Principal component analysis of steers performance and structural and nutritional characte

Principal component analysis of a dataset from a 2015-2018 study on Mombasa grass pastures explains 99.6% of variance with two components. The data includes pasture structural characteristics, nutritional value, and beef steer performance metrics like average daily gain and stocking rate. Antônio Leandro Chaves Gurgel authored this research to identify factors explaining cattle performance under residual nitrogen fertilizer effects.

Use Cases

• Modeling pasture stocking rate based on forage accumulation rate and forage mass
• Analyzing the relationship between pasture structural characteristics and cattle average daily gain
• Identifying key drivers of secondary productivity in fertilized grasslands using principal component analysis

Strengths

• Principal component analysis explains 99.6% of the dataset's variance with two components.
• Data collection spans multiple years (2015-2018) under controlled nitrogen application rates.
• Study evaluates multiple interrelated variables: pasture structure, nutritional value, and animal performance.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Antônio Leandro Chaves Gurgel

Collection Method

Data collected from Mombasa grass pastures under increasing nitrogen rates from 2015 to 2017, with a residual effect study in 2018.

Time Range

2015 to 2018