Identification and Classification of the Tea Samples by Using Sensory Mechanism and Arduino UNO

• Published in: Inventions (Basel) Vol. 6; no. 4; p. 94
• Main Authors: Patil, Amruta, Bachute, Mrinal, Kotecha, Ketan
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.12.2021
• Subjects: Additives; Antioxidants; Artificial intelligence; artificial intelligence (AI); artificial taste perception; Beverages; Black tea; Caffeine; Cold; Data analysis; Dental caries; Dental erosion; Green tea; machine learning (ML); Nutrition; Oral hygiene; pH measurement; Sensors; sensory mechanism; Tea; tea samples; China; India
• ISSN: 2411-5134; 2411-5134
• DOI: 10.3390/inventions6040094

Tea is the most popular hot beverageworldwide. In 2020, the value of the global tea market was almost USD 200 billion, and is estimated to reach up to USD 318 billion by the year 2025. Tea has been included as part ofa regular diet for centuries because of its various health benefits. However, tea is acidic, and over-consumption causes heat problems, disturbance of the sleep cycle, tooth erosion, and low calcium absorption in the body. Strong tea concentration is very harmful and toxic. The safe consumption of tea should be guaranteed. The treatment applied in this research work is on sensory mechanisms and Arduino UNO. The objective of this paper is to find out community interest in a particular tea species and inform them about tea overdose.The acidity is mapped with tea taste in terms of strong, medium, and low flavors. Based on the data analysis, the results differentiatethe acidity level of black tea (pH: 3.89–4.08) as very high, green tea (pH: 4.68–4.70) is in the 2nd position, and the energy drink Herbalife Nutrition (pH: 5.59–5.64) is the least acidic comparatively, with a proportion ratio 1:10 of tea to water. Experimental analysis reveals that in the additives, lemon is most acidic, followed byginger, lemongrass, and Tulasi.