Fingerprinting of monovarietal olive oils from Argentina and Uruguay via stable isotope, fatty acid profile, and chemometric analyses.

Tracing methods of non-European EVOOs commercialized worldwide are becoming crucial for effective authenticity controls. Limited analytical studies of these oils are available on a global scale, similar to those of European EVOOs. We report for the first time the fatty acid concentrations, bulk-oil 2H/1H, 13C/12C, and 18O/16O ratios and fatty acid 13C/12C ratios of 43 authentic monovarietal EVOOs from different geographical regions in Argentina and Uruguay. The samples were obtained from a wide range of latitudes and altitudes along an E-W profile, from lowlands near the Atlantic Ocean to the pre-Andean highlands near the Pacific Ocean. Principal component scores were used to cluster EVOOs into three groups- central-western Argentina, central Argentina, and Uruguay-based on nine stable isotope ratios and the oleic-linoleic acid concentration ratio. The bulk 2H/1H and 18O/16O values and 13C/12C of palmitoleic and linoleic acids provide good tools for differentiating these oils via linear discriminant analysis.

Behavioral decision-making of government, agricultural product producers, and consumers on agricultural product quality and safety regulation in a digital environment.

The quality and safety of agricultural products are related to people's lives and health, economic development, and social stability, and have always been a hot issue of concern to the government and society. The rapid development of digital traceability technology in the digital environment has brought new opportunities for the supervision of agricultural product quality and safety, but the frequent occurrence of agricultural product safety incidents in recent years has exposed many problems such as the lack of governmental supervision, unstandardized production process of enterprises, and weak consumer awareness. To improve the cooperation efficiency of stakeholders and ensure the quality and safety of agricultural products, this paper proposes a dynamic model based on evolutionary game theory. The model incorporates the government, agricultural product producers, and farmers, and evaluates the stability and effectiveness of the system under different circumstances. The results of the study show that there are multiple evolutionary stabilization strategies in the tripartite evolutionary game model of agricultural product quality and safety supervision, and there are corresponding evolutionary stabilization conditions. There are several factors affecting the stability of the system, the most important of which are government regulation, severe penalties for agricultural product producers, and incentives. When these factors reach a certain threshold, the stakeholder cooperation mechanism can establish an evolutionarily stable strategy. This study contributes to the understanding of the operational mechanism of stakeholder cooperation in agricultural product quality and safety regulation in the digital environment and provides decision support and policy recommendations for stakeholders to promote the sustainable development and optimization of agricultural product quality and safety regulation.

The role of analytical performance specifications in international guidelines and standards dealing with metrological traceability in laboratory medicine.

The goal of metrological traceability is to have equivalent results for a measurand in clinical samples (CSs) irrespective of the in-vitro diagnostic medical device (IVD-MD) used for measurements. The International Standards Organization standard 17511 defines requirements for establishing metrological traceability of values assigned to calibrators, trueness control materials and human samples used with IVD-MDs. Each step in metrological traceability has an uncertainty associated with the value assigned to a material. The uncertainty at each step adds to the uncertainty from preceding steps such that the combined uncertainty gets larger at each step. The combined uncertainty for a CS result must fulfil an analytical performance specification (APS) for the maximum allowable uncertainty (umax CS). The umax CS can be partitioned among the steps in a metrological traceability calibration hierarachy to derive the APS for maximum allowable uncertainty at each step. Similarly, the criterion for maximum acceptable noncommutability bias can be derived from the umax CS. One of the challenges in determining if umax CS is fulfilled is determining the repeatability uncertainty (u Rw) from operating an IVD-MD within a clinical laboratory. Most of the current recommendations for estimating u Rw from internal quality control data do not use a sufficiently representative time interval to capture all relevant sources of variability in measurement results. Consequently, underestimation of u Rw is common and may compromise assessment of how well current IVD-MDs and their supporting calibration hierarchies meet the needs of clinical care providers.

Sybil Attacks Detection and Traceability Mechanism Based on Beacon Packets in Connected Automobile Vehicles.

