Traceability from a European perspective

Emerging Perspectives of Blockchains in Food Supply Chain Traceability Based on Patent Analysis

In the field of blockchain (BC) technology application in the food supply chain (FSC), a patent portfolio is collected, described, and analyzed using Latent Dirichlet Allocation (LDA) modeling, with the aim of obtaining insight into technology trends in this emerging and promising field. A patent portfolio consisting of 82 documents was extracted from patent databases using PatSnap software. The analysis of latent topics using LDA indicates that inventions related to the application of BCs in FSCs are patented in four key areas: (A) BC-supported tracing and tracking in FSCs; (B) devices and methods supporting application of BCs in FSCs; (C) combining BCs and other ICT technologies in FSC; and (D) BC-supported trading in FSCs. Patenting of BC technology applications in FSCs started during the second decade of the 21st century. Consequently, patent forward citation has been relatively low, while the family size confirms that application of BCs in FSCs is not yet widely accepted. A significant increase in the number of patent applications was registered after 2019, indicating that the number of potential users in FSCs is expected to grow over time. The largest numbers of patents originate from China, India, and the US.

Blockchain-Based Traceability Architecture for Mapping Object-Related Supply Chain Events

Supply chains have evolved into dynamic, interconnected supply networks, which increases the complexity of achieving end-to-end traceability of object flows and their experienced events. With its capability of ensuring a secure, transparent, and immutable environment without relying on a trusted third party, the emerging blockchain technology shows strong potential to enable end-to-end traceability in such complex multitiered supply networks. This paper aims to overcome the limitations of existing blockchain-based traceability architectures regarding their object-related event mapping ability, which involves mapping the creation and deletion of objects, their aggregation and disaggregation, transformation, and transaction, in one holistic architecture. Therefore, this paper proposes a novel 'blueprint-based' token concept, which allows clients to group tokens into different types, where tokens of the same type are non-fungible. Furthermore, blueprints can include minting conditions, which, for example, are necessary when mapping assembly processes. In addition, the token concept contains logic for reflecting all conducted object-related events in an integrated token history. Finally, for validation purposes, this article implements the architecture's components in code and proves its applicability based on the Ethereum blockchain. As a result, the proposed blockchain-based traceability architecture covers all object-related supply chain events and proves its general-purpose end-to-end traceability capabilities of object flows.

Differentiation of meat species of raw and processed meat based on polar metabolites using 1H NMR spectroscopy combined with multivariate data analysis

Meat species of raw meat and processed meat products were investigated by 1H NMR spectroscopy with subsequent multivariate data analysis. Sample preparation was based on aqueous extraction combined with ultrafiltration in order to reduce macromolecular components in the extracts. 1H NMR data was analyzed by using a non-targeted approach followed by principal component analysis (PCA), linear discrimination analysis (LDA), and cross-validation (CV) embedded in a Monte Carlo (MC) resampling approach. A total of 379 raw meat samples (pork, beef, poultry, and lamb) and 81 processed meat samples (pork, beef, poultry) were collected between the years 2018 and 2021. A 99% correct prediction rate was achieved if the raw meat samples were classified according to meat species. Predicting processed meat products was slightly less successful (93 %) with this approach. Furthermore, identification of spectral regions that are relevant for the classification via polar chemical markers was performed. Finally, data on polar metabolites were fused with previously published 1H NMR data on non-polar metabolites in order to build a broader classification model and to improve prediction accuracy.

Food Traceability as an Element of Sustainable Consumption-Pandemic-Driven Changes in Consumer Attitudes

A conscious approach to the issue of food traceability on the part of consumers is essential for making rational food purchases, which in turn contributes to sustainable consumption and globally, is an element of sustainable development. The study aims to assess the changes in consumers' buying behaviors in the context of food traceability before and during the COVID-19 pandemic, as well as the impact of sociodemographic factors on those changes. Therefore, an online survey was conducted on a sample of 1000 respondents who were Polish food consumers. The study covered aspects related to the traceability of food by consumers before and during the pandemic. The results allowed for positive verification of the H1: Polish consumers attitudes related to food buying process changed during the COVID-19 pandemic. The results didn't allow for fully positive verification of the H2: Sociodemographic factors significantly influence Polish consumers attitudes to the food shopping during COVID-19 period compared to pre-pandemic period. The significant influence was supported in almost all (in 6 out of 8) analyzed aspects in case of age, education, and place of residence. However, in case of gender it was confirmed only in terms of two out of eight aspects: choosing product of national origin and using the online form of ordering purchases.

