Correlation and Regression Analyses for Yield and Yield Related Traits in Spring Wheat (<i>Triticum aestivum </i>L<i>.</i>)

The present experiment was conducted at the experimental area at Latif farm Sindh Agriculture University, Tandojam the experiment was laid out in randomized complete block design with three replications in order to study the inheritance pattern of various agronomic traits in six genotypes of wheat. Analysis of variance (ANOVA), mean performance, correlation, regression, and heritability were used to assess the genotypes. Twelve distinct features, derived from six different genotypes were subjected to an ANOVA. With the exception of tillers plant-1 and seed index, the mean squares of genotypes for all the traits were significantly (P≤0.05) different from one another, as were the mean squares for the bulk of the traits in the parents. In a similar vein, the majority of the qualities' mean squares likewise showed significant differences (P≤0.05). Every attribute under research differed considerably (P≤0.05) according to the analysis of variance for every genotype, indicating greater genetic diversity among the genotypes that can be further utilized for different breeding programs aimed at improving bread genotypes. With regards to heritability percentage in broad sense, genotypic variance (δ2g), phenotypic variance (δ2p), heritability h2 %, selection index and genetic advance (GA) of different wheat traits were significantly affected. Most of the yield-associated features have been successfully transferred, according to the current findings. According to the analysis of variance, there was a significant difference (P≤0.05) between all the features under investigation, indicating a higher level of genetic variability across the genotypes. This can be further utilized in various breeding programs to advance genotypes. In order to increase wheat grain yield, selection criteria that are beneficial may be provided by estimating correlation and doing regression analysis between yield and yield components. A rise in plant height will result in a proportional increase in related features, according to the correlation and regression analysis of plant height, which showed a statistically positive link with spikelet per spike-1, tillers per plant, grain per spike, and grain production.