Connected Automobile Vehicles (CAVs) enable cooperative driving and traffic management by sharing traffic information between them and other vehicles and infrastructures. However, malicious vehicles create Sybil vehicles by forging multiple identities and sharing false location information with CAVs, misleading their decisions and behaviors. The existing work on defending against Sybil attacks has almost exclusively focused on detecting Sybil vehicles, ignoring the traceability of malicious vehicles. As a result, they cannot fundamentally alleviate Sybil attacks. In this work, we focus on tracking the attack source of malicious vehicles by using a novel detection mechanism that relies on vehicle broadcast beacon packets. Firstly, the roadside units (RSUs) randomly instruct vehicles to perform customized key broadcasting and listening within communication range. This allows the vehicle to prove its physical presence by broadcasting. Then, RSU analyzes the beacon packets listened to by the vehicle and constructs a neighbor graph between the vehicles based on the customized particular fields in the beacon packets. Finally, the vehicle's credibility is determined by calculating the edge success probability of vehicles in the neighbor graph, ultimately achieving the detection of Sybil vehicles and tracing malicious vehicles. The experimental results demonstrate that our scheme achieves the real-time detection and tracking of Sybil vehicles, with precision and recall rates of 98.53% and 95.93%, respectively, solving the challenge of existing detection schemes failing to combat Sybil attacks from the root.

Digital Traceability in Agri-Food Supply Chains: A Comparative Analysis of OECD Member Countries.

In an era marked by globalization and rapid technological advancements, the agri-food sector confronts both unprecedented challenges and opportunities. Among these, digital traceability systems have emerged as pivotal in enhancing operational efficiencies, ensuring food safety, and promoting transparency throughout the supply chain. This study presents a comparative analysis of digital traceability adoption and its impact across member countries of the Organization for Economic Co-operation and Development (OECD). By utilizing a multidimensional analytical framework, this study investigates national regulations, legal frameworks, and key food commodities affected by digital traceability implementations. It systematically assesses the efficacy of these systems in meeting consumer transparency expectations, regulatory compliance, and the overarching goal of sustainable agri-food supply chains. Through case studies and empirical evidence, the paper elucidates the complex interplay between technological innovation and regulatory environments, offering insights into best practices and potential integration barriers. Ultimately, this comprehensive investigation contributes to the scholarly discourse on digital traceability, providing actionable recommendations for policymakers, industry stakeholders, and academia to navigate the complexities of modern agri-food systems.

Garlic Origin Traceability and Identification Based on Fusion of Multi-Source Heterogeneous Spectral Information.

The chemical composition and nutritional content of garlic are greatly impacted by its production location, leading to distinct flavor profiles and functional properties among garlic varieties from diverse origins. Consequently, these variations determine the preference and acceptance among diverse consumer groups. In this study, purple-skinned garlic samples were collected from five regions in China: Yunnan, Shandong, Henan, Anhui, and Jiangsu Provinces. Mid-infrared spectroscopy and ultraviolet spectroscopy were utilized to analyze the components of garlic cells. Three preprocessing methods, including Multiple Scattering Correction (MSC), Savitzky-Golay Smoothing (SG Smoothing), and Standard Normalized Variate (SNV), were applied to reduce the background noise of spectroscopy data. Following variable feature extraction by Genetic Algorithm (GA), a variety of machine learning algorithms, including XGboost, Support Vector Classification (SVC), Random Forest (RF), and Artificial Neural Network (ANN), were used according to the fusion of spectral data to obtain the best processing results. The results showed that the best-performing model for ultraviolet spectroscopy data was SNV-GA-ANN, with an accuracy of 99.73%. The best-performing model for mid-infrared spectroscopy data was SNV-GA-RF, with an accuracy of 97.34%. After the fusion of ultraviolet and mid-infrared spectroscopy data, the SNV-GA-SVC, SNV-GA-RF, SNV-GA-ANN, and SNV-GA-XGboost models achieved 100% accuracy in both training and test sets. Although there were some differences in the accuracy of the four models under different preprocessing methods, the fusion of ultraviolet and mid-infrared spectroscopy data yielded the best outcomes, with an accuracy of 100%. Overall, the combination of ultraviolet and mid-infrared spectroscopy data fusion and chemometrics established in this study provides a theoretical foundation for identifying the origin of garlic, as well as that of other agricultural products.

