. After the SNV pretreatment, the accuracy of the training set and test set of SVM reached the highest values, which were 99.73% and 98.40%, respectively. The accuracy of SIMCA pretreated with SNV and MSC was the highest for the origin traceability of Ophiopogon japonicus, which could reach 100%. The distance between the two classification models of SIMCA-SNV and SIMCA-MSC is greater than 3, indicating that the SIMCA model has good performance.

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The cuisine of the Balearic Islands (Spain, southern Europe) has several products of a great tradition, recognized worldwide and covered by European Union quality schemes, such as Protected Designation of Origin (PDO) and Protected Geographical Indication (PGI). Among them, the most emblematic products are sobrasada de Mallorca (a type of raw curated pork meat), ensaimada de Mallorca (pastry product), and Mahón-Menorca cheese (cow's milk cheese). During 4 consecutive years (2018-2021), the presence/absence of Escherichia coli ß-glucuronidase positive (henceforth as E. coli), Listeria monocytogenes, Salmonella spp., and Staphylococcus aureus in these products has been monitored, as well as the total yeast and mold count in ensaimada de Mallorca. The results of the microbiological analysis showed that sobrasada presented similar microbiological patterns to those of other raw curated meat products (some presence of E. coli and L. monocytogenes). Furthermore, the sobrasada de Mallorca made with white pork tended to be positive in E. coli compared to other sobrasada subtypes. In the case of ensaimada, only a reduced number of cases within filled ensaimadas (with higher moisture content) presented unacceptable mold and yeast counts (>500 colony-forming unit [CFU]/g). Finally, the Mahón-Menorca cheese presented a surprising microbiology pattern: higher E. coli contamination in the pasteurized milk cheese compared to its raw counterpart. This pattern was observed for all the years, being statistically significant in 2020. This study has detected good microbiological status in the three traditional products studied. However, worrisome issues in Good Hygienic Practices have been detected for some companies that produce pasteurized milk Mahón-Menorca cheese under the PDO quality label. The companies involved and even the competent authorities should address these problems to correct this deviation in food security.

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For the protection of Protected Geographical Indication (PGI) Sunite lamb, PGI Sunite lamb samples and lamb samples from two other banners in the Inner Mongolia autonomous region were distinguished by stable isotopes (δ13C, δ15N, δ2H, and δ18O) and two local modeling approaches. In terms of the main characteristics and predictive performance, local modeling was better than global modeling. The accuracies of five local models (LDA, RF, SVM, BPNN, and KNN) obtained by the Adaptive Kennard-Stone algorithm were 91.30%, 95.65%, 91.30%, 100%, and 91.30%, respectively. The accuracies of the five local models obtained by an approach of PCA-Full distance based on DD-SIMCA were 91.30%, 91.30%, 91.30%, 100%, and 95.65%, respectively. The accuracies of the five global models were 91.30%, 91.30%, 91.30%, 100%, and 91.30%, respectively. Stable isotope ratio analysis combined with local modeling can be used as an effective indicator for protecting PGI Sunite lamb.

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Food product nutritional and sensory characteristics are often deeply linked to its territory of origin; therefore, its authentication by means of elemental composition becomes crucial for traceability and fighting food fraud. This study aims to establish a fast and reproducible procedure for origin and quality assessment of Sicilian tomato fruits, including PGI "Pomodoro di Pachino", by using the X-ray fluorescence (XRF) technique. Measurements were performed on different parts of PGI Pachino tomatoes belonging to the same production lot. Principal Component and Cluster Analyses show that the samples cluster accordingly with the production lot, disentangling the different parts of the fruit. This procedure, which uses XRF yield elemental pattern and statistical analysis, establishes a solid basis for characterizing elemental profiles by a fast XRF in-situ campaign, supporting the traceability system. The reliability of XRF results was confirmed by comparing elemental concentrations with ICP-MS measurements, performed for comparison, and tomato literature values.

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Paipa cheese is the only Colombian semi-ripened cheese with protected geographical indication. In the current work, the effect of applying starch coatings carrying carvacrol on Paipa cheeses was analyzed. Coatings were prepared based on blends of potato starch (2 g/100 g), carvacrol (0.1 g/100 g), polysorbate 80, glycerol, and water and applied to the cheese's surface by brushing. Uncoated cheeses were also analyzed for comparison. Moreover, films were prepared and characterized in terms of their moisture content, water vapor permeability, mechanical properties, transparency, water solubility, swelling (%), and antioxidant activity. Carvacrol/starch films showed a slight decrease in their water solubility and Young's modulus, while not significant changes were observed in water vapor permeability, moisture content, transparency, and swelling behavior, in comparison with the starch films. After application on the Paipa cheeses, the carvacrol/starch coatings enhanced the brightness of the cheeses without causing significant changes in water activity, moisture content, color attributes, and mesophilic aerobic bacteria and molds/yeasts count. Moreover, edible coatings have a significant effect on the hardness, the gumminess, the springiness, and the chewiness of the Paipa cheese. Coated cheeses were better preserved at day 60 of storage because they did not show changes in their lightness, hardness, and springiness.

