AN APPLICATION OF ANALYSIS OF VARIANCE (ANOVA) FOR ESTIMATING VARIANCE COMPONENTS IN FARM CROPS (MAIZE)

The study applied the Analysis of Variance (ANOVA) technique to estimate the variance components associated with maize grain yield, with the aim of quantifying the relative contributions of genetic and environmental factors to the total variation. Five maize genotypes were evaluated across three locations using a Randomized Complete Block Design (RCBD) with three replications. Data collected on grain yield were analyzed using SPSS (Version 27), and the Restricted Maximum Likelihood (REML) method was employed to estimate variance components. The ANOVA results were revealed highly significant effects (p < 0.01) for both genotype and location, while the genotype × location interaction was not significant, indicating stable performance of genotypes across environments. The estimated genotypic variance (σ²G = 819955.467) was higher than the residual variance (σ²E = 16082.309), suggesting that most of the variation in maize yield was due to genetic differences among genotypes. The broad-sense heritability estimate was 0.98, implying that maize yield is highly heritable and that selection based on yield performance would be very effective. Finally we confirm that ANOVA and variance component analysis are powerful tools in quantifying genetic variability and assessing the stability of maize genotypes. The high heritability value underscores the importance of genetic factors in yield determination and supports the effectiveness of selection for yield improvement in maize breeding programs.