Discriminant canonical analysis as a tool for genotype traceability testing based on turkey meat and carcass traits.

The present study aims to develop a statistical tool for turkey breed traceability testing based on meat and carcass quality characteristics. To this end, a comprehensive meta-analysis was performed, collecting data from a total of 75 studies approaching meat and carcass attributes of 37 turkey strains and landraces since the late 1960s. A total of 22 meat and carcass traits were considered variables, grouped in the following clusters: carcass dressing traits, muscle fiber properties, pH, colorimetry, water-capacity traits, texture-related attributes, and nutritional composition of the meat. Once the multicollinearity analysis allowed the deletion of redundant variables, cold carcass weight, slaughter weight, muscle fiber diameter, sex-female, carcass/piece weight, meat redness, ashes, pH24, meat lightness, moisture, fat, and water-holding capacity showed explanatory properties in the discriminating analysis (p < 0.05). In addition, strong positive and negative correlations were found among those variables studied. Carcass traits were positively associated, particularly slaughter weight and cold carcass weight (+0.561). Among meat physical traits, pH showed positive correlations with drip loss (+0.490) and pH24 (+0.327), and water-holding capacity was positively associated with cholesterol (+0.434) and negatively associated with collagen (-0.398). According to nutritional traits, fat and ash showed a strong correlation (+0.595), and both were negatively associated with moisture (-0.375 and -0.498, respectively). Strong negative correlations were found as well between meat protein and fat (-0.460) and between collagen and cholesterol (-0.654). Finally, the Mahalanobis distance suggested a clustering pattern based on meat and carcass characteristics that report information about interbreeding and variety proximity. This study establishes a departure point in the development of a tool for breed traceability guaranteeing aimed at enhancing distinguished, local breed-based turkey meat.

Combination of fingerprint and chemometric analytical approaches to identify the geographical origin of Qinghai-Tibet plateau rapeseed oil.

Verification of the geographical origin of rapeseed oil is essential to protect consumers from fraudulent products. A prospective study was conducted on 45 samples from three rapeseed oil-producing areas in Qinghai Province, which were analyzed by GC-FID and GC-MS. To assess the accuracy of the prediction of origin, classification models were developed using PCA, OPLS-DA, and LDA. It was found that multivariate analysis combined with PCA separate 96% of the samples, and the correct sample discrimination rate based on the OPLS-DA model was over 98%. The predictive index of the model was Q2 = 0.841, indicating that the model had good predictive ability. The LDA results showed highly accurate classification (100%) and cross-validation (100%) rates for the rapeseed oil samples, demonstrating that the model had strong predictive capacity. These findings will serve as a foundation for the implementation and advancement of origin traceability using the combination of fatty acid, phytosterol and tocopherol fingerprints.

TaqMan® and HRM approaches for SNP genotyping in genetic traceability of musts and wines.

The fight against fraud in the wine sector requires continuous improvements and validations of new technologies applicable to musts and wines. Starting from published data from the Vitis18kSNP array, a series of new specific single nucleotide polymorphism (SNP) markers have been identified for some important north-western Italian cultivars, such as Barbera, Dolcetto and Arneis (Vitis vinifera L.), used in the production of high-quality wines under Protected Denomination of Origin. A pair of new SNP markers for each grape variety were selected and validated using two real-time PCR techniques: TaqMan® genotyping assays and high-resolution melting analysis (HRM). The TaqMan® assay has proven to be more reliable and repeatable than HRM analysis because despite being an economical and versatile technique for the detection of different types of genomic mutations (SNPs, insertions or deletions), HRM has shown limitations in the presence of poor-quality DNA extracted from musts and wines. TaqMan® assays have successfully identified Barbera, Dolcetto and Arneis in their respective musts and experimental wines, and with good efficiency in commercial wines. Marked differences between genotypes were observed, varietal identification in Dolcetto-based musts/wines was more efficient than that in Arneis-based wines. Therefore, the TaqMan® assay has considerable potential for varietal identification in wines and the procedure described in the present work can be easily adapted to all wines with adequate setup of DNA extraction methods that should be adapted to different wines.

