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This study comprehensively characterised a protected designation of origin mussel 'Cozza di Scardovari' (Mytilus galloprovincialis) by examining how it is affected by the farming site (outer vs. inner area of the lagoon) and harvest time (21 April vs. 18 May vs. 16 June). Harvest time affected the marketable traits and fatty acid profile of mussels, whereas farming site scarcely affected marketable traits and mussel yields. Mussels from the inner area of the lagoon displayed a superior nutritional profile, including higher contents of proteins (7.8% vs. 7.4%; P < 0.05), lipids (1.2% vs. 1.0%; P < 0.001) and essential amino acids such as tryptophan (+24%; P < 0.05) and valine (+8%; P < 0.05), with a more favourable n-3/n-6 ratio (7.7 vs. 7.0; P < 0.001) than those from the close-to-sea area. Volatile organic compounds, mainly octanoic acid, dimethyl sulphide and 1-penten-3-ol, differed between farming sites within the same lagoon.

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Italy and France are historically among the countries that produce the most prestigious wines worldwide. In Europe, these two countries together produce more than half of the wines classified under the Protected Designation of Origin (PDO) label, the strictest quality mark of food and wines in the European Union. Due to their long tradition in wine protection, Italy and France include highly detailed specifications in their wine PDO regulatory documents that are usually not available for other countries, such as specific information about the main cultivars that must be used to make each wine or the required planting density in the vineyards. However, this information is scattered throughout the documents of each wine production area and has never been extracted and homogenised in a unique dataset. Here, we present the first dataset that characterizes the PDO wines produced in Italy and France at very high detail based on the information from the official EU geographical indication register. For each country it includes a standardized list of the PDO wine names, linked with their specific requirements, such as the wine colour, type, cultivars used and maximum allowed yields. The unprecedented level of detail of this dataset allows for the first time the analysis of more than 5000 traditional wines and their legal and agronomic specifications. This gives insights into the interplay between the European Union quality regulation policy, the wine sector, and agronomic practices, enabling researchers and practitioners to analyze wine production in the context of specific regulations or economic scenarios.

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Northeastern states of India are known for unique landraces of Capsicum spp. with geographical indications. However, little information is available about these valuable landraces of chillies. Surveys and collections were carried out in niche areas to find out their ecology and diversity through morphological traits and molecular analysis using microsatellite markers. Our result characterized the ecology of niche areas as cool (11.0°C-20.7°C) and humid (>60% relative humidity) climates for dalle-chilli (Capsicum annuum L.); mild-warm (12.2°C-28.6°C) and humid for king-chilli (C. chinense Jacq.); and cool to warm (11.3°C-33.1°C) and humid for bird's eye chilli (C. frutescens L.) during the crop period. The canonical correspondence analysis has shown the significant impact of temperature on the agro-morphological traits and distribution of the landraces in their niche areas. A wide variability was observed for different quantitative traits and yield attributing characters (fruit length, diameter, weight, and yield), showing high heritability (97.0%-99.0%), and genetic advance as a percentage of the mean (119.8%-434.0%). A total of 47 SSR markers used for the molecular analysis generated 230 alleles, ranging from 2 (HPMSE-7) to 10 (HPMSE-5), with an average of 4.89 alleles per locus. The average polymorphism information content was also high (0.61) and ranged from 0.20 (HPMSE-7) to 0.85 (CAMS-91). The observed average heterozygosity was lower than the expected value. Analysis of molecular variance has shown significant variation within (69%) and between (31%) of the populations of Capsicum spp. Based on Nei's genetic distance, bird's eye chilli and king-chilli were found to be closer to each other, whereas dalle-chilli, a tretraploid species, was closer to hot pepper (C. annuum). However, the flower size of dalle-chilli was large and found closer to king-chilli in color and differs from C. chinense due to the presence of calyx teeth. For quality traits, landraces king-chilli, dalle-chilli, and bird's eye chilli have shown 2.8, 2.0, and 1.4 times higher average capsaicin and 0.46, 0.25, and 0.22 times higher average oleoresin content over the hot pepper, respectively. The knowledge of ecology and diversity can be used in identifying new areas for production, selection of elite lines, conservation, and crop improvement.

