Abstract
Nowadays, an artificial perception of beverages is in high demand as
working hours increase, and people depend on readymade food and beverages. An
assurance of quality, safety, and edibility of food and drink products is essential both
for food producers and consumers. Assurance of unique beverage taste and consistent
taste uniformity creates a distinct identity in the market. India is the second largest tea
producer country in the world. Based on geographic location, the tea has a specific
flavor and aroma. Artificial Intelligence (AI) can contribute to the feature identification
and grading of tea species. The taste, aroma, and color are the three main attributes that
can be sensed with the help of E-tongue, E-nose and E-vision, and can be processed
further for automatic tea grading. The various potentiometric, voltammetric, Metal
Oxide Semiconductor (MOS) and acoustic sensors are available with Principal
Component Analysis (PCA). For tea analysis, various reviews are mentioned, like User
Experience (UX evaluation, literature review, bibliometric review, and patent review.
An in-depth analysis of artificial taste perception using machine learning has been
described in the chapter. The topic covered almost all possible approaches to the
artificial perception of tea with various interesting facts.