[Traceability Analysis and Environmental Quality Assessment of Soil Heavy Metal Pollution in West Hunan Province].

In order to explore the status of soil heavy metal pollution and environmental quality in west Hunan, relevant areas of Phoenix County were selected as the study area. Using data from 440 soil samples collected in the study area from June to August 2022, the pH value of the soil and contents of eight heavy metal elements, namely, As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn, were analyzed. The PMF model was used for traceability analysis and geochemical evaluation of soil environmental quality. The results showed that the average values of soil heavy metals ω(Zn), ω(Cr), ω(Pb), ω(Ni), ω(Cu), ω(As), ω(Cd), and ω(Hg) were 81.02, 64.67, 31.63, 29.27, 25.52, 9.93, 0.28, and 0.13 mg·kg-1, respectively. The soil in the study area was mainly weakly acidic, and the contents of the Cd and Hg elements were relatively high compared to the national soil background values and were highly variable. The contents of the Hg and Cd elements in forest land were higher than that in other land uses. The PMF model results showed that the contribution rates of heavy metal pollution sources in the study area were mining sources (37.4%), atmospheric sedimentation sources (7.7%), natural sources (41.1%), and agricultural activity sources (13.8%) and provided suggestions on pollution control measures according to the spatial distribution of the four types of pollution sources. Through the comprehensive assessment of soil environmental geochemistry, the study area was divided into three types of plots, namely, non-risk areas (94.27 km2), accounting for 76.38%; risk-controllable areas (27.45 km2), accounting for 22.24%; and high-risk areas (1.7 km2), accounting for 1.38%. This study provided data support for the prevention and control measures of land pollution in the research area, as well as the delineation of the prevention and control scope.

Effect of Beverage Composition on Radio Frequency Identification (RFID) Performance Using Polyethylene Terephthalate (PET) Bottles for Smart Food Packaging Applications.

Radio frequency identification (RFID) technology is crucial in revolutionizing the food supply chain and combating global food waste. However, this technology faces challenges in full integration due to disruptive effects on tags caused by the dielectric properties of food and beverage ingredients, chemical constituents, and their packaging. This paper aims to demonstrate the effect of packaging and beverage contents on RFID tag performance. Three commercially available ultra-high frequency (UHF) RFID tags with different designs were tested on polyethylene terephthalate (PET) bottles, measuring tag performance through sensitivity, backscatter, and read range in the presence of various water-based solutions and commercially available beverages. The results highlight the substantial impact of the beverage type and tag design on RFID performance. The results of this study showed that tag 3 was the most consistent and readable tag amongst those tested in the presence of different beverage contents. Tag 3 resulted in a sensitivity ranging from -0.49 to -2.01 dBm, backscatter from -38.16 to 43.59 dBm, and read range from 1.58 to 1.88 m, while tag 1 performed the best in the presence of an empty PET bottle resulting in a sensitivity of -20.78 dBm, backscatter of -23.65 dBm, and read range of 16.34 m. The results of this study can be used for further investigations to develop a mathematical model that predicts the RFID tag performance based on the food composition. This model will be helpful for the design of the tags while facilitating the adoption of smart packaging for food traceability.

A Redactable Blockchain-Based Data Management Scheme for Agricultural Product Traceability.

