Southern Oat Association Panel: Genomic Prediction for Stem Rust Resistance

440 oat lines from the Southern Oat Association Panel were genotyped with a 3K SNP array and GBS and phenotyped for stem rust resistance across seven environments from 2022 to 2024. Predictive ability for disease severity and infection response was evaluated under three cross-validation scenarios using Bayesian and machine-learning models. The dataset was created by Janam Prabhat Acharya and published on figshare under a CC-BY-4.0 license.

Use Cases

• Benchmark genomic prediction models based on Bayesian and machine-learning methods.
• Evaluate cross-validation strategies for predicting untested genotypes or new environments.
• Compare predictive accuracy between SNP array and genotyping-by-sequencing platforms.
• Assess the potential of genomic selection to reduce reliance on large-scale phenotyping.

Strengths

• 440-line panel provides a substantial sample for genomic analysis.
• Data includes phenotyping across seven environments from 2022 to 2024.
• Genotyping performed with both a 3K SNP array and genotyping-by-sequencing.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect geographic bias inherent to the Southern United States focus.

Provenance

Source

figshare

Collection Method

Field trials and genomic analysis of the Southern Oat Association Panel.

Time Range

2022-2024

Freshness

Last updated 2026-03-19 06:49:00; freshness should be verified.

Geography

Southern United States