Genome-wide selection of discriminant SNP markers for breed assignment in indigenous sheep breeds

The assignment of an individual to the true population of origin is one of the most important applications of genomic data for practical use in animal breeding. The aim of this study was to develop a statistical method and then, to identify the minimum number of informative SNP markers from high-throughput genotyping data that would be able to trace the true breed of unknown samples in indigenous sheep breeds. The total numbers of 217 animals were genotyped using Illumina OvineSNP50K BeadChip in Zel, Lori-Bakhtiari, Afshari, Moqani, Qezel and a wild-type Iranian sheep breed. After SNP quality check, the principal component analysis (PCA) was used to determine how the animals allocated to the groups using all genotyped markers. The results revealed that the first principal component (PC1) separated out the two domestic and wild sheep breeds, and all domestic breeds were separated from each other for PC2. The genetic distance between different breeds was calculated using FST and Reynold methods and the results showed that the breeds were well differentiated. A statistical method was developed using the stepwise discriminant analysis (SDA) and the linear discriminant analysis (LDA) to reduce the number of SNPs for discriminating 6 different Iranian sheep populations and K-fold cross-validation technique was employed to evaluate the potential of a selected subset of SNPs in assignment success rate. The procedure selected reduced pools of markers into 201 SNPs that were able to exactly discriminate all sheep populations with 100% accuracy. Moreover, a discriminate analysis of principal components (DAPC) developed using 201 linearly independent SNPs revealed that these markers were able to assign all individuals into true breed. Finally, these 201 identified SNPs were successfully used in an independent out-group breed consisting of 96 samples of Baluchi sheep breed and the results indicated that these markers are able to correctly allocate all unknown samples to true population of origin. In general, the results of this study indicated that the combined use of the SDA and LDA techniques represents an efficient strategy for selecting a reduced pool of highly discriminant markers.

The role of green logistics management practices, supply chain traceability and logistics ecocentricity in sustainability performance

Purpose

The priority giving to green practices in today's competitive market has made green logistics management practices (GLMPS) a significant driver of organizational performance. The purpose of this study is to explore the influence of GLMPS, logistics ecocentricity and supply chain traceability on sustainability performance.

Design/methodology/approach

The study uses structured questionnaires to gather data from 274 managers of manufacturing firms in Ghana. The partial least square structural equation modeling approach is used to analyze the data to test the proposed hypotheses.

Findings

The results obtained from the analysis indicate that GLMPS positively influence social sustainability and environmental sustainability. However, GLMPS negatively influence business performance. The results further reveal that logistics ecocentricity and supply chain traceability augment GLMPS to achieve significant improvement in both business performance and environmental sustainability through the mediation effect approach.

Originality/value

The study proposes a conceptual framework that tests the combined effect of GLMPs, logistics ecocentricity and supply chain traceability on environmental sustainability, social sustainability and business performance from the Ghanaian perspective.

The Use of Stable Isotope Ratio Analysis to Trace European Sea Bass (D. labrax) Originating from Different Farming Systems

Simple Summary

European sea bass is one of the most economically important fish species in the Mediterranean area. The potential effects of farming systems on the final quality of this product and the recent popular demand for labels to certify the animal rearing origin, which is increasingly used as a marketing tool, have raised the use of analytical techniques that make it possible to differentiate this fish product according to the rearing farming system and authenticate their geographical origin. The aim of this study was to determine whether isotopic ratio mass spectrometry (IRMS) can discriminate farmed European sea bass according to different farming systems (concrete tank inland, sea cages, and extensive methods in valleys or salt works) and geographic origins (different locations scattered throughout Italy). The results of this study showed the viability of δ¹³C and δ¹⁵N to discriminate cultured sea bass from different farming systems (extensive vs. intensive) reared at different geographical sites in Italy. Meanwhile, the measurement of δ¹⁸O and δ²H made it possible to distinguish the geographical origin of the sea bass farmed extensively and intensively (in cages).

Abstract

This study aimed to determine whether isotopic ratio mass spectrometry (IRMS) can discriminate farmed European sea bass according to different farming systems and geographic origins. Dicentrarchus labrax of commercial size from three different rearing systems (concrete tank inland, sea cages, and extensive methods in valleys or salt works) were collected at the trading period (autumn–winter). For each farming type, different locations spread over Italy were monitored. Once the fish were harvested, the muscle and feed were sampled. For both muscle and feed, δ¹³C and δ¹⁵N were measured by continuous flow elemental analyzer isotope ratio mass spectrometry (CF-EA-IRMS) with the goal of discriminating samples based on the rearing system. Additional δ²H and δ¹⁸O measurements of fish samples were performed by continuous flow total combustion elemental analyzer isotope ratio mass spectrometry (CF-TC/EA-IRMS) to track the geographical origin. The measurements of δ¹³C and δ¹⁵N made it possible to discriminate cultured sea bass from different farming systems (extensive vs. intensive) reared at different geographical sites in Italy. Additional information was obtained from δ¹⁸O and δ²H, which enabled the geographical areas of origin of the sea bass farmed extensively and intensively (in cages) to be distinguished.

