## 1 Introduction  
The world population is expected to exceed the threshold of nine billion people by 2050 [1], so the adoption of \"Food Informatics\" technologies is shown as a solution to the need to increase the production of more and better food [2] and overcoming the challenges of food security, food safety, sustainable development, and health [3]. Some research shows how data captured from smart agriculture can optimize yield with minimum inputs, reduce environmental pollution [4], and improve the market prices of agricultural products through decision-making on crop state and quality [5]. Likewise, applying technologies such as Blockchain facilitates transparency between farmers, markets, sellers, logistics, and consumers, combating fraud and generating trust throughout the agri-food chain [6]. It is clear that adopting this set of technologies throughout the agri-food chain is one of the determining factors for improving productivity and competitiveness [2] and facilitating data capture, interoperability, transmission, processing, and analysis. The complexity of actorsthat participate in the production chains, such as farmers, food processors, and marketers, besides the challenges they permanently face in the development of their activities--especially those associated with technology, human talent, and market changes--generates a permanent barrier to achieving the transformation and optimization of their activities. At a global level, there are several examples of the use of data to improve efficiency in cultivation. Among these, the automation of robots and the increase in food quality based on artificial intelligence are highlighted (e.g., CGIAR Platform for Big Data in Agriculture, AgBioData consortium, and Global Open Data for Agriculture and Nutrition [SODAN]) [7]. However, even in the regional reality, there is a gap in the implementation of these technologies framed in three major causes: (1) the use and adoption of these types of emerging technologies [8; 9], (2) the poor articulation and trust between the links in the chain for capturing and exchanging data under different standards and formats [10; 11; 12; 13; 14; 15], and (3) the development of solutions fragmented per link that do not contemplate the bidirectional interoperability of data and decision-making under a farm-to-fork model [16; 17; 18]. These causes are even more relevant in contexts such as Latin America, where the economic dependence on agri-food activities is the basis of the livelihood of many peasant families. At an international level, progress is being made in developing agri-food data repositories that allow, under the \"open\" logic, the exploitation and use of the same by the different links. This is the case with the Global Open Data for Agriculture and Nutrition (GODAN) (more information at [[http://aims.fao.org/godan_open_data](http://aims.fao.org/godan_open_data)]([http://aims.fao.org/godan_open_data](http://aims.fao.org/godan_open_data)), accessed on 19 March 2024), as well as the Internet of Food and Farm (IOF2020) (more information at [[https://www.iof2020.eu/](https://www.iof2020.eu/)]([https://www.iof2020.eu/](https://www.iof2020.eu/)), accessed on 17 May 2024) Project of the Horizon 2020 program of the European Commission, which seeks to develop a more sustainable food chain by using open data obtained through the Internet of Things (IoT) via a data ecosystem. Finally, the \"Future Internet for Safe and Healthy Food from Farm to Fork\" Project (some case studies of this project are available at [https://kylkos40 project.eu/](https://kylkos40 project.eu/), accessed on 19 March 2024) developed by the European Union agrees on the importance of developing a robust Internet infrastructure and improving real-time data processing from the food chain [19]. The Internet of Food provides new opportunities and has meant a crucial change in the digitalization of the agroindustry world.