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The current European agri-food and forestry (AFF) systems are perceived to be moving too slowly towards more sustainable agriculture, forestry, food and bio-based value chains. The European Green Deal and Farm to Fork (FtF) Strategy stress the importance of the sustainable transition of food systems that emphasize resilience and justice along food chains. In this direction, education and training (ET) are given a major role, constituting one of the pillars of the Agricultural Knowledge and Innovation Systems (AKIS) framework. This study aims to propose an extended version of the AKIS framework to focus on the transition of policies concerning the ET pillar and to use this framework as a conceptual background with which to identify strategies for the improvement of ET policies in the AFF sectors. Data collection was undertaken through a round of workshops, and the data were analyzed using a thematic analysis approach. The results revealed that the need for a high-quality educational policy and the need to enhance collaboration, entrepreneurship and innovative learning methods were among the most important for the sector, where urgent changes in pace and an approach in ET are necessary for the entire value chain, from farm to fork. These results emphasize that pivoting the transition of ET systems toward achieving the Green Deal, FtF and new CAP objectives requires the development of policies that support student-centered and interdisciplinary education, while also being flexible and supported by non-formal and lifelong learning approaches. © 2024 by the authors., Educating the Next Generation of Professionals in the Agri-food and Forestry System (NEXTFOOD)

The artisanal food chain is enriched by a wide diversity of local food productions with delightful organoleptic characteristics and valuable nutritional properties. Despite their increasing worldwide popularity and appeal, several food safety challenges are addressed in artisanal facilities context suffering from less standardized processing conditions. In such scenario, recent advances in molecular typing and genomic surveillance (e.g., Whole Genome Sequencing [WGS]) represent an unprecedent solution capable of inferring sources of contamination as well as contributing to food safety along the artisanal food continuum. The overall objective of this PhD thesis was to explore potential microbial hazards among different artisanal food productions of animal origins (dairy and meat-derived) typical of the food culture and heritage landscape belonging to Mediterranean countries. Three different studies were then carried out, specifically focussing on: 1) compare the seasonal variability of microbiological quality and potential occurrence of microbial hazards in two batches of Italian artisanal fermented dairy and meat productions; 2) Investigate genetic relationships as well as virulome and resistome of foodborne pathogens isolated within dairy and meat-derived productions located in Italy, Spain, Portugal and Morocco; 3) investigate the population structure, virulome, resistome and mobilome of Klebsiella spp. isolates collected from study 1, including an extended range of public sequences.

To ensure food safety and to prevent food-borne illnesses, rapid and accurate detection of pathogenic agents is essential. It has already been demonstrated that shotgun metagenomic sequencing can be used to detect pathogens and their antibiotic resistance genes in food. In the studies presented in this thesis, the application shotgun metagenomic sequencing has been applied to investigate both the microbiome and resistome of foods of animal origin in order to assess advantages and disadvantages of shotgun metagenomic sequencing in comparison to the cultural methods. In the first study, it has been shown that shotgun metagenomics can be applied to detect microorganisms experimentally spiked in cold-smoked salmon. Nevertheless, a direct correlation between cell concentration of each spiked microorganism and number of corresponding reads cannot be established yet. In the second and third studies, the microbiomes and resistomes characterizing caeca and the corresponding carcasses of the birds reared in the conventional and antibiotic free farms were compared. The results highlighted the need to reduce sources of microbial contamination and antimicrobial resistance not only at the farm level but also at the post-harvest one. In the fourth study, it has been demonstrated that testing a single aliquot of a food homogenate is representative of the whole homogenate because biological replicates displayed overlapping taxonomic and functional composition. All in all, the results obtained confirmed that the application of shotgun metagenomic sequencing represents a powerful tool that can be used in the identification of both spoilage and pathogenic microorganism, and their resistome in foods of animal origin. However, a robust relationship between sequence read abundance and concentration of colony-forming unit must be still established.

An inter-laboratory proficiency test was organized to assess the ability of participants to perform shotgun metagenomic sequencing of cold smoked salmon, experimentally spiked with a mock community composed of six bacteria, one parasite, one yeast, one DNA, and two RNA viruses. Each participant applied its in-house wet-lab workflow(s) to obtain the metagenomic dataset(s), which were then collected and analyzed using MG-RAST. A total of 27 datasets were analyzed. Sample pre-processing, DNA extraction protocol, library preparation kit, and sequencing platform, influenced the abundance of specific microorganisms of the mock community. Our results highlight that despite differences in wet-lab protocols, the reads corresponding to the mock community members spiked in the cold smoked salmon, were both detected and quantified in terms of relative abundance, in the metagenomic datasets, proving the suitability of shotgun metagenomic sequencing as a genomic tool to detect microorganisms belonging to different domains in the same food matrix. The implementation of standardized wet-lab protocols would highly facilitate the comparability of shotgun metagenomic sequencing dataset across laboratories and sectors. Moreover, there is a need for clearly defining a sequencing reads threshold, to consider pathogens as detected or undetected in a food sample.

Salmonella enterica subspecies enterica serovar Typhimurium and its monophasic variant are among the most common Salmonella serovars associated with human salmonellosis each year. Related infections are often due to consumption of contaminated meat of pig, cattle, and poultry origin. In order to evaluate novel microbial subtyping methods for source attribution, an approach based on weighted networks was applied on 141 human and 210 food and animal isolates of pigs, broilers, layers, ducks, and cattle collected in Denmark from 2013 to 2014. A whole-genome SNP calling was performed along with cgMLST and wgMLST. Based on these genomic input data, pairwise distance matrices were built and used as input for construction of a weighted network where nodes represent genomes and links to distances. Analyzing food and animal Typhimurium genomes, the coherence of source clustering ranged from 89 to 90% for animal source, from 84 to 85% for country, and from 63 to 65% for year of isolation and was equal to 82% for serotype, suggesting animal source as the first driver of clustering formation. Adding human isolate genomes to the network, a percentage between 93.6 and 97.2% clustered with the existing component and only a percentage between 2.8 and 6.4% appeared as not attributed to any animal sources. The majority of human genomes were attributed to pigs with probabilities ranging from 83.9 to 84.5%, followed by broilers, ducks, cattle, and layers in descending order. In conclusion, a weighted network approach based on pairwise SNPs, cgMLST, and wgMLST matrices showed promising results for source attribution studies.