Wheat Seed Quality Dataset

Zenodo (CERN European Organization for Nuclear Research) 2026 Dataset Open access

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Authors: DL Wang
DOI: 10.5281/zenodo.18222640
Cited by: 0

Abstract

This dataset contains high-resolution images of wheat seeds categorized into five classes: perfect wheat grains, insect-damaged wheat grains, scab-damaged wheat grains, moldy wheat grains, and black germ wheat grains. The dataset is intended for machine learning and deep learning experiments in seed quality assessment.

Fields of Study & Subjects

Smart Agriculture and AI Industrial Vision Systems and Defect Detection Agricultural Engineering and Mechanization

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
12 January 2026
Document type
Dataset