Importance of Big Data variables in Agriculture: A comprehensive literature review with a particular focus on variables

Abstract

The sharp increase of information in our life and in particular in agriculture leads to the development and new opportunities that did not exist a couple of decades ago. At the same time the ability to collect and analyze large volumes of data from remote sensing sources has revolutionized the way farmers make decisions and manage their agricultural activities. The great role in this process corresponds to Big Data, which is not only the data in itself, but a set of strategies for analysis that allow you to benefit from owning it. The goal of this study is to review published articles on big data in agriculture throughout 2017–2023. In line with this goal, we have collected (using Science direct database), reviewed, and analyzed 60 papers published during within this period of time. Our results revealed an increasing number of big data studies during last years, with authors from India, the USA and China dominating in the published outcomes (42 % of total), followed by authors from Australia, Canada and the Netherlands. Another key finding is that from all existing variables for big data only five are really important and there is no need to expand these parameters. It is more optimal to use main variables (volume, velocity, variety, veracity and value) for an in-depth and detailed description of the state of the data. Results also revealed different big data sources and techniques for mail areas of data application.