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Data Descriptor

A Data Descriptor for Black Tea Fermentation Dataset

African Center of Excellence in Internet of Things (ACEIoT), College of Science and Technology, University of Rwanda, P.O. Box, 3900 Kigali, Rwanda
Department of Mathematics, Physics and Computing, Moi University, P.O. Box, 3900-30100 Eldoret, Kenya
Department of Biological Sciences, Moi University, P.O. Box, 3900-30100 Eldoret, Kenya
Sustainable Communication Networks, University of Bremen, 8359 Bremen, Germany
Author to whom correspondence should be addressed.
Academic Editors: Munish Kumar, R. K. Sharma and Ishwar Sethi
Received: 9 March 2021 / Revised: 15 March 2021 / Accepted: 15 March 2021 / Published: 19 March 2021
(This article belongs to the Special Issue Machine Learning in Image Analysis and Pattern Recognition)
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. View Full-Text
Keywords: tea; fermentation; internet of things; detection; dataset tea; fermentation; internet of things; detection; dataset
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MDPI and ACS Style

Kimutai, G.; Ngenzi, A.; Ngoga Said, R.; Ramkat, R.C.; Förster, A. A Data Descriptor for Black Tea Fermentation Dataset. Data 2021, 6, 34.

AMA Style

Kimutai G, Ngenzi A, Ngoga Said R, Ramkat RC, Förster A. A Data Descriptor for Black Tea Fermentation Dataset. Data. 2021; 6(3):34.

Chicago/Turabian Style

Kimutai, Gibson, Alexander Ngenzi, Rutabayiro Ngoga Said, Rose C. Ramkat, and Anna Förster. 2021. "A Data Descriptor for Black Tea Fermentation Dataset" Data 6, no. 3: 34.

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