Rooibos tea classification

Description

Welcome to the project on rooibos tea classification ! From the tutorials you will learn to do the following:

• Tutorial 1: Data visualization
• Tutorial 2: Data correlation
• Tutorial 3: Classification using simple statistics
• Tutorial 4: Classification using machine learning

Data

98 randomly selected fermented (fer) (51 samples) and nonfermnted (nf) (47 samples) were kindlydonated by Rooibos LTD-BPK (Clanwilliam, South Africa) during March 2020.

Hackathon Task

From the proposed pipeline (tutorials), investigate new ways to classify between fer and nf rooibos tea

Prerequisites

All the libraries/dependencies necessary to run the tutorials are listed in the requirements.txt file.

Installation

All the required libraries can be installed using pip and the requirements.txt file in the repo:

> pip install -r requirements.txt

Would you like to clone this repository? Feel free!

> git clone https://github.com/Hack4Dev/rooibosTea_classification.git

Then make sure you have the right Python libraries for the tutorials.

New to Github?

The easiest way to get all of the lecture and tutorial material is to clone this repository. To do this you need git installed on your laptop. If you're working on Linux you can install git using apt-get (you might need to use sudo):

apt install git

You can then clone the repository by typing:

git clone https://github.com/Hack4Dev/rooibosTea_classification.git

To update your clone if changes are made, use:

cd rooibosTea_classification/
git pull

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Original research work

Hussein, E.A.; Thron, C.; Ghaziasgar, M.; Vaccari, M.; Marnewick, J.L.; Hussein, A.A. Comparison of Phenolic Content and Antioxidant Activity for Fermented and Unfermented Rooibos Samples Extracted with Water and Methanol. Plants 2022, 11, 16. https://doi.org/10.3390/plants11010016