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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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The Selçuk district of Izmir is one of the most essential regions in terms of olive oil production. In this study, 60 olive oil samples were obtained from five different locations (ES: Eski Sirince Yolu, KK: Kinali Köprü, AU: Abu Hayat Üst, AA: Abu Hayat Alt, and DB: Degirmen Bogazi) in the Selçuk region of Izmir during two (2019-2020 and 2020-2021) consecutive cropping seasons. Quality indices (free acidity, peroxide value, p-Anisidine value, TOTOX, and spectral absorption at 232 and 270 nm) and the fatty acid, phenolic, and sterol profiles of the samples were determined to analyze the changes in the composition of Selcuk olive oils according to their growing areas. When the quality criteria were analyzed, it was observed that KK had the lowest FFA (0.11% oleic acid, PV (6.66 meq O2/kg), p-ANV (11.95 mmol/kg), TOTOX (25.28), and K232 (1.99) values and K270 had the highest value. During the assessment of phenolic profiles, the ES group exhibited the highest concentration of the phenolic compound p-HPEA-EDA (oleocanthal), with a content of 93.58 mg/kg, equivalent to tyrosol. Upon analyzing the fatty acid and sterol composition, it was noted that AU displayed the highest concentration of oleic acid (71.98%) and ß-sitosterol (87.65%). PCA analysis illustrated the distinct separation of the samples, revealing significant variations in both sterol and fatty acid methyl ester distributions among oils from different regions. Consequently, it was determined that VOOs originating from the Selçuk region exhibit distinct characteristics based on their geographical locations. Hence, this study holds great promise for the region to realize geographically labeled VOOs.

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The essential characteristic of geographical indication products is the association of the products with their region of origin. However, consumers have different associations between products and their region of origin (i.e., different regional typicality) according to different geographical indication products. In this regard, this research aims to explore how to adopt supporting advertising appeal types to improve consumers' attitudes and intentions toward geographical indication products with different regional typicality. To this end, this article proposes and tests the interaction between regional typicality and advertising appeal types on consumption intention toward products and the underlying mechanism and boundary conditions of this effect. Using three studies, this research finds that the adoption of abstract (vs. concrete) appeal is more likely to enhance consumption intention toward products when the geographical indication products have high regional typicality. Moreover, the reverse is true when the geographical indication products have low regional typicality. Furthermore, the results show that processing fluency mediates the interaction effect. In addition, the high (low) regional typicality and abstract (concrete) appeal on consumption intention toward products are more significant in the distant (close) spatial distance condition. In this way, this research provides a new perspective for studying consumer behavior with respect to geographical indication products and has implications for promoting the sales of geographical indication products and enhancing the brand value of geographical indication.

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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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Food fraud, along with many challenges to the integrity and sustainability, threatens the prosperity of businesses and society as a whole. Tea is the second most commonly consumed non-alcoholic beverage globally. Challenges to tea authenticity require the development of highly efficient and rapid solutions to improve supply chain transparency. This study has produced an innovative workflow for black tea geographical indications (GI) discrimination based on non-targeted spectroscopic fingerprinting techniques. A total of 360 samples originating from nine GI regions worldwide were analysed by Fourier Transform Infrared (FTIR) and Near Infrared spectroscopy. Machine learning algorithms (k-nearest neighbours and support vector machine models) applied to the test data greatly improved the GI identification achieving 100% accuracy using FTIR. This workflow will provide a low-cost and user-friendly solution for on-site and real-time determination of black tea geographical origin along supply chains.

