A Scoping Review of the Smart Irrigation Literature Using Scientometric Analysis

Abstract

Background. Smart irrigation is a research field which grows very fast. It facilitates the contribution of technologies on smart agriculture. Smart irrigation is a broad topic with overwhelming literature published and available semantic ambiguity, so covering such a vast topic is not easy without scoping reviews. To enable researchers to gain a deep knowledge of structure of the field, a scientometric-based scoping review was conducted. Methods. The bibliometric data focused on smart irrigation from databases such as Scopus, Web of Science, and Google Scholar were downloaded, thoroughly merged, and cleaned to meet the inclusion criteria. These data were analyzed and clustered using K-means from VOSviewer. VOSviewer is used to create coauthor and coword occurrence network graphs from keywords, titles, and abstracts. Results. The findings highlight the broad scope of the research field, the ambiguity of the terminology, the lack of collaboration, and the absence of research into the impact of smart irrigation on agriculture. The leading institutions and researchers in the field and geographical distribution are from China, Israel, Australia, and Egypt. The leading main topics addressed in the field are IOT, smart irrigation, irrigation, water stress, energy, deep learning, soil moisture, and relations in the network. Conclusion. Smart irrigation (drip irrigation + IoT) in agriculture increases crop yield, increases water use efficiency, and decreases costs. In future work, large studies need to be conducted to establish and investigate the scope of smart irrigation research to reveal the knowledge structure, current state of practice, and key actors in the field.