Analysis of the scientific knowledge structure on automation in the wine industry: a bibliometric and systematic review

Abstract

The objective of this research is to analyze the knowledge structure of the academic literature indexed in the Core Collection of the Web of Science on automation in the wine industry, from the first registered article in 1996 to 2022, in order to identify the latest trends in the study of this subject. A bibliometric and systematic analysis of the literature was carried out. First, for the quantitative analysis of the scientific production, the bibliometric study was conducted, using the WoS database for data collection and the VosViewer and Bibliometrix applications to create the network maps. Second, once the literature had been examined quantitatively, content analysis was undertaken using the PRISMA methodology. The results show, among other aspects, the uneven distribution of the examined scientific production from 1996 to 2022, that computer vision, data aggregation, life cycle assessment, precision viticulture, extreme learning machine and collaborative platforms are the major current keywords and the predominance of Spain and Italy in terms of scientific production in the field. There are various justifications which support the originality of this study. First, it contributes to the understanding of academic literature and the identification of the most recent trends in the study of automation in the wine industry. Second, to the best of our knowledge, no prior bibliometric studies have considered this topic. Third, this research evaluates the literature from the first record to the year 2022, thereby providing a comprehensive analysis of the scientific production.