WoS-Driven Bibliometric Analysis on Plant Disease Prediction Model

Today's society revolves around artificial intelligence and relies on it for various businesses, like agriculture, where they want to use it as a tool. We should be worried because people waste about 1.6 billion metric tons of staple foods every year. We are slowly realizing this and implementing new techniques like food preservation and crop care. Using a literature review and bibliometric analysis, this article presents study findings exploring the existence and growth of the phrase “plant diseases” from 2016 to 2022. The main aim of this study is to look at the quantity and quality of empirical evidence on the prevention of plant diseases that supports the use of this strategy. The researchers recognized and confirmed that this topic of study is important and holds great promise for helping future researchers achieve strategic alignment between information and technology. The Web of Science bibliometric methodology has been used to analyze a total of 1000 publications on this topic. This research will be of great interest to academics and practitioners who wish to improve their understanding of plant diseases and trace key individuals, topics, and historical events that have contributed to the body of knowledge in this field. This bibliometric analysis includes published research in the form of articles, conference papers, and book chapters that helps determine the global impact of publications in a research community. This review paper discusses how to use bibliometric studies in R as well as how to effectively perform bibliometric studies. The visualization makes it easy to see and understand different ideas in the research field of predicting plant diseases.