Artículo

A Bibliometric Network Analysis of Recent Publications on Digital Agriculture to Depict Strategic Themes and Evolution Structure

Resumen

The agriculture sector is one of the backbones of many countries’ economies. Its processes have been changing to enable technology adoption to increase productivity, quality, and sustainable development. In this research, we present a scientific mapping of the adoption of precision techniques and breakthrough technologies in agriculture, so-called Digital Agriculture. To do this, we used 4694 documents from the Web of Science database to perform a Bibliometric Performance and Network Analysis of the literature using SciMAT software with the support of the PICOC protocol. Our findings presented 22 strategic themes related to Digital Agriculture, such as Internet of Things (IoT), Unmanned Aerial Vehicles (UAV) and Climate-smart Agriculture (CSA), among others. The thematic network structure of the nine most important clusters (motor themes) was presented and an in-depth discussion was performed. The thematic evolution map provides a broad perspective of how the field has evolved over time from 1994 to 2020. In addition, our results discuss the main challenges and opportunities for research and practice in the field of study. Our findings provide a comprehensive overview of the main themes related to Digital Agriculture. These results show the main subjects analyzed on this topic and provide a basis for insights for future research.
Chavez, Henry (57213581521); Albornoz, María Belén (57192277503); Martín, Fernando (57746138000)
‘Big data’ Research: A Bibliometric Analysis of the Scopus Database, 2009-2019
2022
10.5530/jscires.11.1.7
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132106342&doi=10.5530%2fjscires.11.1.7&partnerID=40&md5=94cfb7404692c0b2ce9373f1b3b2d931
All Open Access; Hybrid Gold Open Access
Scopus
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