Periodic Reporting for period 1 - SAFFI (Safe Food for Infants in the EU and China)
Berichtszeitraum: 2020-09-01 bis 2022-02-28
SAFFI targets food for EU’s 15 million and China’s 45 million children under the age of three. It aims at developing an integrated approach to enhance the identification, assessment, detection and mitigation of safety risks raised by microbial and chemical hazards all along EU and China infant food chains. This project will focus on infant food as this is a sensitive population and product group, whose cross-cutting nature will allow project outcomes to be transferred to most of the other food sectors. SAFFI is benchmarking the main safety risks through an extensive hazard identification system based on multiple data sources and a risk ranking procedure (WP1). It also develops procedures to improve top-down and bottom-up risk control by combining management options, i) with a range of innovative food processing technologies aimed at mitigating priority risks while preserving other dimensions of product quality (WP2) and, ii) with a panel of high-throughput detection techniques dedicated to improving the monitoring of priority chemical hazards (WP3). SAFFI also aims at discovering unexpected/unknown chemical hazards by non-targeted approaches combining bio-, chemo-analytics and bioinformatics (WP3) and improve risk-based food safety management of biohazards by omics and predictive microbiology (WP4). SAFFI is co-developing and delivering to stakeholders a decision-support system (DSS) to enhance safety control all along the food chain (WP5). This DSS will integrate the databases, procedures and methods described above and will be a framework for a generic DSS dedicated to other food. This overall methodology is going to be implemented in two complementary European and Chinese sides of the project and exemplified for each, with four case studies that were selected to cover priority hazards, main ingredients, processes and control steps of the infant food chain. SAFFI is also setting up training and knowledge transfer activities to foster EU-China harmonization of good practices, regulations, standards and technologies, and is clustering with the DiTECT project (GA N°861915) for continuous upgrade of food safety control.
WP1- In order to enhance hazard identification and risk ranking most relevant hazards for infant food were determined from all potential microbiological and chemical hazards: 32 microbiological hazards and 101 chemical hazards have been identified. Specific characteristics and knowledge rules for these hazards are being collected and stored on a data collection repository. This information can be used to further identify the hazards relevant in specific food products. Knowledge rules and a decision tree to classify the hazards into different empirical rankings was devised. Criteria for microbiological and chemical hazard risk ranking were drafted. Data collected on the microbiological and chemical hazard databases can now be used to develop the risk ranking prototypes for both types of hazards.
WP2- In order to improve hazard control and risk mitigation, SAFFI first focused on the impact of High-Pressure Processing (HPP) on the fate of key chemicals and the behaviour of main pathogens on apple-based fruit puree. Based on the collection of scientific information, a predictive model has already enabled the definition of HPP conditions validating this technology for pasteurization. A meta-analysis identified and quantified the effect of factors determining microbial inactivation in fruit puree while plating-based method enabled to assess sublethal damage due to HPP on major pathogens. Experiments on the impact of HPPs on the chemical hazards of apple-based fruit purees showed that HPPs did not induce the neoformation of HMF, nor the transfer of migrants from the material in contact with food.
WP3- In order to enhance chemical hazard detection and discovery, the different samples that will be collected and analysed in this WP were determined. These include raw material to end products, spiked samples, incurred samples. In order to enhance the targeted surveillance of known priority contaminants, several bio- and chemo-analytic methods have been identified and/or developed. Focus was on high-throughput, cost effective and robust targeted approaches for detection of priority contaminants. Work has been initiated to develop a sample pooling approach on several contaminant/food pairs. In parallel, non-targeted analytical chemistry- and bioassay-based methods for non-suspected/unknown substances have been identified and developed. A quality control and validation structure has been set up which is currently evaluated by partners.
WP4- In order to enhance the detection of microbial hazard and to improve the prediction of their behaviour, the presence, distribution and prevalence of target foodborne was analysed in the samples which have been collected until now. Targeting infant cereals, samples are represented by raw materials, intermediates and final products but also collected from the production environment. So far, the work has been focused on the determination of presence/absence of target pathogens. Collection of relevant metadata will allow an analysis of distribution in time and space. With a view to upgrading predictive models by implementing omics data; preliminary discussions and decisions regarding the experimental plan relating to the stress/adaptation conditions the lethal conditions and the microorganism to test have taken place during the monitoring period.
