Smart farming integrates digital technologies to optimize agricultural production and promote sustainability. Its impact depends both on technological development and adoption by farmers. Research shows significant progress, but technical and socio-behavioral gaps remain, requiring integrated approaches to strengthen its contribution to the SDGs. In this context, scientific research on smart farming has grown significantly, becoming a key axis for the fulfillment of the Sustainable Development Goals (SDGs). The aim of this study was to analyze the evolution, structure, and impact of scientific production in smart farming, identifying its main trends, authors, journals, and contributions to the SDGs. To this end, a bibliometric analysis was applied to 1580 articles indexed in the Web of Science (WoS) database, using productivity, citation, and impact indicators based on Price’s, Lotka’s, Bradford’s, and Zipf’s laws, as well as the Hirsch index. The results reveal important growth in scientific production between 2014 and 2024, with a strong concentration in high-impact journals and international collaboration networks. In conclusion, smart farming represents an engine of innovation and sustainability, integrating science, technology, and digital management to address the global challenges of food security, climate change, and sustainable development.

Smart farming has established itself as a strategic field in the digital and sustainable transformation of the agri-food sector. The rise of technologies such as the Internet of Things (IoT), artificial intelligence (AI), machine learning, big data, and blockchain has revolutionized production systems, improving efficiency, sustainability, and adaptability to climate change. In this context, scientific research on smart farming has grown exponentially, becoming a key axis for the fulfillment of the Sustainable Development Goals (SDGs). The objective of this study was to analyze the evolution, structure, and impact of scientific production in smart farming, identifying its main trends, authors, journals, and contributions to the SDGs. To this end, a bibliometric analysis was applied to 1,580 articles indexed in the Web of Science (WoS) database, using productivity, citation, and impact indicators based on Price's, Lotka's, Bradford's, and Zipf's laws, as well as the Hirsch index. The results reveal important growth in scientific production between 2014 and 2024, with a strong concentration in high-impact journals and international collaboration networks. In conclusion, smart farming represents an engine of innovation and sustainability, integrating science, technology, and digital management to address the global challenges of food security, climate change, and sustainable development.

The aim of this study is to conduct a scoping review of the literature on the marketing environment and Fair Trade in the coffee industry, identifying its contribution to organizations and society. Quantitative studies were selected from databases such as Web of Science and Scopus, following a selection process aligned with the PRISMA methodological guidelines and establishing eligibility criteria for articles using the PICOS strategy. To understand the effects of macromarketing, strategic marketing, and operational marketing on the development of the Fair Trade coffee market, the results demonstrate that marketing plays a significant role in the market's growth. Specifically, marketing is crucial in communicating the value of Fair Trade, raising consumer awareness, and supporting the economic well-being of coffee producers. Ethical consumption and branding strategies are essential for positioning Fair Trade coffee in competitive markets. However, further studies are needed to corroborate these findings and provide more up-to-date perspectives.

Smart farming (SF) integrates digital technologies, automation, and data analytics to enhance agricultural decision-making and sustainability. However, adoption in emerging economies remains limited due to structural constraints. This study examines the determinants of SF adoption intention in Honduras using an extended Technology–Organization–Environment (TOE) framework that incorporates technological attributes, farm manager characteristics, organizational factors, and business environmental conditions. A cross-sectional survey of 313 agricultural workers, mainly young and female, was analyzed using partial least squares structural equation modeling (PLS-SEM). The model explained 80.8% of the variance in adoption intention. Among the eleven hypothesized predictors, only government support and changes in the digital environment showed significant positive effects. Technological factors, managerial capabilities, organizational conditions, and competitive pressure were not significant. These findings indicate that, in structurally constrained agricultural systems, external enabling conditions—particularly institutional support and digital infrastructure—play a decisive role in shaping adoption intention. The results highlight the need for policies that strengthen rural connectivity, technical training, financing mechanisms, and institutional assistance to facilitate effective implementation of smart farming technologies. The study validates the TOE framework in an emerging economy and underscores the contextual variability of its explanatory dimensions.

Business models are increasingly recognized as key architectures that may help coordinate technological, organizational, social, and territorial innovations in sustainable agriculture. This study conducts a comprehensive bibliometric analysis of 325 publications indexed in the Web of Science Core Collection (2002–2026) to map the epistemic, conceptual, and intellectual structure of research on business models for building sustainable agriculture. Using Price’s, Lotka’s, Bradford’s, and Zipf’s laws, along with co-citation analysis, the study examines temporal growth, author productivity, journal concentration, thematic clusters, and foundational literature. Results suggest exponential growth in scientific production, strong alignment with SDGs related to food security, circular economy, climate action, and biodiversity, and a highly concentrated intellectual core centered on business model design, sustainability transitions, and digital transformation. Four thematic clusters emerge: innovation and agricultural systems; management, governance, and business models; sustainability and climate-energy dynamics; and challenges, assessment, and ecosystem services. Co-citation analysis reveals three major axes shaping the field: strategic business model design, circular and sustainable value creation, and digital and territorial transformation of agri-food systems. Overall, the findings suggest that sustainable agriculture may benefit from hybrid business models integrating technological innovation, circularity, governance, and multi-actor collaboration.

Este artículo presenta un modelado de procesos en una finca cafetalera en Honduras bajo la certificación de comercio justo. El objetivo es modelar el procesamiento productivo en una finca y cooperativa cafetalera, aplicando el enfoque sistémico de Katz y Kahn. La investigación se centra en la eficiencia y sostenibilidad de los procesos de procesamiento, con el fin de mejorar los ingresos de los productores locales. La metodología empleada es el estudio de caso, utilizando entrevistas semiestructuradas y observación directa. Primero, se identifica y describe detalladamente el área de procesamiento de una finca de café. Luego, se propone la implementación de un sistema informático de gestión, recomendando el uso de una aplicación blockchain para mejorar la trazabilidad y eficiencia en las operaciones. Se concluye que el enfoque sistémico y la integración de tecnologías de la información contribuyen significativamente a mejorar las condiciones de vida de los productores agrícolas y promueven un comercio más justo y equitativo entre estos.