An Overview of Agricultural Technology Trends from 2009-2019 through Research Mapping Analysis by Data Mining
The main idea of this platform is to explore research fronts in agricultural science for insight into the future development in agricultural technology. Through science mapping results, the members of governmental organizations (such as policymakers, technology managers, and research departments) can be aware of the emerging technology trends and arrange the resources to deal with important issues for sustainable agriculture. "AgriAnalytics" is a digital tool to understand research fronts of agricultural science and technology from pioneering agricultural journals between 2009 and 2019 by informatic techniques. Text mining and bibliometric analysis were used to reveal the important research topics and their evolution pattern based on scientific publications. And the bibliometric data of each literature were used for research mapping by statistical analysis, including title, keyword, author, publication date, and journal names. Consequently, 205 keywords were selected as popular topics because the author simultaneously mentioned keywords in all five journals. Moreover, ten major disciplines with 205 topics in agricultural research trends, such as agricultural multi-disciplines, intelligent agriculture, plant species, agricultural management, soil, crop phenotypes, environment, plant physiology, ecology, pest, and disease, were classified depending on the semantic definition of keywords. The knowledge structure of ten major disciplines was further constructed by those 205 popular keywords, which could help identify more emerging topics and insight into the new research directions. To evaluate each topic's trends from 2009 to 2019, statistical analysis was performed by counting the number of keywords each year. The results showed that sustainable agriculture, conservation agriculture, precision agriculture, organic agriculture, and food security were the leading scientific area issues. In short, the combination of data mining and bibliometric approach was performed in this study, which not only annotated the multidisciplinary issues of agriculture for having focused on the main thematic areas but also providing the insight information for discovering potential technologies in the agricultural sector.