COMPARISON OF SELECTION INDICES BASED ON PER CENT RELATIVE EFFICIENCY IN FINGER MILLET CROP 

Abstract

The data on different biometrical characters of 40 genotypes of finger millet were collected from a P. G. student research work of AAU, Anand for present study. The experiment was carried out in randomised block design with three replications at the Genetics and Plant Breeding Farm, AAU, Anand during kharif 2020. Six distinct biometrical characteristics of forty genotypes of finger millet were used in the experiment: days to maturity, main ear length (cm), plant height (cm), test weight (g), productive tillers per plant and grain yield per plant (g). To investigate the crop improvement the selection index technique was used by assigning different weights to each biometric characters. Selection indices for individual characters, combinations of two characters, combinations of three characters, and so forth were computed. The combination that produced the highest relative efficiency was selected. Between yield and yield-attributing traits, the basic correlation coefficient, genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) were calculated. Six biometric characters were used to calculate the selection indices, which were then built using all potential character combinations. Using the simple correlation coefficient[W₁], GCV[W₂] and PCV[W₃] as weights for each character, a total of 63 selection indices were created. Different indicators' predicted genetic advance and percent relative efficiency (PRE) were determined. The findings showed that, across all index combinations PRE with standard deviation as its weight was generally greater than the other weights. The selection index I₂₄₅₆ in GCV weight method was found the best.