Genomic Prediction Accuracy for Milk Production Traits in Mehsana Buffalo

Mayank R. Patel's dataset compares the accuracy of pedigree-based and genomic prediction models for milk production traits in Mehsana buffalo. It includes phenotype records from over 10,500 buffaloes and genotype data from 3,887 buffaloes using a 54K SNP array. The results show an 11.37% average improvement in prediction accuracy using the ssGBLUP model.

Use Cases

• Compare genomic and pedigree-based prediction models based on reported accuracy metrics for milk yield traits.
• Analyze prediction bias in breeding value estimation based on regression coefficients of corrected yield on predicted breeding values.
• Benchmark genomic prediction performance for dairy buffalo using a dataset of over 10,000 phenotype records.
• Study the impact of single nucleotide polymorphism (SNP) data on genetic evaluation accuracy for livestock.

Strengths

• Includes phenotype records from over 10,500 Mehsana buffaloes for multiple milk production traits.
• Contains genotype data from 3,887 buffaloes with 53,292 SNPs after quality control.
• Provides specific prediction accuracy metrics, ranging from 0.078 to 0.100 for different models.
• Quantifies an 11.37% average improvement in accuracy from using genomic data.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data is specific to the Mehsana buffalo breed, limiting generalizability.

Provenance

Source

Mayank R. Patel via figshare.

Collection Method

Phenotype data collected from test day records; genotype data collected from blood samples and processed using a BUFFCHIP 54K SNP array.

Freshness

Last updated 2026-06-01 22:02:47; freshness should be verified.

Geography

Mehsana buffalo population.