With the development of agricultural information technology, the Internet of Things and blockchain have become important in the traceability of agricultural products. Sensors collect real-time data in agricultural production and a blockchain provides a secure and transparent storage medium for these data, which improves the transparency and credibility of agricultural product traceability. However, existing agricultural product traceability solutions are limited by the immutability of the blockchain, making it difficult to delete erroneous data and modify the scope of data sharing. This damages the credibility of traceability data and is not conducive to the exchange and sharing of information among enterprises. In this article, we propose an agricultural product traceability data management scheme based on a redactable blockchain. This scheme allows agricultural enterprises to encrypt data to protect privacy. In order to facilitate the maintenance and sharing of data, we introduce a chameleon hash function to provide data modification capabilities. Enterprises can fix erroneous data and update the access permissions of the data. To improve the efficiency of block editing, our scheme adopts a distributed block editing method. This method supports threshold editing operations, avoiding single-point-of-failure issues. We save records of data modifications on the blockchain and establish accountability mechanisms to identify malicious entities. Finally, in this paper we provide a security analysis of our proposed solution and verify its effectiveness through experiments. Compared with the existing scheme, the block generating speed is improved by 42% and the block editing speed is improved by 29.3% at 125 nodes.

Characterization among and within Sicilian Tetraploid Wheat Landraces by Gluten Protein Analysis for Traceability Purposes.

The criteria of "Distinctness, Uniformity and Stability" as well as a high "overall quality index" are used to register the Italian modern varieties to the national register. Differently, local conservation varieties can be certified under different EU Directives that facilitate, as an overall objective, the preservation of biodiversity and the containment of genetic erosion. In recent years, products derived from ancient grains are perceived to be healthier and more sustainable by consumers, especially in Italy, with consequent higher market prices. The ancient tetraploid wheat varieties registered in the national register of conservation varieties amount to 28, 24 of which are Sicilian. They are supposed to have wide genetic variability compared to modern ones, making them vulnerable to fraud because they are difficult to trace. It is therefore important to have tools able to discriminate between autochthonous Sicilian varieties. This can be completed by gluten proteins composition, which also provides information on the technological properties of derived products. Fifty-one accessions belonging to twenty-two ancient varieties of Sicilian tetraploid (mostly durum) wheat were analyzed. Although wide intra-accession and intra-varietal variability measurements were assessed, the gliadin pattern of bulks of seeds belonging to each variety was discriminatory. Moreover, differences in technological attitudes were found between landraces. This paves the way to use gluten protein patterns for traceability, allowing local farmers and producers to valorize their products and assure consumers regarding the transparency of the entire supply chain.

External quality assurance in the era of standardization.

Metrology in clinical chemistry aims to ensure the equivalence of measurement results from different in-vitro diagnostic measurement devices (IVD MD) for use in healthcare. The metrological traceability of measurement results to higher-order references is the cornerstone to achieving equivalent results. However, other fundamentals are also needed, including the commutability of reference materials and external quality assessment (EQA) materials for monitoring the equivalence of measurement results at the end-user level. This manuscript summarizes the findings and opinions expressed at the Joint Community for Traceability in Laboratory Medicine (JCTLM) workshop held on December 4-5, 2023. The workshop explored the relationship between EQA/proficiency testing and metrological traceability to higher-order references. EQA monitors the equivalence of measurement results from end-user IVD MDs. The workshop discussed the role and challenges of using EQA to improve and maintain the equivalence of measurement results. It also elucidated current developments in establishing the clinical suitability of laboratory results expressed as analytical performance specifications (APS).

Shaping the Future of Coffee: Climate Resilience, Liberica's Rise, and By-Product Innovation-Highlights from the International Coffee Convention 2023 (ICC2023).

