View source: R/breeding_metrics.R
breeding_metrics | R Documentation |
This function calculates key breeding metrics such as genotypic variance, environmental variance, genotypic coefficient of variation (GCV), phenotypic coefficient of variation (PCV), heritability, and genetic advance (GA). These metrics are critical for assessing genotype performance and genetic potential in crop breeding experiments.
breeding_metrics(data, genotype_col, trait_col, replication_col)
data |
A data frame containing the dataset with required columns. |
genotype_col |
Character. Name of the genotype column. |
trait_col |
Character. Name of the trait column. |
replication_col |
Character. Name of the replication column. |
A list containing:
'ANOVA': The summary of the ANOVA table.
'GenotypicVariance': Genotypic variance, which measures the genetic variability among genotypes.
'EnvironmentalVariance': Environmental variance, which reflects the variability due to environmental factors.
'PhenotypicVariance': Phenotypic variance, the sum of genotypic and environmental variances.
'GCV': Genotypic coefficient of variation, expressed as a percentage of the mean.
'PCV': Phenotypic coefficient of variation, expressed as a percentage of the mean.
'Heritability': Broad-sense heritability, the proportion of phenotypic variance attributable to genetic variance.
'GeneticAdvance': Genetic advance under selection, a measure of genetic improvement.
'GAPercentage': Genetic advance as a percentage of the mean, indicating the relative genetic improvement.
Falconer, D. S. (1996). "Introduction to Quantitative Genetics". ISBN: 9780582243026. Singh, R. K., & Chaudhary, B. D. (1985). "Biometrical Methods in Quantitative Genetic Analysis". ISBN: 9788122433764.
set.seed(123)
data <- data.frame(
Genotype = rep(c("G1", "G2", "G3"), each = 10),
Replication = rep(1:10, times = 3),
Trait = c(rnorm(10, 50, 5), rnorm(10, 55, 5), rnorm(10, 60, 5))
)
result <- breeding_metrics(data, "Genotype", "Trait", "Replication")
print(result)
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