Variation and fractionation of δ2H, δ18O, and δ17O stable isotopes from irrigation water to soil, grapes, and wine for the traceability of geographical origins.

To investigate the variation and fractionation of stable isotopes from irrigation water to soil, grapes, and wine, δ2H, δ18O, and δ17O in different samples from 10 regions in China were determined using a water isotope analyser. The values were significantly different among regions according to the chemometric analysis. All isotopes were significantly and positively correlated with irrigation water-soil and grape-wine. A significant water isotopic fractionation effect was observed from the irrigation water to the soil, grapes, and wine. Stable isotope distribution characteristics correlated with longitude, latitude, altitude, temperature, precipitation, station pressure and wind speed. The linear discriminant analysis (LDA), random forest (RF), support vector machine (SVM), and feed-forward neural network (FNN) models 58.33-100 %, 80-100 %, 53.33-100 %, and 73.33-100 % accurate for distinguishing the geographical origins of all samples from training and test data, respectively. These findings provide a theoretical basis for authenticating the geographic origin of Chinese wines using stable isotope analysis.

Metrological traceable calibration of organic carbon and elemental carbon based on laboratory-generated reference materials.

Carbonaceous aerosol, including organic carbon (OC) and elemental carbon (EC), has significant influence on human health, air quality and climate change. Accurate measurement of carbonaceous aerosol is essential to reduce the uncertainty of radiative forcing estimation and source apportionment. The accurate separation of OC and EC is controversial due to the charring of OC. Therefore, the development of reference materials (RM) for the validation of OC/EC separation is an important basis for further study. Previous RMs were mainly based on ambient air sampling, which could not provide traceability of OC and EC concentration. To develop traceable RMs with known OC/EC contents, our study applied an improved aerosol generation and mixing technique, providing uniform deposition of particles on quartz filters. To generate OC aerosol with similar pyrolytic property of ambient aerosol, both water soluble organic carbon (WSOC) and water insoluble organic carbon (WIOC) were used, and amorphous carbon was selected for EC surrogate. The RMs were analyzed using different protocols. The homogeneity within the filter was validated, reaching below 2%. The long-term stability of RMs has been validated with RSD ranged from 1.7%-3.2%. Good correlation was observed between nominal concentration of RMs with measured concentration by two protocols, while the difference of EC concentration was within 20%. The results indicated that the newly developed RMs were acceptable for the calibration of OC and EC, which could improve the accuracy of carbonaceous aerosol measurement. Moreover, the laboratory-generated EC-RMs could be suitable for the calibration of equivalent BC concentration by Aethalometers.

Seafood traceability program design: Examination of the United States' Seafood Import Monitoring Program.

The United States' current Seafood Import Monitoring Program (SIMP) and a potential extension are undergoing review, yet quantitative evaluation of the current program is lacking. The SIMP is a traceability program aimed at reducing imports of seafood products that are of illegal, unreported, and unregulated (IUU) origin or associated with seafood fraud. We conducted a quantitative examination of the SIMP's current scope and design by synthesizing publicly available trade data along with measures of IUU fishing and seafood mislabeling. We found prioritized shipments amounted to 33% of 2016 imported tonnage. The SIMP species groups had higher IUU scores and mislabeling rates relative to non-SIMP groups, but the difference was consistent with random prioritization suggesting potential benefits from program expansion. Furthermore, two-thirds of imported volume lacked a mislabeling rate and 5% lacked species information, underlining the urgent need for improved open-access data on globalized seafood supply chains.

Digital transition in pathology lab: a survey from the Lombardy region.

Objective: Digital pathology is an opportunity to revise the routine and old artisanal workflow, moving to standard operating procedures, quality control and reproducibility. Here the results of a survey promoted by the Coordinamento della Medicina di Laboratorio (CRC Med Lab) of the Lombardy region in Italy are reported to shed light on the current situation of digital adoption in the country. Methods: The survey composed of 58 questions was sent to 60 pathology laboratories. The results were collected and most significant answers were reported and discussed. Results: Answers were received from 57 (95%) laboratories, a minority organized in spoke-hub networks (16%) with a centralized processing phase (11%). Hybrid manual/computer-assisted traceability was prevalent (36%), with QR/barcode labeling starting within the pathology lab (23%). Different laboratory information systems (LIS) were employed, mostly with alert functions and/or multimedial file attachments (56% and 46%, respectively). The majority opted for a semi-automated tracking management (44, 77%) and 18 centers (32%) were partly digitizing the routine (¾ scanning < 25% of slides). Whole slide images were retained for 3.7 years in average; in-house blocks/slides archiving was still preferred (30, 53%), with 1838 (±1551) and 1798 (±1950) days (5 years) internal permanence for blocks and slides that are stored in out-source (mean turnaround time for return on-demand 3.7±2.1, range 1-10 days). Conclusions: The advantages of digital pathology must be balanced against the challenges faced in the structural revision of the pathology workflow. This regional scouting can represent the foundation to build an efficient and connected digital pathology system in the territory.

