A dataset revolutionizing Indian bay leaf analysis
Year: 2024
Type: data-paper
Abstract: Indian bay leaf is a crucial spice in Indian cuisine. However, its quality and authenticity are often compromised. To address this, we introduce The Digital Indian Bay leaf dataset, a comprehensive collection of high-resolution 5696 images capturing diverse bay leaf samples under controlled conditions. The dataset encompasses variations in leaf conditions such as fresh leaf, dried leaf and diseased prone leaf. The dataset is meticulously curated to support research in condition analysis and machine learning applications for leaf quality assessment. To ensure data diversity, each category includes a wide range of images captured under controlled conditions with varying lighting, background, and leaf orientation. By providing a standardized and accessible resource, this dataset aims to accelerate research in this domain and contribute to the improvement of the Indian spice industry.
Source: Data in Brief
Authors: Priyanka Paygude, Sandip Thite, Ajay Kumar, Amol Bhosle, Rajendra Pawar, Renuka Mane, Rahul Joshi, Manisha Kasar, Prashant Chavan, Milind Gayakwad
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $850
OpenAlex ID: W4403471713