Agriculture is the backbone of the Indian Economy. For the past few decades, the agriculture sector underwent several metamorphisms and across the globe farmers have adopted a wide variety of farming technologies and farming innovations to improve productivity on as well as the quality of the products. The ultimate aim of all these agricultural technology information management systems are to facilitate the production of quality food items at an affordable cost. Technology adoption and information management in Agriculture may be applied to different levels of farming activities starting from the selection of quality planting materials to harvesting and post harvesting operations. Recent advancements in ICT and mobile applications enables improved usage of precision farming and SMART agriculture practices and brings effective information management. These technological adoptions and information management enable the farmers in producing quality agricultural products and helps to improve their earnings. There are many studies on the acceptance and adoption of Technology by farmers for information management. In this paper we evaluate various Technology Acceptance Models in agriculture using Citation Network Analysis (CNA) to get an understanding about the acceptance and adoption of technology by farmers. Software packages such as Sci2, Gephi and VosViewer were used for CNA analysis. The chronological analysis of data collected from Web of Science database for the period 1989 to 2022 were collected and used for building the network. The main path was identified to understand the evolution of research articles in the subject area of technology acceptance in agriculture. Further we explored the co-citations to trace the extent to which two or more articles are cited together in other research articles. From the main path, we traced the growth of the domain under consideration and identified five different phases of the technology adoption by farmers. Content analysis of major nodes in the main path have been performed to the current trend and future scope of the research area. We performed modularity based clustering algorithm for finding the major research themes in the area. All these analysis provides a clear picture of how the technology adoption in agriculture was evolved over past several years and what are the technologies at different time intervals. The analysis shows that recent research trends in this area is more focussed towards sustainability and majority of scientists have studied and evaluated the technology adoptions using UTAUT model.