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This study (open access) builds upon previously published work.  The authors expand the scope of multiplex digitalPCR (dPCR) analysis for undeclared GM soy to simultaneously check for 19 different GM events and the lectin (Le1) endogene, and proved the method’s transferability to a popular commercial dPCR platform.

They used a nanowell plate-based all-in-one dPCR system, the QIAGEN QIAcuity One. The method used four 5-plex assays, taking advantage of the platform’s multiple fluorescence detection channels.  DNA was extracted by the cetyltrimethylammonium bromide (CTAB) method, with RNase-A and proteinase-K for removal of RNA and protein, respectively, as described in Annex A.3 of ISO21571:2005.  Quantification by simplex and multiplex assays was compared by testing CRM solutions containing single GM events.  The authors report that all four 5-plex assays showed results comparable with simplex assays

They report that the methods complied with the minimum performance requirements in terms of specificity, trueness, precision, sensitivity and dynamic range, making them suitable for use in routine detection and quantification of GM crops.

They conclude that approach represents a significant step forward by providing discriminative quantification of a large number of targets. The use of a commercial system prooves that quantitative multiplexing can become time and cost-effective, and they believe that their approach is particularly well suited to regulatory compliance testing. Sample compartmentalization, temperature cycling, and fluorescence detection are all performed automatically on the same machine, greatly simplifying the workflow and minimizing hands-on time. The experimental protocol requires no specialized sample handling, allowing it to be performed by operators familiar with qPCR workflow without additional training.

Photo by Meredith Petrick on Unsplash

This work, originally presented at an Institute of Electrical and Electronic Engineers conference and now published in an IEEE journal (purchase required), provides an example of how a small team of researchers can develop a bespoke digital traceability system for the Agri-Food industry.  This provides an alternative approach to buying one of the distributive ledger systems available from large commercial software vendors.

The researchers developed a decentralized system for the agrifood supply chain that allows product traceability and quality assurance. System decentralization and privacy preservation were enabled through the combination of Self-Sovereign Identity (SSI), Decentralized Identifiers (DIDs), and Verifiable Credentials (VCs). DIDs provide stakeholders with complete control, eliminating the need for centralized identity providers. Role-based access control is facilitated through VC-Role, which defines the permissions of actors, and VC-Access, which ensures secure interactions with private blockchain channels.

The publication includes a description of the system architecture, DID and VC integration for access control, and a discussion of the QA requirements of the food industry.

The authors conclude that their system promotes traceability and ensures tamper-proof records of product quality. A proof of concept demonstrates the feasibility and potential impact of this approach in improving quality assurance.

The final report has been published from the German “DIGICHECK” project, which aims to strengthen and verify Organic traceability by utilising Internet-of-Things sensors and digital traceability systems.

The project aimed to achieve

1. The digital collection of real-time land, yield and certification data (from certifiers) and product transaction data (from companies of trading, processing, etc.) as well as the linking of this data as information for authorised users;
2. the calculation of mass balances along product chains calculated from land, income and transactions;
3. the use and linking of geographical information systems (GIS) and data collected by sensors to the certification data in order to provide control bodies with additional tools for their control activities, including independently of an on-the-spot visit;
4. the optimisation of control activities and quality assurance measures along the cereal product chain through the exchange of information between the operators involved;
5. clarifying which instruments and measures are permitted under the EU Organic Regulation and the German Organic Farming Act and could be implemented as required;
6. the evaluation of which tools can be usefully used by control authorities and which information should be made available in the event of fraud or monitoring;
7. the evaluation of the extent to which data can be evaluated for statistical purposes.

 Registration is now open for a free online conference, run in partnership between the UK Food Standards Agency and the University of Sheffield, on Monday 9 November 2020 as part of the Economic and Social Research Council’s (ESRC) Festival of Social Science.

The COVID 19 outbreak has necessitated a move away from more traditional data collection methods and accelerated the innovative use of digital data. In partnership with the University of Sheffield, this virtual half-day event will demonstrate how digital data collection and analysis can inform our understanding of food, and outline key findings related to the digitalisation of food behaviours.  

It will cover the recent review of the FSA flagship survey, Food and You, digital self-report methods on handwashing behaviour and key findings from recent social media analysis, including COVID-19 trends in food behaviour.    

The event offers an excellent opportunity for anyone in the social science community to hear about how social science directly informs real life policy-making in a government context under rapidly changing circumstances. As well as learning about the work and priorities of the FSA and international colleagues, virtual panel sessions will provide an opportunity to discuss ideas with experts from academia, industry and policy.  

To book your place, please register using Eventbrite.