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The physicochemical and sensory differences between the PGI-Certified Ternera de Navarra (CTNA) (Spanish origin) and Certified Angus Beef (CAB) (US origin) were assessed in Spain and the USA. To characterize the carcasses, the ribeye areas (REAs), and marbling levels were assessed in both testing places. Twenty striploins per certified beef program were used as study samples. For sensory analysis, the striploins were vacuum packaged and aged for 7 days at 4 °C and 85% RH in each corresponding laboratory. Thereafter, the samples were half cut and frozen. One of the halves was shipped to the other counterpart-testing place. The fat and moisture percentage content, Warner Bratzler Shear Force (WBSF), and total and soluble collagen were tested for all the samples. The CAB carcasses had smaller REAs (p < 0.0001) and exhibited higher marbling levels (p < 0.0001). The CAB striploins had a higher fat content (p < 0.0001) and required lower WBSF (p < 0.05) than the CTNA samples. Trained panelists rated the CAB samples as juicer (p < 0.001), more tender/less tough (p < 0.0001), and more flavorful (p < 0.0001) than the CTNA counterparts. This study shows that beef from both countries had medium-high tenderness, juiciness, and beef flavor scores and very low off-flavor scores. Relevant differences found between the ratings assigned by the Spanish and the US panelists suggest training differences, or difficulties encountered in using the appropriate terminology for defining each sensory attribute. Furthermore, the lack of product knowledge (i.e., consumption habits) may have been another reason for such differences, despite the blind sensory evaluation.

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For Protected Geographical Indication (PGI)-labeled products, such as the dry-cured beef meat "cecina de León", a sensory analysis is compulsory. However, this is a complex and time-consuming process. This study explores the viability of using near infrared spectroscopy (NIRS) together with artificial neural networks (ANN) for predicting sensory attributes. Spectra of 50 samples of cecina were recorded and 451 reflectance data were obtained. A feedforward multilayer perceptron ANN with 451 neurons in the input layer, a number of neurons varying between 1 and 30 in the hidden layer, and a single neuron in the output layer were optimized for each sensory parameter. The regression coefficient R squared (RSQ > 0.8 except for odor intensity) and mean squared error of prediction (MSEP) values obtained when comparing predicted and reference values showed that it is possible to predict accurately 23 out of 24 sensory parameters. Although only 3 sensory parameters showed significant differences between PGI and non-PGI samples, the optimized ANN architecture applied to NIR spectra achieved the correct classification of the 100% of the samples while the residual mean squares method (RMS-X) allowed 100% of non-PGI samples to be distinguished.

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The aim of this qualitative case study is to examine how two post-socialist nation-states-Latvia and Estonia-have appropriated and implemented the European Union (EU) food quality schemes in order to protect traditional food products. Relying on documents, interviews and observations, the focus is on analysing the process of applying for EU quality labels such as Traditional Speciality Guaranteed (TSG) and Protected Geographical Indication (PGI). The results demonstrate that in both countries, these EU quality labels seem to compensate for a lack of national quality schemes for traditional food products. EU quality products are considered as national property and are used as tools for marketing small, post-socialist countries among member states within the EU. The state authorities in Latvia and Estonia have different degrees of intervention in the process of applying for quality labels. Micro and small-scale producers especially lack the administrative resources and expertise needed for the application, as well as surveillance. This study suggests that the implementation of the EU food quality schemes not only benefits food producers but also compels them to confront the multiple controversies related to transforming traditional foods into standardised and certified "European products".

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According to Coldiretti, Italy still continues to hold the European Quality record in extra virgin olive oils with origin designation and protected geographical indication (PDO and PGI). To date, 46 Italian brands are recognized by the European Union: 42 PDO and 4 PGI (Tuscan PGI, Calabria PGI; Tuscia PGI and PGI Sicily). Specific regulations, introduced for these quality marks, include the designation of both the geographical areas and the plant varieties contributing to the composition of the olive oil. However, the PDO and PGI assessment procedures are currently based essentially on farmer declarations. Tuscan PGI extra virgin olive oil is one of the best known Italian trademarks around the world. Tuscan PGI varietal platform is rather wide including 31 specific olive cultivars which should account for at least 95% of the product. On the other hand, while the characteristics of other popular Italian extra virgin olive oils (EVOOs) cultivars from specific geographical areas have been extensively studied (such as those of Coratina based blends from Apulia), little is still known about Tuscan PGI EVOO constituents. In this work, we performed, for the first time, a large-scale analysis of Tuscan PGI monocultivar olive oils by ¹H NMR spectroscopy and multivariate statistical analyses (MVA). After genetic characterization of 217 leaf samples from 24 selected geographical areas, distributed all over the Tuscany, a number of 202 micro-milled oil samples including 10 PGI cultivars, was studied. The results of the present work confirmed the need of monocultivar genetically certified EVOO samples for the construction of ¹H-NMR-metabolic profiles databases suitable for cultivar and/or geographical origin assessment. Such specific PGI EVOOs databases could be profitably used to justify the high added value of the product and the sustainability of the related supply chain.

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Analysis of the attributes determining the formation of consumers' preferences when buying lamb meat is a key aspect in increasing the demand for this product. To this end, by means of conjoint analysis, we determined lamb meat consumers' preferences according to their frequency of consumption, and we used logistic simulation to analyse market shares of the most valued attributes. After segmenting the market into habitual and occasional consumers of lamb meat, our results seem to suggest that while regular consumers base their preferences mostly on origin, occasional consumers take other attributes into account, such as Protected Geographical Origin (PGI) and organic production. An analysis of market shares shows that PGI significantly influences consumer preferences, while ecological production has a less marked impact. This finding confirms the usefulness of PGI in the lamb meat market and highlights the urgent need to improve the communication strategy of the organic production sector as a synergistic effect to increase its acceptance among consumers.

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