WP5- In order to proceed to the integration of Decision Support Systems (DSS), the process of collecting data requirements and developing models is ongoing in WP1-4, working directly to the development of models that will be integrated into a single and upgradable DSS. Data profiling was performed to analyse the collected and generated data. This involves the mapping of variables and the creation of metadata, and allows the identification of dependencies and commonalities between datasets. Next, the logistics of building real-world models from this data are explored by developing conceptual and logical data models, using entity relationships and data flow diagrams. Initial data profiling has taken place for two WP, one of which has progressed to the conceptual model development stage.
WP2- In order to improve hazard control and risk mitigation, SAFFI first focused on the impact of High-Pressure Processing (HPP) on the fate of key chemicals and the behaviour of main pathogens on apple-based fruit puree. Based on the collection of scientific information, a predictive model has already enabled the definition of HPP conditions validating this technology for pasteurization. A meta-analysis identified and quantified the effect of factors determining microbial inactivation in fruit puree while plating-based method enabled to assess sublethal damage due to HPP on major pathogens. Experiments on the impact of HPPs on the chemical hazards of apple-based fruit purees showed that HPPs did not induce the neoformation of HMF, nor the transfer of migrants from the material in contact with food.
WP3- In order to enhance chemical hazard detection and discovery, the different samples that will be collected and analysed in this WP were determined. These include raw material to end products, spiked samples, incurred samples. In order to enhance the targeted surveillance of known priority contaminants, several bio- and chemo-analytic methods have been identified and/or developed. Focus was on high-throughput, cost effective and robust targeted approaches for detection of priority contaminants. Work has been initiated to develop a sample pooling approach on several contaminant/food pairs. In parallel, non-targeted analytical chemistry- and bioassay-based methods for non-suspected/unknown substances have been identified and developed. A quality control and validation structure has been set up which is currently evaluated by partners.
WP4- In order to enhance the detection of microbial hazard and to improve the prediction of their behaviour, the presence, distribution and prevalence of target foodborne was analysed in the samples which have been collected until now. Targeting infant cereals, samples are represented by raw materials, intermediates and final products but also collected from the production environment. So far, the work has been focused on the determination of presence/absence of target pathogens. Collection of relevant metadata will allow an analysis of distribution in time and space. With a view to upgrading predictive models by implementing omics data; preliminary discussions and decisions regarding the experimental plan relating to the stress/adaptation conditions the lethal conditions and the microorganism to test have taken place during the monitoring period.
WP5- In order to proceed to the integration of Decision Support Systems (DSS), the process of collecting data requirements and developing models is ongoing in WP1-4, working directly to the development of models that will be integrated into a single and upgradable DSS. Data profiling was performed to analyse the collected and generated data. This involves the mapping of variables and the creation of metadata, and allows the identification of dependencies and commonalities between datasets. Next, the logistics of building real-world models from this data are explored by developing conceptual and logical data models, using entity relationships and data flow diagrams. Initial data profiling has taken place for two WP, one of which has progressed to the conceptual model development stage.
Besides improving targeted detection (WP3) and hazard control (WP2), SAFFI will implement several approaches enabling a real paradigm shift i) to enlarge food safety control to the wide range of unknown chemical hazards that may be at risk for the consumer (WP3) ii) to better predict the behaviour and finally assess the risk related to food-borne pathogens (WP4), iii) to propose broad hazard identification and risk-ranking to define the priority hazard to focus on (WP1). In order to overcome the complexity of food chains the knowledge, tools, databases, procedures and models collected/developed by SAFFI will be integrated in a user-friendly and upgradable DSS for identification, detection, ranking and control of hazards and risk assessment (WP5).
SAFFI will contribute to ensure and enhance the transparency and reliability of food safety along the food chain with regard to international trade. SAFFI will also i) enhance the capacity of operators along the chain to detect, assess and mitigate food safety risks; ii) improve the efficiency of the official controls and iii) contribute to standard setting and regulatory cooperation in the EU and China.
SAFFI will contribute to ensure and enhance the transparency and reliability of food safety along the food chain with regard to international trade. SAFFI will also i) enhance the capacity of operators along the chain to detect, assess and mitigate food safety risks; ii) improve the efficiency of the official controls and iii) contribute to standard setting and regulatory cooperation in the EU and China.