A Data Descriptor for Black Tea Fermentation Dataset

Gibson Kimutai, Alexander Ngenzi, Rutabayiro Ngoga Said, Rose C. Ramkat and Anna Förster
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Gibson Kimutai: African Center of Excellence in Internet of Things (ACEIoT), College of Science and Technology, University of Rwanda, P.O. Box, 3900 Kigali, Rwanda
Alexander Ngenzi: African Center of Excellence in Internet of Things (ACEIoT), College of Science and Technology, University of Rwanda, P.O. Box, 3900 Kigali, Rwanda
Rutabayiro Ngoga Said: African Center of Excellence in Internet of Things (ACEIoT), College of Science and Technology, University of Rwanda, P.O. Box, 3900 Kigali, Rwanda
Rose C. Ramkat: Department of Biological Sciences, Moi University, P.O. Box, 3900-30100 Eldoret, Kenya
Anna Förster: Sustainable Communication Networks, University of Bremen, 8359 Bremen, Germany

Data, 2021, vol. 6, issue 3, 1-8

Abstract: Tea is currently the most popular beverage after water. Tea contributes to the livelihood of more than 10 million people globally. There are several categories of tea, but black tea is the most popular, accounting for about 78% of total tea consumption. Processing of black tea involves the following steps: plucking, withering, crushing, tearing and curling, fermentation, drying, sorting, and packaging. Fermentation is the most important step in determining the final quality of the processed tea. Fermentation is a time-bound process and it must take place under certain temperature and humidity conditions. During fermentation, tea color changes from green to coppery brown to signify the attainment of optimum fermentation levels. These parameters are currently manually monitored. At present, there is only one existing dataset on tea fermentation images. This study makes a tea fermentation dataset available, composed of tea fermentation conditions and tea fermentation images.

Keywords: tea; fermentation; internet of things; detection; dataset (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2021
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