Dataset Development for Automated Grade Labelling of Virginia Flue-Cured Tobacco Leaves in Tanzania: A Focus on Stalk Leaf Position

Abstract

Objectives: This study aimed at developing a dataset for automated grade labeling of Virginia flue-cured tobacco leaves based on stalk leaf position by focusing on quality, colour and anomalies. Methods: Virginia flue-cured tobacco leaves were collected from four Tanzanian tobacco regions: Tabora municipal, Uyui, Urambo and Kaliua. Canon 5D Mark III cameras with a Canon EF 100mm F/2.8L Macro IS USM lens were used to capture tobacco leaves. The collected data concentrated on the upper leaves of the tobacco plant, also known as leaf position. In Tanzania, the tobacco plant position is a very crucial entity during grade labeling processes. Findings: To fulfil the study’s intention, a dataset was created by collecting Virginia flue-cured tobacco leaf images. The study utilized our published dataset of Virginia flue-cured tobacco leaf images, which consisted of 49,779 high-resolution images with 22 grade labels (classes). Novelty: The important findings highlight the dataset's quality, making it crucial to develop automated systems for Virginia flue-cured tobacco leaf grade labeling processes based on stalk leaf position.labeling