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Strawberry is the most consumed berry fruit worldwide due to its unique aroma and high nutritive value. This fruit is also an important source of phenolic compounds. Changping strawberries are recognized as a national agricultural product of geographical indication (GI) due to their unique flavor. Widely accepted standards for identifying GI strawberries from non-GI strawberries are currently unavailable. This study compared the aroma and phenolic acid composition of GI and non-GI strawberries. Furthermore, the characteristic aroma and phenolic acid markers of GI strawberries were determined. A classification model based on the markers was established using Fisher discriminant analysis (FDA). In this study, six groups of strawberries with variety name of "Hongyan", including GI strawberries from Changping and non-GI strawberries from Changping, Miyun, Pinggu, Shunyi, and Tongzhou, were collected. A total of 147 volatile substances were discovered using gas chromatography-tandem mass spectrometry. The contents of a few compounds principally responsible for the distinctive aroma in GI strawberries were in the top three of the six groups, providing GI strawberries with a generally pleasant fragrance. OPLS-DA identified isoamyl butyrate and trans-2-octen-1-ol as characteristic markers. Enrichment analysis indicated that beta-oxidation of very long-chain fatty acids, mitochondrial beta-oxidation of very long-chain fatty acids, fatty acid biosynthesis, and butyrate metabolism played critical roles in volatile compound biosynthesis. The total phenolic content was 24.41-36.46 mg/kg of fresh weight. OPLS-DA results revealed that cinnamic acid could be used as a characteristic phenolic acid marker of GI strawberries. Based on the three characteristic markers, FDA was performed on the different groups, which were then divided. The separation of strawberry samples from different origins using the three characteristic markers was found to be feasible. These findings help effectively understand the aroma and phenolic acid composition of strawberries and contribute to the development of strawberries with a pleasant fragrance and health benefits.

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Establishing the concept of terroir in wines, combined with the exploitation of native grape varieties, is considered a viable alternative to produce quality wines for increasing interest in the wine market. The aim of this study is the characterization of Protected Geographical Indication (PGI) Savatiano white wines from different regions of Attica (Greece), through the chemical and sensory description of the aroma of wines and the determination of their phenolic profiles. The wines produced with the same vinification protocol were evaluated using the descriptive sensory analysis method while they underwent profiling of volatile and phenolic compounds by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) respectively. The presence of regional differences within the wines was also explored, elaborated with variables that contribute to their differentiation, such as soil type, monthly average temperature, and rainfall. Volatile and sensory profiles of the wines separated the regions and confirmed that sub-regional differences attributed mainly to soil characteristics affect wine aroma. The wines from the east part of Attica were higher in esters, terpenes and higher alcohols with high scores in fruity and blossoms attributes while wines from the north part of Attica presented higher intensity of mineral, nutty and herbaceous attributes. The separations based solely on the phenolic compounds concentration were less clear but a relationship was found between the content of phenolic acids and flavonoids and the studied regions. To our knowledge this is the first characterization of Savatiano PGI wines of Attica generating a fingerprint including chemical composition and sensory aroma characteristics to differentiate wines, combining this pattern with particular sub-regions.

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Geographical indications (GI) are used to protect the brand value of agricultural products, foodstuffs, and wine and promote the sustainable development of the agricultural and food industries. Despite the necessity for the traceability and recognition of GI product characteristics, no rapid, non-destructive approaches currently exist to identify, classify, and predict these properties. The application of gas chromatography-ion mobility spectrometry (GC-IMS) has increased exponentially due to instrument robustness and simplicity. This paper provided a detailed overview of recent GC-IMS applications in China for the quality evaluation of GI products and food, including agricultural products, as well as traditional Chinese food and liquor. The general workflow of GC-IMS coupled with chemometric analysis is presented, including sample collection, model construction and interpretation, and data acquisition, processing, and fusion. Several conclusions are drawn to increase partial least squares-discriminant analysis (PLS-DA) model precision, a chemometric technique frequently combined with GC-IMS.

