The steady increase in food falsification, which has caused large economic losses and eroded consumers’ trust, has become a pressing issue for producers, researchers, governments, consumers and other stakeholders Tracking and authenticating the food supply chain to understand provenance is critical with a view to identifying and addressing sources of contamination in the food supply chain worldwide One way of solving traceability issues and ensuring transparency is by using blockchain technology to store data from chemical analysis in chronological order so that they are impossible to manipulate afterwards This review examines the potential of blockchain technology for assuring traceability and authenticity in the food supply chain It can be considered a true innovation and relevant approach to assure the quality of the third step of the analytical processes: data acquisition and management

Future challenges on the use of blockchain for food traceability analysis

In the last decade, the use of multivariate statistical techniques developed for analytical chemistry has been adopted widely in food science and technology. Usually, chemometrics is applied when there is a large and complex dataset, in terms of sample numbers, types, and responses. The results are used for authentication of geographical origin, farming systems, or even to trace adulteration of high value-added commodities. In this article, we provide an extensive practical and pragmatic overview on the use of the main chemometrics tools in food science studies, focusing on the effects of process variables on chemical composition and on the authentication of foods based on chemical markers. Pattern recognition methods, such as principal component analysis and cluster analysis, have been used to associate the level of bioactive components with in vitro functional properties, although supervised multivariate statistical methods have been used for authentication purposes. Overall, chemometrics is a useful aid when extensive, multiple, and complex real-life problems need to be addressed in a multifactorial and holistic context. Undoubtedly, chemometrics should be used by governmental bodies and industries that need to monitor the quality of foods, raw materials, and processes when high-dimensional data are available. We have focused on practical examples and listed the pros and cons of the most used chemometric tools to help the user choose the most appropriate statistical approach for analysis of complex and multivariate data.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/1541-4337.12341

Trends in Chemometrics: Food Authentication, Microbiology, and Effects of Processing

An overview of multivariate qualitative methods for food fraud detection

Background Food security can benefit from the technology's transparency, relatively low transaction costs and instantaneous applications. A blockchain is a distributed database of records in the form of encrypted blocks, or a public ledger of all transactions or digital events that have been executed and shared among participating parties and can be verified at any time in the future. Generally, the robust and decentralized functionality of the blockchain is used for global financial systems, but it can easily be expanded to contracts and operations such as tracking of the global supply chain. In the precision agriculture context, Information and Communications Technology can be further implemented with a blockchain infrastructure to enable new farm systems and e-agriculture schemes. Results The purpose of this review is to show a panorama of the scientific studies (enriched by a terms mapping analysis) on the use of blockchain in the agri-food sector, from both an entirely computational and an applicative point of view. As evidenced by the network analysis, the reviewed studies mainly focused on software aspects (e.g. the architecture and smart contracts). However, some aspects regarding the different blockchain knots (computers always connected to the blockchain network) having the role to store and distribute an updated copy of each block in a food supply-chain, result of crucial importance. Conclusion These technologies appear very promising and rich of great potential showing a good flexibility for applications in several sectors but still immature and hard to apply due to their complexity. © 2019 Society of Chemical Industry.

A review on blockchain applications in the agri-food sector.

Class-modelling in food analytical chemistry: Development, sampling, optimisation and validation issues – A tutorial

Food authentication is a rapidly growing field due to increasing public awareness concerning food quality and safety. This review presents critically the analytical techniques which are used for authenticity assessment, explaining how and why they give plausible solutions. Classification of different methodologies is based on authenticity indicators providing insight into future developments. Analytical breakthroughs and novel techniques that emerged recently are discussed, along with their applications on food authentication. We have discussed current limits and gaps, related to informatics needs for data analysis of large quantities. Reporting standards and reference database are elaborated indicating urgent needs for the progress of this field. A scientometric evaluation highlighted the research trends and emerging approaches of this evolving field. Popular analytical techniques are commented, while the potential of the field is depicted in the temporal evolution of the research output focusing on geographical distribution of research activity and preferred journals used for dissemination.

/pdf/food-authentication-techniques-trends-emerging-approaches-4zevpnzap6.pdf

Food authentication: Techniques, trends & emerging approaches

Food authentication is analytical process that validates label information about the food origin and production process. This review discusses emerging food authenticity indicators including rare earth elements, metabolic profiles, sensory profile evaluation, and microbial fingerprinting. A scientometric evaluation that highlights research trends and emerging approaches of this evolving field is presented. We analyzed and provided an insight into most commonly studied food types and drinks and highlighted the most promising authenticity markers for each major group. Finally, we discussed the data explosion that is emerging and discussed the developing trends in the field. The future of food authentication lies in Big Data since we are already collecting and analyzing huge amounts of data that converge from multiple sources. Big Data Analytics will include standardization of experiments, study design workflows, and of data reporting. Emerging data analytical tools will include integration of geographic information systems with climate information systems and metabolomics databases for precise spatio-temporal identification of food origin.

Aristidis S. Tsagkaris

Papers

Food authentication: Techniques, trends & emerging approaches

Food authentication: state of the art and prospects

Detection of Food Processing Techniques