The International Coffee Convention 2023 comprehensively addressed the contemporary challenges and advancements in the coffee industry, emphasizing sustainability, health, and innovation. This convention gathered experts and stakeholders to explore diverse aspects of coffee, ranging from the potential of underutilized species like Coffea liberica in terms of climate resilience to the innovative use of coffee by-products. The convention featured presentations and discussions, employing both empirical research and analytical reviews to explore various topics, including the health benefits of coffee, the advancements in traceability and authentication methods, and the impact of global regulatory changes on coffee production and trade. The key findings highlighted the importance of biodiversity in coffee production as a response to climate change, the significant health benefits and sustainability potential of coffee by-products, and the evolving landscape of coffee consumption patterns driven by technological innovations. The convention also stressed the need for alignment in global coffee trade regulations, particularly concerning deforestation and traceability. The 2023 convention underscored the complexity and interconnectivity of the coffee industry's challenges and opportunities. It concluded with a forward-looking perspective, emphasizing the need for continued research, sustainable practices, and collaborative efforts to shape the future of the coffee industry. The community is looking forward to furthering these discussions at the next International Coffee Convention in 2024.

An isotope dilution-liquid chromatography-tandem mass spectrometry (ID-LC-MS/MS)-based candidate reference measurement procedure (RMP) for the quantification of primidone in human serum and plasma.

OBJECTIVES: Primidone is an anticonvulsive drug used in the treatment of epilepsy and essential tremor. It offers beneficial effects in controlling seizures, but its usage is also associated with possible side effects. To ensure optimal therapy, it is crucial to measure its concentration through accurate quantification methods. Therefore, our main goal was to develop and validate a new reference measurement procedure (RMP) for accurately measuring primidone levels in human serum and plasma. METHODS: In our study, we focused on the separation of primidone from both known and unknown interferences using a C18 column. To achieve accurate sample preparation, we developed a protocol involving protein precipitation followed by a high dilution step. The validation of the assay and determination of measurement uncertainty were carried out following guidelines from organizations such as the Clinical and Laboratory Standards Institute, the International Conference on Harmonization, and the Guide to the Expression of Uncertainty in Measurement. These rigorous validation processes ensure the reliability and accuracy of our method for quantifying primidone levels in human serum and plasma samples. RESULTS: The RMP was shown to be highly selective and specific, with no evidence of matrix interference. It can be used to quantify primidone in the range of 0.150-30.0 µg/mL. Intermediate precision was less than 4.0 %, and repeatability CV ranged from 1.0 to 3.3 % across all concentration levels. The relative mean bias ranged from 0.1 to 3.9 % for native serum levels, and from -2.6 to 2.8 % for lithium-heparin plasma levels. The measurement uncertainties for single measurements and target value assignment were 1.5-4.1 % and 0.9-1.0 %, respectively. CONCLUSIONS: In this study, we introduce an innovative LC-MS/MS-based candidate RMP specifically designed for primidone in human serum and plasma. Our RMP offers a traceable platform, facilitating the standardization of routine assays and enabling the evaluation of clinically relevant samples. With this novel approach, we aim to enhance the accuracy and reliability of primidone measurements, ultimately benefiting the field of clinical research and patient care.

Development of machine learning models using multi-source data for geographical traceability and content prediction of Eucommia ulmoides leaves.

Rapid and scientific quality evaluation is a hot topic in the research of food and medicinal plants. With the increasing popularity of derivative products from Eucommia ulmoides leaves, quality and safety have attracted public attention. The present study utilized multi-source data and traditional machine learning to conduct geographical traceability and content prediction research on Eucommia ulmoides leaves. Explored the impact of different preprocessing methods and low-level data fusion strategy on the performance of classification and regression models. The classification analysis results indicated that the partial least squares discriminant analysis (PLS-DA) established by low-level fusion of two infrared spectroscopy techniques based on first derivative (FD) preprocessing was most suitable for geographical traceability of Eucommia ulmoides leaves, with an accuracy rate of up to 100 %. Through regression analysis, it was found that the preprocessing methods and data blocks applicable to the four chemical components were inconsistent. The optimal partial least squares regression (PLSR) model based on aucubin (AU), geniposidic acid (GPA), and chlorogenic acid (CA) had a residual predictive deviation (RPD) value higher than 2.0, achieving satisfactory predictive performance. However, the PLSR model based on quercetin (QU) had poor performance (RPD = 1.541) and needed further improvement. Overall, the present study proposed a strategy that can effectively evaluate the quality of Eucommia ulmoides leaves, while also providing new ideas for the quality evaluation of food and medicinal plants.

