Physiological, and Digital Seedling Phenotyping Data of Maize Landraces Used for Seed Quality Assessment

This dataset contains the complete experimental data used in the study entitled “Integration of Digital X-ray Imaging and Automated Seedling Phenotyping for Seed Quality Assessment of Maize Landraces”.

The dataset includes measurements obtained from 24 maize landraces and one commercial hybrid reference, encompassing:

• Seed physical attributes derived from digital X-ray imaging, including morphometric and densitometric descriptors (e.g., seed area, perimeter, circularity, relative density, integrated density, and gray-value-based measurements);

• Physiological quality assessments, including germination, first count, emergence, emergence speed index, accelerated aging, moisture content, seed infestation, purity analysis, and thousand-seed weight;

• Digital seedling phenotyping variables obtained through automated image analysis, including shoot length, root length, total seedling length, shoot dry mass, root dry mass, and vigor-related indices;

• Supporting data used for correlation analysis, multivariate statistics, and principal component analysis (PCA).