Traceability in food processing: problems, methods, and performance evaluations-a review

Processed food has become an indispensable part of the human food chain. It provides rich nutrition for human health and satisfies various other requirements for food consumption. However, establishing traceability systems for processed food faces a different set of challenges compared to primary agro-food, because of the variety of raw materials, batch mixing, and resource transformation. In this paper, progress in the traceability of processed food is reviewed. Based on an analysis of the food supply chain and processing stage, the problem of traceability in food processing results from the transformations that the resources go through. Methods to implement traceability in food processing, including physical separation in different lots, defining and associating batches, isotope analysis and DNA tracking, statistical data models, internal traceability system development, artificial intelligence (AI), and blockchain-based approaches are summarized. Traceability is evaluated based on recall effects, TRUs (traceable resource units), and comprehensive granularity. Different methods have different advantages and disadvantages. The combined application of different methods should consider the specific application scenarios in food processing to improve granularity. On the other hand, novel technologies, including batch mixing optimization with AI, quality forecasting with big data, and credible traceability with blockchain, are presented in the context of improving traceability performance in food processing.

Concentration of fifteen elements in herbaceous stems of Ephedra intermedia and influence of its growing soil

Mineral nutrients play important roles in the growth and metabolism of Ephedra intermedia, and are affected by soil factors. Fifteen elements were measured from wild E. intermedia as well as their growing soils using inductively coupled plasma mass spectroscopy to investigate the influences and characteristics of herb elements. The pH, cation exchange capacity, humus and soil mechanical composition were also determined in rhizosphere soils. Results showed that E. intermedia stems contained high N, low P concentrations in macronutrients and high Fe in micronutrients, and enriched N, S, Cl, P and Sr from soils. The 15 herb elements were affected by one or more soil factors, and K, P, Zn, Fe and Mn were important soil elements that influenced the mineral accumulation of E. intermedia. This study was useful for the artificial cultivation of wild E. intermedia.

Food Origin Traceability from a Consumer’s Perspective

The awareness of food origin in the consumers’ perspective has gradually become more significant not only in reference to consumers from highly developed countries but also from emerging ones, which are already on their way from a developing to developed economy. The purpose of the paper is to answer the research question by verifying four hypotheses formulated in the research process. The research question is: "Do the variables which characterize consumers of food products in Poland, including gender, age, education and financial status, affect the aspects related to food traceability, such as identification of the producer, importance of food product features when shopping, importance of the information given on food product packaging and influence of the shopping place and frequency on tracing the food origin?" The paper presents the results, analysis, and conclusions from the study in reference to the four assumed hypotheses related to the above-mentioned research question. The study was carried out on a group of 500 consumers of food products in Poland. The study topic selection is justified by the assumed significance of tracing back a food product’s origin for a consumer who functions in a globalization-based economy; this was confirmed by the subject literature presented in the paper.

The employment of Fourier transform infrared spectroscopy coupled with chemometrics techniques for traceability and authentication of meat and meat products

Meat-based food such as meatball and sausages are important sources of protein needed for the human body. Due to different prices, some unethical producers try to adulterate high-price meat such as beef with lower priced meat like pork and rat meat to gain economical profits, therefore, reliable and fast analytical techniques should be developed, validated, and applied for meat traceability and authenticity. Some instrumental techniques have been applied for the detection of meat adulteration, mainly relied on DNA and protein using polymerase chain reaction and chromatographic methods, respectively. But, this method is time-consuming, needs a sophisticated instrument, involves complex sample preparation which make the method is not suitable for routine analysis. As a consequence, a simpler method based on spectroscopic principles should be continuously developed. Food samples are sometimes complex which resulted in complex chemical responses. Fortunately, a statistical method called with chemometrics could solve the problems related to complex chemical data. This mini-review highlights the application of Fourier-transform infrared spectroscopy coupled with numerous chemometrics techniques for authenticity and traceability of meat and meat-based products.

