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ABSTRACT: In this study, we have carried the bibliometric review of the “Tea quality evaluation using artificial intelligence”. Only the Scopus database is under consideration for this analysis. To coat all possible research approaches here we have generated the valid search queries which excludes irrelevant literature. The result analysis shows overall 602 useful papers are available on the tea quality evaluation out of which 12 papers are specifically on artificial taste perception of tea. This survey illustrates the emerging trend of quality evaluation and assurance (QEA) in tea industry and its importance. As the production of tea is huge, storage and aging of the tea are the effective factors which will harm tea industry business this kind of analysis and further research is required in this field. The global standards for such electronic artificial systems in tea industry are highly sensitive, biased and inconsistent. The primary analysis of search results is derived from Scopus database directly and some other tools have utilized for bibliometric analysis such as Microsoft Excel, VOSviewer, and ScienceScape. This survey discovered the contribution of various organizations, research authors, funding sponsors in the area of tea quality evaluation and artificial taste perception of tea.