## 6 Conclusions  
The identified factors are linked to each other through systemic interactions, which implies that they are independent of each other and that one factor can generate negative or positive changes in others, so they cannot be understood individually [160]. These are, in general terms, social (ease of use, transparency, and traceability), economic (initial investment costs, return on investment, and access to credit), and technological (data privacy and connectivity) factors [81]. The implementation of Food Informatics technologies requires the participation of a large number of nodes for data capture. However, if the nodes are small firms or small producers with limited technological expertise and scarce financial resources, it could become a limitation to keep the system operational and the flow of information managed for all participants [9]. Studies show that the primary motivations for adopting food informatics technologies are associated with the desire to obtain information to improve crop management [103], the optimization of processing processes, and the increase in demand for agri-food products. In some of the cases studied, it is considered necessary that the information linked to Food Informatics processes be previously validated by certifying bodies to protect all parties, especially the final consumer [136]. The literature shows that there is a direct relationship between the implementation of Food Informatics technologies (Blockchain) and compliance with voluntary standards in some chains such as cocoa and coffee, as is the case in \"Choco4 Peace\" (more information at [[https://www.choco4](https://www.choco4) peace.com/]([https://www.choco4](https://www.choco4) peace.com/), accessed on 24 July 2024), which allows vulnerable Colombian farmers to improve their lives by finding markets for their cocoa, allowing them to escape poverty and conflict [161]. In this sense, Choco4 peace measures the economic, social, and environmental benefits of the investments developed based on the data recorded in Blockchain. Adopting technologies such as Agriculture 4.0, precision agriculture, Blockchain, robotics, IoT, and artificial intelligence in food chains requires new roles, understanding, and skills necessary to support all aspects of the technology, which generates a barrier to its adoption [162]. In general terms, to achieve an efficient adoption of Food Informatics technologies, the following are required: (1) Achieve a change in mentality, culture, and skills that facilitates the integration and adoption of technologies; (2) generate public policies that allow access to energy and connectivity infrastructure, especially in remote areas, to achieve adoption processes; (3) integrate academia through research, technology development, and innovation processes for the promotion of technologies and the generation of capacities from the territory; and finally, (4) use data ecosystem models that connect the three links (production, processing, and commercialization) through effective elements of data governance, cybersecurity that facilitates transparency, and the use of data by the parties involved. A key limitation of this study was the independent analysis of barriers and enablers to Food Informatics adoption in agri-food chains. While the literature suggests interdependencies among these factors, this study treated them separately. This study recommends that future research develop a computational model that simulates the adoption process to address this issue. This model, incorporating hierarchical structures, would allow for a more nuanced understanding of how these factors interact, influencing each other's impact on adoption. Such a model could provide decision-makers with more refined policy guidelines for promoting Food Informatics adoption in agri-food chains. Conceptualization, W.A.O.-G. and A.S.-A. ; methodology, W.A.O.-G.; software, W.A.O.-G. and J.J.M.-A. ; validation, W.A.O.-G., A.S.-A. and J.J.M.-A.