An ontology-based approach for supply-chain quality control: From a principal–agent perspective

The efficacy of the principal–agent contract in supply-chain quality control depends not only on contract parameters but also such noncontract parameters as cost of a high-quality effort and the diagnostic error of the inspection policy. The noncontract parameters usually fluctuate and are unobservable during contract execution, which may hinder suppliers’ high-quality effort, or, in other words, result in a lower efficacy for the contract. This article proposes an ontology-based approach to facilitating a principal–agent contract by monitoring the contract’s loss of efficacy. The approach consists of ontology-based models and data-centric algorithms. The ontology-based models not only formally represent concepts and relations between concepts involved in predicting whether a contract is efficient, but also organise multichannel data such as news, marketplace reports and industry databases containing information of factors impacting the unobservable noncontract parameters’ fluctuations. Based on the ontology-based models and multichannel data, the data-centric algorithms are developed to predict whether a contract will lose efficacy. We evaluate our approach through case study, simulation and comparison against related approaches to supply-chain quality control. The case study proves that our approach is appropriate. In the simulation evaluation, a combination of our approach and principal–agent contract is more efficient than just a principal–agent contract. The comparison results against related approaches show that our approach is a novel, inexpensive and directly applicable tool for reducing both asymmetric information and moral hazard in supply-chain quality control.

Origin Detection During Food-borne Disease Outbreaks - A Case Study of the 2011 EHEC/HUS Outbreak in Germany

The key challenge during food-borne disease outbreaks, e.g. the 2011 EHEC/HUS outbreak in Germany, is the design of efficient mitigation strategies based on a timely identification of the outbreak's spatial origin. Standard public health procedures typically use case-control studies and tracings along food shipping chains. These methods are time-consuming and suffer from biased data collected slowly in patient interviews. Here we apply a recently developed, network-theoretical method to identify the spatial origin of food-borne disease outbreaks. Thereby, the network captures the transportation routes of contaminated foods. The technique only requires spatial information on case reports regularly collected by public health institutions and a model for the underlying food distribution network. The approach is based on the idea of replacing the conventional geographic distance with an effective distance that is derived from the topological structure of the underlying food distribution network. We show that this approach can efficiently identify most probable epicenters of food-borne disease outbreaks. We assess and discuss the method in the context of the 2011 EHEC epidemic. Based on plausible assumptions on the structure of the national food distribution network, the approach can correctly localize the origin of the 2011 German EHEC/HUS outbreak.

The Use of Mobile Technology in Management and Risk Control in the Supply Chain

The use of mobile technologies is important for Supply Chain Management (SCM) because these technologies allow for a ubiquitous flow of information, higher agility and risk reduction in supply chains. In food markets, these issues are particularly relevant due to food safety risks. The main goal of this paper is to analyze the use of mobile technology for management and risk control in the Brazilian beef supply chain, since Brazil is one of the main producers and beef exporters in the world. The research method was a single case study. Results show the actual level of mobile technology use; drivers and barriers to mobile technology adoption and how mobile technology is applied to beef traceability and risk reduction along the chain. The authors propose a framework that links the issues of mobile technology use for SCM and risk control, considering the context of a developing country such as Brazil.

On the way to functional agro biodiversity: coat colour gene variability in goats

Functional agro biodiversity defines the exploitation of biodiversity to provide ecosystem services, support sustainable agricultural production and benefit the regional and global environment and the public at large (ELN-FAB, 2009; www.eln_fab.eu). Tracking of animal products back to the breed of origin based on their genetic make-up undoubtedly falls in this category. The aim of this paper was to identify and validate a set of single nucleotide polymorphisms (SNPs) in goat coat colour genes, most of which have not been investigated before, to trace five goat populations of the Italian Alps and their product. Several regions of 28 genes influencing coat colour pathways were amplified in eight animals (two per breed). Sequence comparison revealed 48 SNPs and three INDEL (INsertion DELetion). No breed-specific alleles were detected; however, several SNPs showed an uneven frequency distribution between breeds. In BIO, the genotype frequency distribution of a non-synonymous SNP suggested a possible role of TYRP1 in brown eumelanic goat coat colour. A total of 29 independent SNPs in 20 genes were selected and used to allocate 159 minimally related goat samples using STRUCTURE 2.2 and GeneClass 2 software. STRUCTURE 2.2 assigns 99% of individuals to the correct breed considering the prior information on putative breed of origin for each sample and 81% using only the genotypic data. The three algorithms available in GeneClass 2 performed with nearly equal efficiency, with 86% and 87% correct allocations. All the methods yielded an average probability of assignment >0.92 and a specificity index >0.86. Despite their coat colour variability, individuals belonging to ORO were fully assigned, showing that, in the absence of a breed-specific allele tied to coat colour, the best assignment resulted for the most genetically distinct breed. The lowest rate of correct assignment was observed in Verzaschese (73%), not ascertained in the breed panel used in the SNP discovery phase.