Pattern recognition of multiple metal ions using fluorescent Perylenyl nanoaggregates and application in food traceability.

Metal ions (MIs) identification is essential for the safety assessment, traceability and authentication of food. Most current approaches for detecting MIs are difficult to reconcile the simplicity, sensitivity and stability simultaneously. In this work, we proposed a novel strategy for discriminating MIs based on fluorescent supramolecular nanoaggregates (SNAs). In the presence of MI, perylene diimide derivatives (PDI)-based SNAs could be formed through the multiple non-covalent interactions between them including electrostatic, coordination and π-π interactions. With the assistance of discriminant analysis (LDA), different MIs (Hg2+, Ag+, Cd2+, Fe3+, Cr3+, Fe2+, Zn2+, Cu2+ and Pb2+) were successfully identified at three different concentration levels. It featured good quantitative sensing abilities in buffer solutions and practical samples. Furthermore, a water-quality evaluation model was successfully constructed for the distinction of different sources of drinking water, and the fluorescence array sensor technology was applied for the first time to the geographical traceability of apples.

Supporting traceability and biosecurity in the sheep and goat industries in NSW: understanding barriers to implementing electronic identification.

Efficient traceability is paramount for Australia's biosecurity system and market access. Electronic identification (eID) offers higher traceability performance than that achieved with visual and mob-based identification used for the sheep and goats National Livestock Identification System (NLIS). The current study aims to gain an understanding of the barriers and motivations of using eID for NLIS sheep and goats in New South Wales (NSW) and to provide recommendations to support the transition to eID. A social research study using a mixed-methods approach was used through semi-structured interviews and a cross-sectional epidemiological and behavioural study among sheep and goat producers. The COM-B behaviour change model based on capabilities, opportunities and motivations was used as a framework for the study. A total of 269 participants informed this study: 25 interviews were conducted with government, industry and private stakeholders, and 184 and 58 sheep and goat producers participated in the cross-sectional study, respectively. The study identified poor understanding of the purpose and importance of NLIS among producers, with over two-thirds not supporting eID implementation. The main barriers identified to the eID implementation were practical, including costs, technology quality and increased workload. Attitudinal, behavioural and knowledge barriers, such as the perception of the current system providing efficient traceability and the perceived lack of benefits of eID were also identified. This study provides an in-depth analysis of practices and perceptions of stakeholders and producers on sheep and goat traceability and recommendations to address barriers identified, based on education and appropriate behavioural and technical support.

Design of agricultural product traceability system based on blockchain and RFID.

Ensuring the traceability of agricultural products is essential for quality control and food safety. Recent technological advances have provided new ways to enhance traceability systems. This study aims to use blockchain technology, centralized database and RFID tags to develop a secure agricultural product traceability system, retain the detailed information of agricultural products traceability, ensure that the summary information of agricultural products on the chain cannot be modified, and optimize the SM3 algorithm to effectively summarize the traceability data and improve the efficiency of the system. The aggregated data is time-stamped, recorded on the blockchain, and written into an RFID tag. The optimization of the SM3 algorithm improved the efficiency by 30% and reduced the execution time of 192-byte messages to 210µs. The system ensures accurate linking of traceability data through secure data retention and unalterable summaries on the blockchain. The integrated use of blockchain, centralized database and RFID technology, as well as the enhanced SM3 algorithm, allows the system to meet the standards for data accuracy and performance requirements in agricultural traceability applications.

Blockchain implementation for food safety in supply chain: A review.

Food safety has emerged as the topmost priority in the current fast-paced food industry era. According to the World Health Organization, around 600 million people, approximately 1 in 10 individuals worldwide, experience illness due to contaminated food consumption, resulting in nearly 0.42 million fatalities annually. The recent development in software and hardware sectors has created opportunities to improve the safety concerns in the food supply chain. The objective of this review is to explain the fundamentals of blockchain and its integration into the supply chain of various food commodities to enhance food safety. This paper presents the analysis of 31 conceptual works, 10 implementation works, 39 case studies, and other investigations in blockchain-based food supply chain from a total of 80 published papers. In this paper, the significance of adapting conceptual ideas into practical applications for effectively tracing food commodities throughout the supply chain has been discussed. This paper also describes the transformative role of blockchain platforms in the food industry, providing a decentralized and transparent ledger to access real-time and immutable records of a product's journey. In addition, both the positive impacts and challenges associated with implementing blockchain technology in the food supply chain have been evaluated. In summary, the blockchain-based food supply chains offer greater transparency, traceability, and trust, ultimately resulting in higher standards of food safety and quality.