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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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Panax notoginseng (P. notoginseng) has excellent medicinal and food dual-use characteristics. However, P. notoginseng with a unique origin label has become the target of fraud because of people confusing or hiding its origin. In this study, an untargeted nuclear magnetic resonance (NMR)-based metabolomics approach was used to discriminate the geographical origins of P. notoginseng from four major producing areas in China. Fifty-two components, including various saccharides, amino acids, saponins, organic acids, and alcohols, were identified and quantified through the NMR spectrum, and the area-specific geographical identification components were further screened. P. notoginseng from Yunnan had strong hypoglycemic and cardiovascular protective effects due to its high acetic acid, dopamine, and serine content, while P. notoginseng from Sichuan was more beneficial for diseases of the nervous system because of its high content of fumarate. P. notoginseng from Guizhou and Tibet had high contents of malic acid, notoginsenoside R1, and amino acids. Our results can help to distinguish the geographical origin of P. notoginseng and are readily available for nutritional recommendations in human consumption.

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With the rising trend of valuing flavor complexity of coffees, means to distinguish the properties of individual coffee sources is vital to the sustainable growth of the coffee industry. Herein, paper spray mass spectrometry (PS-MS), a simple technique with little sample preparation, was used to collect mass data from aqueous extracts of coffees from various sources. Thereafter, principal component analysis and linear discriminant analysis were used to successfully classify coffee samples (with 80-100 % accuracy) from various studies including the differentiations of Arabica and Robusta coffees, Arabica coffees from different countries, Robusta coffees from different geographical locations, and Arabica coffees from different locations within the same province in Thailand. With further insight from significant test via Fisher weight determination, this method was proved to be practical for differentiating coffees based on types and geographical origins, thus paving the way for broader applications.

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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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Analytical assurance of coffees' geographical indication (GI) authenticity is essential for producers and consumers. In this way, chemometric methods, electrochemical techniques, and 3D printed sensors become attractive to assure the coffee's quality. These sensors are low-cost, fast, and simple, with the possibility of miniaturization and portability. Therefore, 3D printed electrodes with chemometrics were used to classify-three Brazilian coffees from regions with GI. Further, Au/Gpt-PLA electrodes with partial least squares regression were used to detect the blending of GI coffee with traditional coffee. Soft independent modelling of class analogies coupled with cyclic voltammetry had the best performance, with 91-95% accuracy, specificity of 94-100%, and 80-83% sensitivity. Furthermore, the calibration models detected and quantified traditional coffee in all three coffees from regions with GI. The detection limits ranged from 1.4 to 10% (w/w), and quantification 4.6-32%, depending on the specific coffee.

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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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The paper examined the factors influencing farmer's willingness to adopt GI (geographical indication) practices in the Indonesian coffee sector from a psycho behavioral perspective. Specifically, the paper examined the psychological factors influencing the willingness of farmers to adopt GI. The study combined (1) the Planned Behavior (TPB) theory and (2) Technology Acceptance Model (TAM) as the theoretical framework. The following psycho behavioral factors were constructed and tested: subjective norm (SN), perceived behavioral control (PBC), attitudes toward behavior (ATB), perceived usefulness (PU) and perceived economic benefit (PEB). The study also investigated the effects of sociodemographic factors on these psycho behavioral constructs. The survey was conducted in two geographical indication coffee territories in Indonesia that involved 178 farmers who are perceived as willing to adopt GI practices and procedures. The relationship between constructs was investigated in which structural equation modeling (SEM) was used. The obtain data were analyzed using WarpPLS 7.0. The study finds that attitude toward behavior, perceived behavioral control, and perceived economic benefit, as important factors influencing the willingness to adopt GI practices. The subjective norm did not affect willingness to adopt GI practices. Farmers' knowledge mainly affected perceived behavioral control and willingness to adopt GI practices and procedures.

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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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