Radio frequency identification technologies for livestock management and meat supply chain traceability

Barge, P., Gay, P., Merlino, V. and Tortia, C. 2013. Radio frequency identification technologies for livestock management and meat supply chain traceability. Can. J. Anim. Sci. 93: 23–33. Animal electronic identification could be exploited by farmers as an interesting opportunity to increase the efficiency of herd management and traceability. Although radio frequency identification (RFID) solutions for animal identification have already been envisaged, the integration of a RFID traceability system at farm level has to be carried out carefully, considering different aspects (farm type, number and species of animals, barn structure). The tag persistence on the animal after application, the tag-to-tag collisions in the case of many animals contemporarily present in the reading area of the same antenna and the barn layout play determinant roles in system reliability. The goal of this paper is to evaluate the RFID identification system performance and determine the best practice to apply these devices in livestock management. RFID systems were tested both in laboratory, on the farm and in slaughterhouses for the implementation of a traceability system with automatic animal data capture. For this purpose a complete system for animal identification and tracking, accomplishing regulatory compliance as well as supply chain management requirements, has been developed and is described in the paper. Results were encouraging for identification of calves both in farms and slaughterhouses, while in swine breeding, identification was critical for small piglets. In this case, the design of a RFID gate where tag-to-tag collisions are avoided should be envisaged.

Geographic origins of Korean and Chinese kimchi determined by multiple elements

An elemental analysis was performed on 30 Korean and Chinese kimchi samples in combination with strontium (Sr) isotope ratio measurements to develop a method for tracing the geographic origins of Korean and Chinese kimchi. We found a distinct difference between Korean and Chinese kimchi in such specific elements as K, Na, Ca, Ba, Sr, Zn, Li, and Sc, but no significant difference in the Sr isotope ratio. A comparative analysis was performed with washed kimchi (containing no submaterial) and unwashed kimchi to evaluate the effect of submaterials on the determination of geographic origin. A linear discriminant analysis provided a clear distinction between Korean and Chinese kimchi. The results indicate that combining multi-elemental and statistical analyses has the potential to determine the geographic origins of such processed food as kimchi.

The frequency and distance of movements of pigs and semen between commercial and non-commercial piggeries in New Zealand

AIMS

The study was conducted to identify movement patterns of disease conveyors in the New Zealand pig industry. The principal objective of the study was to identify data relating to the frequency and distance of movements of pigs and semen amongst pig holdings. A secondary objective of the study was to generate criteria suitable for categorisation of different pig breeding or raising operations.

METHODS

Prospective data were collected by a census of all known pig holdings in New Zealand using a mailed-out questionnaire.

RESULTS

The survey yielded 1,477 responses (114 commercial and 1,363 non-commercial pig holdings) for descriptive analysis. Seven farm-types were created to describe typical pig holdings and were based on pig herd inventory, herd type, and participation in the movement of pigs or semen: Commercial genetic supplier, commercial feeder, commercial weaner producer, para-commercial genetic supplier, para-commercial feeder, para-commercial weaner producer, and non-commercial herd. The farm-type with the highest frequency of movements off the piggery was the para-commercial genetic suppliers with a median of 5.3 movements off per month. Commercial feeders had the second highest off farm movement with a median of 4.6 movements per month; these primarily represented movements to an abattoir. The highest frequencies of movements on to a piggery were experienced by commercial genetic suppliers (3.5 per month) and were due to the delivery of semen or replacement gilt/boars. Para-commercial and non-commercial farm-types reported less frequent movement activities both onto and off the piggery compared to their commercial counterparts. Most movements of pigs and semen occurred over distances of less than 100 km.

CONCLUSIONS

The study showed that New Zealand has a relatively small but widely dispersed commercial pig industry with a large number of non-commercial pig holdings and there was a substantial geographic overlap between these industry sectors. Knowledge of the frequency of movements of pigs and semen among different pig farm-types and the distance over which these movements occur helps to assess the likely connectivity between piggeries, abattoirs, and sale yards. However, the study also highlighted the knowledge deficiencies that result in the absence of mandatory livestock identification and tracking schemes.

CLINICAL RELEVANCE

In an industry with substantially more non-commercial pig holdings than commercial pig-holdings, key issues such as biosecurity education, ensuring sufficient veterinary involvement in non-commercial sectors, and building robust systems to ensure border security will remain critical in the effort to keep the pig industry at its current level of high health.