Trace the origin of yak meat in Xizang based on stable isotope combined with multivariate statistics.

In this study, the feasibility of tracing the origin of yak meat in Xizang Autonomous Region based on stable isotope combined with multivariable statistics was researched. The δ13C, δ15N, δ2H and δ18O in yak meat were determined by stable isotope ratio mass spectrometry, and the data were analyzed by analysis of variance, fisher discriminant analysis (FDA), back propagation (BP) neural network and orthogonal partial least squares discrimination analysis (OPLS-DA). The results showed that the δ13C, δ15N, δ2H and δ18O had significant differences among different origins (P < 0.05). The overall original correct discrimination rate of fisher discriminant analysis was 89.7 %, and the correct discrimination rate of cross validation was 88.2 %. The correct classification rate of BP neural network based on training set was 93.38 %, and the correct classification rate of BP neural network based on test set was 89.83 %. The OPLS-DA model interpretation rate parameter R2Y was 0.67, the model prediction rate parameter Q2 was 0.409, which could distinguish yak meat from seven different producing areas in Xizang Autonomous Region. The results showed that the origin of yak meat in Xizang Autonomous Region can be traced based on stable isotope combined with multivariate statistics.

Markers for meat provenance and authenticity with an account of its defining factors and quality characteristics - a review.

Provenance is becoming increasingly important in meat supply chains as it lends products higher perceived quality. However, its precise definition and interpretation along with its associated characteristics factors have remained somewhat elusive. This review meticulously defines meat provenance while dissecting the essential factors and associated quality attributes that constitute its essence and are subsequently employed to establish pertinent markers for provenance. Meat provenance emerges as a multi-dimensional construct stemming from the adept management of a constellation of factors relating to geographical origin, farm production system, traceability, and authenticity. Through intricate interactions, these factors unveil innate originality that not only forges a distinct reputation but also imparts a unique typicity to the meat product. Gaining insights into a meat product's provenance becomes attainable by scrutinizing its pertinent composition and organoleptic quality traits. Trace elements and stable isotopes stand out as provenance markers, forging a direct connection to both geographical origin and dietary sources. While somewhat less direct in linkage, other markers such as plant biomarkers, fatty acid composition, pH levels, flavour and aromatic compounds along with organoleptic characteristics contribute to the overall understanding of provenance. Additionally, the identification of animal species and breeds serves as key markers, particularly in the context of protected geographical indications. The study findings are useful for the various stakeholders of how the information for meat provenance can be linked with intrinsic and extrinsic factors for meat quality and protecting the integrity of the supply chain with special reference to traceability and authenticity. This article is protected by copyright. All rights reserved.

Ergonomic RFID tag placement on surgical instruments - a preliminary user study.

OBJECTIVES: RFID tags on surgical instruments allow tracking of individual instruments. However, the tags on the instruments can restrict the handling, potentially increasing patient risks. Previous studies analyzed hand contact areas to identify potential locations for tags. However, the studies did not conduct interaction tests using instruments equipped with RFID tags, potentially neglecting the influence of haptic perception. In addition, previous studies required time-consuming evaluations by clinicians. METHODS: Therefore, the present study aims to verify the previous findings in interaction-centered tests with clinicians using real RFID tags on the instruments. Additionally, we had instrument design experts rate RFID tag positions and examined whether they could predict the clinician's preferred tag positions. RESULTS: We found that nearly all RFID tag positions decreased the user satisfaction of clinicians compared to a reference instrument. Compared to previous studies, our study shows that the RFID tag influences the orientations in which an instrument can be comfortably held, which was criticized by clinicians. Instrument design experts could only predict the clinician's preferred tag positions for some instruments. CONCLUSIONS: Therefore, we recommend investigating further changes to instrument design, for what the "ideal" positions proposed by the clinicians in this study can provide initial pointers.