Development of purity certified reference materials to establish metrological traceability for the measurement of nitroimidazoles in agricultural products.

It is of significant importance to public health that reliable monitoring of nitroimidazoles be conducted, while certified reference materials (CRMs) are essential for accurate and reliable detection. A project has been initiated with the objective of developing nitroimidazole purity CRMs to ensure that results from nationwide monitoring laboratories for nitroimidazoles in antibiotic residues can be compared and traced. The candidates were successively characterized in terms of their structure by means of infrared (IR) spectroscopy and mass spectrometry (MS). The mass balance (MB) method and the quantitative nuclear magnetic resonance (qNMR) method were utilized to determine the purity of nitroimidazoles with remarkable accuracy. Furthermore, a methodical investigation was conducted on homogeneity, stability, and uncertainty. Six nitroimidazole purity CRMs, including tinidazole (GBW09252), secnidazole (GBW09286), ronidazole (GBW09288), metronidazole (GBW(E)090755), dimetridazole (GBW(E)090819), and ornidazole (GBW(E)090820), were finally manufactured following authorization from China's State Administration for Market Regulation (SAMR). By using these CRMs, it is possible to improve the traceability, accuracy, and comparability of nitroimidazole measurements in a range of agricultural products, protecting public health.

Preliminary study on the geographical origin of Chinese 'Cuiguan' pears using integrated stable isotope and multi-element analyses.

Distinguish the geographical origin of the pear is important due to the increasingly valued brand protection and reducing the potential food safety risks. In this study, the profiles of stable isotopes (δ13C, δ15N, δ2H, δ18O) and the contents of 16 elements in pear peer from four production areas were analyzed. The δ13C, δ15N, δ2H, δ18O and 12 elements were significantly different (p < 0.05) in the four production areas. Chemometrics analysis including principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA) and linear discriminant analysis (LDA) were exploited for geographical origin classification of samples. OPLS-DA analysis showed that crucial variables (δ13C, δ18O, δ2H, Ni, Cd, Ca, δ15N, Sr and Ga) are more relevant for the discrimination of the samples. OPLS-DA achieved pear origin accuracy rates of 87.76 % by combining stable isotope ratios and elemental contents. LDA had a higher accuracy rate than OPLS-DA, and the LDA analysis showed that the original discrimination rate reached to 100 %, while the cross-validated rate reached to 95.7 %. These studies indicated that this method could be used to assess the geographical discrimination of pear from different producing areas and could potentially control the fair trade of pear in fruit markets.

Isotope-dilution-LC-MS/MS candidate reference measurement procedure for cefepime in human serum.

Background: Reference measurement procedures are an essential element in the standardization and comparability of analytical measurement results in laboratory medicine. No LC-MS/MS-based reference measurement procedure for cefepime in serum has been published previously. Materials and methods: An isotope-dilution based two-dimensional LC-MS/MS reference measurement procedure for cefepime concentrations in human serum was developed and tested. The value assignment of unknown samples is based on a defined measurement series validation. Six unknown samples can be measured per series. Pass criteria for the run and the samples were determined empirically based on a performance evaluation. For this purpose, a between-run determination of five runs of the defined measurement series with six cefepime samples was carried out and evaluated. The goal was to define rigorous, realistic target limits and minimize measurement uncertainty. The final defined target limits are used for series-based validation and value assignment. The results for the six unknown samples are provided with the associated measurement uncertainty for this series. Results: The developed and extensively studied measurement procedure for the quantification of cefepime in serum was found to be practicable and fit for its purpose. The between-run mean imprecision of the six cefepime samples was ≤ 2.0 %, for the QCs it was ≤ 2.3 % and the between-run mean inaccuracy of the QCs was within ± 1.1 %. Conclusion: The novel isotope-dilution-LC-MS/MS measurement procedure in accordance to ISO 15193 can be recommended as candidate reference measurement procedure for the value assignment of cefepime concentrations in human serum.

Tracking perishable foods in the supply chain using chain of things technology.

