Miscanthus Genomic Prediction: Sparse Testing for Biomass Yield

A Miscanthus sacchariflorus population of 336 genotypes observed across three environments provides data for evaluating sparse testing designs in genomic prediction. The dataset includes phenotypic measurements for dry biomass yield, total culm, average internode length, and culm node number, used to test models accounting for genotype-by-environment interactions. Results indicate the interaction model achieved the highest predictive ability for culm node number and dry biomass yield.

Use Cases

• Evaluating sparse testing designs for genomic prediction based on a fixed testing set of 224 genotypes.
• Comparing predictive ability of models with and without genotype-by-environment interaction effects for traits like dry biomass yield.
• Optimizing training set composition and size (from 52 to 112 samples) for forecasting performance in perennial grass breeding.

Strengths

• Includes data for 336 distinct Miscanthus sacchariflorus genotypes, providing a substantial genetic population for analysis.
• Phenotypic data spans four key agronomic traits measured across three environments, enabling multi-environment trial analysis.
• Dataset is openly shared under a CC-BY-4.0 license, facilitating reuse and collaboration.

Limitations

• Column names and the exact data structure are not provided in the source metadata, limiting immediate understanding of the file contents.
• The row count is not specified, and the dataset size (419353842) is given in bytes without context, making the data's scale unclear.
• The geographic scope of the three trial environments is not detailed, limiting ecological interpretation.

Provenance

Source

Diego Jarquin

Collection Method

Data likely originates from a multi-environment trial (MET) phenotyping study of a Miscanthus sacchariflorus breeding population.

Freshness

Last updated on 2026-03-18.