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                <identifier>oai:data.mendeley.com/p728rgr8bg.1</identifier>
                <datestamp>2026-09-18T13:54:07Z</datestamp>
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    <dc:creator>Debnath, Susmoy</dc:creator>
    <dc:title>Spiny Gourd Tri-Class Quality Dataset</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>The &quot;Spiny Gourd Tri-Class Quality Dataset&quot; is a specialized, curated subset extracted and refined from the open-source &quot;Nature&apos;s Best vs. Bruised: A Veggie Evaluation&quot; dataset under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. 

This dataset focuses specifically on Spiny Gourd (Momordica dioica), a widely consumed vegetable, to facilitate automated quality assessment and edibility evaluation using Computer Vision (CV) and Deep Learning (DL) models.

Key Details of the Dataset:

1. Target Crop: Spiny Gourd (Scientific Name: Momordica dioica)
2. Classification Categories: The dataset is structured into three distinct physical quality classes:
   - Fresh: High-quality, unblemished vegetables suitable for consumption.
   - Damaged: Vegetables showing minor structural, mechanical, or surface defects.
   - Severely Damaged: Highly degraded or rotten specimens unsuitable for commercial sale/consumption.
3. Environmental Conditions: Images feature authentic natural progression captured under varied camera angles, non-uniform illumination conditions, and consistent background setups.

Purpose &amp; Academic Usage:

This dataset is designed to address the lack of specialized single-crop quality benchmarks in agricultural computer vision. Researchers can utilize this dataset to train, validate, and benchmark deep learning architectures (e.g., CNNs, Vision Transformers) for real-time agricultural sorting, post-harvest quality inspection, and automated grading systems.

Attribution &amp; License:

Original Dataset: &quot;Nature&apos;s Best vs. Bruised: A Veggie Evaluation&quot;
License: Creative Commons Attribution 4.0 International (CC BY 4.0)
Modification Note: Filtered specifically for Spiny Gourd samples, re-annotated, and structured into a three-class quality taxonomy.</dc:description>
    <dc:subject>Computer Vision</dc:subject>
    <dc:subject>Vegetable</dc:subject>
    <dc:subject>Deep Learning</dc:subject>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/p728rgr8bg.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/p728rgr8bg.1</dc:identifier>
    <dc:rights>Creative Commons Attribution 4.0 International</dc:rights>
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    <dc:relation>https://data.mendeley.com/datasets/p728rgr8bg</dc:relation>
    <dc:date>2026-09-18T13:54:07Z</dc:date>
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