Modern food supply chains are intrinsically sophisticated due to their multi-participant and multi-echelon structure, which are challenging to handle high turbulent business environment. The development of Perishable Food Supply Chains (PFSC) has to be strong enough to manage any type of disruptions in the food industry. At the same time, the food processing industry must also take responsibility for the social and environmental consequences of their deeds. This has further led to performance deterioration and intensified design complexity. Recently, digitalization and Blockchain technology (BCT) have brought unfathomed rebellions in PFSC. Despite the potential and market hype, the application of BCT to track the perishable products and status of in-transit shipments is still a challengingtask for the food industry due to privacy and security issues, restricted transactional and scalability performance, deficiency of industry standards and managerial abilities, etc. However, integrating the BCT with the eventual benefits of the Internet of Things (IoT) (i.e., Chain of Things (CoT)) increases the performance of good traceability in any supply chain. The proposed CoT-based Track and Trace system (CoT-TTS) employs a set of IoT devices, BCT, and Adaptive Neuro-Fuzzy Inference System (ANFIS). The performance of CoT-TTS is evaluated through a case study using an EOSIO platform. The effectiveness of the proposed system is evaluated in terms of depth, breadth, access, and precision of the transactions.

Toward food safety-driven process design: a systematic review and research agenda.

Process design strategies are important to prevent or reduce food safety risks in production systems. In this sense, the Codex Alimentarius presents a set of principles for good hygiene practices to guide food producers. However, studies in food safety often focus on analyzing and controlling implemented production processes without a policy of designing them with a preventive logic, leading to resource misallocation and noncompliance. This study aims to gather and analyze techniques, drivers, challenges, and research opportunities for food safety-driven process design. A systematic literature review was carried out following three steps: (i) Data collection, including 52 studies; (ii) Bibliometric analysis; and (iii) Content analysis, identifying techniques, drivers, challenges, and research opportunities. Three main themes in the subject were identified: process assessment models, risk assessment, and whole-chain traceability. Eleven design techniques were identified and compared according to their typology, structure, and coverage of themes addressed by the Codex Alimentarius. There is a gap in techniques addressing employee competence and personal hygiene. We suggest developing a tool encompassing the Codex Alimentarius good hygiene practices themes in process design to guide food safety-driven process development.

A Microbial Phenomics Approach to Determine Metabolic Signatures to Enhance Seabream Sparus aurata Traceability, Differentiating between Wild-Caught and Farmed.

BACKGROUND: The need for efficient and simplified techniques for seafood traceability is growing. This study proposes the Biolog EcoPlate assay as an innovative method for assessing wild and farmed Sparus aurata traceability, offering advantages over other molecular techniques in terms of technical simplicity. METHODS: The Biolog EcoPlate assay, known for its high-throughput capabilities in microbial ecology, was utilized to evaluate the functional diversity of microbial communities from various organs of S. aurata (seabream) from the Mediterranean area. Samples were taken from the anterior and posterior gut, cloaca swabs and gills to distinguish between farmed and wild-caught individuals. The analysis focused on color development in OmniLog Units for specific carbon sources at 48 h. RESULTS: Gills provided the most accurate clusterization of sample origin. The assay monitored the development of color for carbon sources such as α-cyclodextrin, D-cellobiose, glycogen, α-D-lactose, L-threonine and L-phenylalanine. A mock experiment using principal component analysis (PCA) successfully identified the origin of a blind sample. Shannon and Simpson indexes were used to statistically assess the diversity, reflecting the clusterization of different organ samples; Conclusions: The Biolog EcoPlate assay proves to be a quick, cost-effective method for discriminate S. aurata traceability (wild vs. farmed), demonstrating reliable reproducibility and effective differentiation between farmed and wild-caught seabream.

Tracing pistachio nuts' origin and irrigation practices through hyperspectral imaging.

Pistachio trees have become a significant global agricultural commodity because their nuts are renowned for their unique flavour and numerous health benefits, contributing to their high demand worldwide. This study explores the application of Hyperspectral Imaging (HSI) and Machine Learning (ML) to determine pistachio nuts' geographic origin and irrigation practices, alongside predicting essential commercial quality and yield parameters. The study was conducted in two Spanish orchards and employed HSI technology to capture spectral data. It used ML models like Partial Least Squares (PLS), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost) for analysis. The results demonstrated high accuracy in classifying pistachios based on origin, with accuracies exceeding 94%, and in assessing water content and colour pigments, where both PLS and SVM models achieved 99% accuracy. The research highlighted distinct spectral signatures associated with different irrigation treatments, particularly in the Near-Infrared (NIR) region, with PLS showing an accuracy of 92%. However, challenges were noted in predicting fruit orientation, while predicting height location within the tree was more successful, reflecting clearer spectral distinctions. Regression models also showed promise, particularly in predicting yield (R2 = 0.89 with PLS) and percentage of blank nuts (R2 = 0.71 with PLS). The correlation analysis revealed key insights, such as an inverse relationship between blank nuts and yield, and a strong correlation between yield and split nuts. Despite challenges in predicting fruit orientation, the research showed promising results in forecasting yield and commercial quality factors, indicating the effectiveness of spectral analysis in optimising pistachio production and sustainability.

