## 4 Results
### Barriers and Enablers Identified for the Processing Link  
Table 10 shows the barriers identified for the processing link. The agro-industrial landscape is evolving, and the use of technologies such as Blockchain, industrial IoT, robotization (cobots), and additive manufacturing, among others, allows for the improvement of product quality and value, as well as the optimization of processing (transformation) processes, creating competitive advantages [9; 131]. These intelligent systems that use sensors enable monitoring, exchanging data even between languages and models that are not the same, achieving interoperability [132], and integrating models and resources that operate in a network to generate manufacturing environments and collective logistics [131], which allow for the implementation of the factories of the future, increasing the innovation potential. This approach, understood as intelligent production, is divided into four parts of a life cycle: logistics, production, design, and marketing, impacting the nutritional quality of the products through human-machine integration and delivering to the end customer products that are much more adjusted to the requirements, mainly due to the impact that storage, transportation, and even packaging can have, affecting the health, safety, taste, and stability of food [48]. Adopting Food Informatics technologies in the processing link can improve the quality and safety of food that reaches the consumption link [9]. Despite this, in the agro-industrial chains, especially for the processing link, there is still a long way to go to reach these levels of automation. Connectivity is a critical element when deploying technologies such as Blockchain in processing processes, so if connectivity is poor, the environment is not ideal for the operation of electronic devices [133]. Adopting technologies such as Blockchain requires the understanding and skills necessary to support all aspects of the technology, so limited technical skills and knowledge present a critical barrier to its adoption [133]. Small companies may not have enough understanding and experience to allow them to commit to the full implementation of Food Informatics technologies, which becomes a limitation for their adoption [9; 139]. Likewise, research has shown that successful implementation processes of this type of technology have been achieved through a learning-by-doing process, through which the firm increases its digital skills [137]. Collaboration between the different links operating in the value chain is key not only for the joint implementation of technologies, but also for maintaining the transparency, trust, and traceability of data because a change in data chains can generate nonconformity and fraud [136]. Similarly, the collaborative and multidisciplinary role of the actors in the food industry is key to developing intelligent or smart food factories,  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Barrier** & **Description** & **Chain** & **Technology** & **Reference** \\ \hline \multirow{4}{*}{Connectivity} & Access to energy and Internet infrastructure is key to deploying technologies associated with real-time data capture. & \multirow{2}{*}{Wine} & \multirow{2}{*}{Blockchain} & \multirow{2}{*}{[133]} \\ \cline{1-1} \cline{5-5}  
which facilitate the development process of new and better products, as well as the optimization of inputs and benefits, guaranteeing quality and safety, reducing food waste, and tracking food from \"farm to fork\" [138]. The maturity and preparation level of the chain actors are mainly associated with the enabling conditions of the environment, i.e., support infrastructure, human capital, and organizational support can increase the availability of and reduce the effort to implement Food Informatics technologies [145].