Browntop Millet Agronomic Trait Data for 121 Genotypes

A 2026 study by C. Nandini evaluated a diversity panel of 121 browntop millet accessions for key agronomic traits. The dataset includes results from genetic parameter estimation, correlation and path analysis, and principal component and cluster analyses. It identifies 11 promising genotypes for breeding high-yielding, climate-resilient cultivars.

Use Cases

• Identify high-yielding donor genotypes for breeding programs based on grain and fodder yield data.
• Analyze trait correlations and path coefficients to understand relationships between yield and contributing traits.
• Perform cluster analysis to group genotypes based on phenotypic similarity for selection.
• Apply multi-trait selection indices like MGIDI to select superior, ideotype-matching genotypes.

Strengths

• Dataset is based on a structured study of 121 distinct genetic accessions.
• Analysis includes heritability and genetic advance estimates, indicating additive gene action for key traits.
• Principal component analysis accounted for 68.66% of total variation with the first five components.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The data is contained in a 150.3 KB PDF, which is a very small file and may limit scope or detail.

Provenance

Source

C. Nandini via figshare.

Collection Method

Phenotypic evaluation of a diversity panel of Urochloa ramosa accessions, with subsequent statistical and genetic analyses.

Time Range

The study was published in 2026, but the temporal coverage of the data collection is not specified.

Freshness

Last updated 2026-04-13 04:35:45; freshness should be verified.

Geography

Geographic origin of the 121 accessions is not specified.