Research on the mechanisms of 2D road runoff pollution migration and the influence of pipeline overflow onto roads.

In this paper, a novel numerical model capable of high-resolution, accurate simulation of the accumulation, wash-off, and migration of nonpoint source (NPS) pollutants on roads is proposed, effectively addressing the challenge of limited pipe network data for high-density urban building communities. This approach is based on a 1D-2D hydrodynamic and water quality dynamic bidirectional coupling model: GAST-SWMM. The calculation accuracy of the GAST two-dimensional road NPS wash-off model is validated via comparison with experimental data. The obtained Nash-Sutcliffe efficiency (NSE) is greater than 0.8. Moreover, the model was used to simulate the NPSs in a densely populated urban region of Xi'an, China, lacking building community pipeline data. The NPS pollutant transport and fate under the influence of both road runoff and the building community hydrodynamic water quality during rainfall events with a specific return period were examined. The proposed model can effectively and accurately replicate the accumulation and removal of NPS pollutants on a two-dimensional road and their dynamic interaction with the drainage network. With increasing rainfall return period, the peak time of the surface contaminant total load is postponed. The maximum surface pollutant load durations during rainfall events with 2-, 10-, and 50-year return periods are 60, 75, and 80 minutes, respectively. During the peak surface pollutant load time, the overflow pollutant fraction can exceed 85% for a 50-year rainfall return period. The simulation method presented in this paper accurately captures the spatial and temporal variations in NPS pollutants in densely populated urban areas, even when pipe network data for building communities are lacking. This method offers valuable technical assistance for urban environmental management and water quality protection.

New concept for control material in glucose point-of-care-testing for external quality assessment schemes.

OBJECTIVES: Until now, the external quality assessment (EQA) of glucose point-of-care testing (POCT) has lacked a high quality, suitable and commutable control material to assess measurement accuracy. Here we present a concept for determining the accuracy of glucose measurements, which uses human whole blood and does not require stabilising agents. METHODS: This new generation of quality control samples uses a bead that contains a specific amount of glucose. The bead is then dissolved in a whole blood matrix by the EQA participant immediately before the POCT. We analysed its suitability as an EQA material with respect to its reproducibility, homogeneity and stability, and applied it in an EQA pilot study. The glucose target value was determined using the reference measurement procedure and served as an evaluation criterion for the accuracy of the EQA survey results. RESULTS: The homogeneity and stability of the new control material fulfilled the quality requirements of ISO 17043. Based on the reference measurement value for glucose, the results of the pilot EQA scheme showed a pass rate of 84.6 % for the participating POCT devices. The acceptance limit was a 15 % permitted deviation from the target value according to Rili-BAEK. All of the device collectives deviated from the target value by 0-4.4 % with the exception of one device type, which deviated by 21 %. CONCLUSIONS: The new concept offers, for the first-time, whole blood-based trueness controls for glucose POCT analysis for external quality assurance. The concept does not require the addition of any stabilising reagent and is easy to use.

Tracing Microplastic Aging Processes Using Multimodal Deep Learning: A Predictive Model for Enhanced Traceability.

The aging process of microplastics (MPs) affects their surface physicochemical properties, thereby influencing their behaviors in releasing harmful chemicals, adsorption of organic contaminants, sinking, and more. Understanding the aging process is crucial for evaluating MPs' environmental behaviors and risks, but tracing the aging process remains challenging. Here, we propose a multimodal deep learning model to trace typical aging factors of aged MPs based on MPs' physicochemical characteristics. A total of 1353 surface morphology images and 1353 Fourier transform infrared spectroscopy spectra were achieved from 130 aged MPs undergoing different aging processes, demonstrating that physicochemical properties of aged MPs vary from aging processes. The multimodal deep learning model achieved an accuracy of 93% in predicting the major aging factors of aged MPs. The multimodal deep learning model improves the model's accuracy by approximately 5-20% and reduces prediction bias compared to the single-modal model. In practice, the established model was performed to predict the major aging factors of naturally aged MPs collected from typical environment matrices. The prediction results aligned with the aging conditions of specific environments, as reported in previous studies. Our findings provide new insights into tracing and understanding the plastic aging process, contributing more accurately to the environmental risk assessment of aged MPs.