H. P. Chaturvedi*, D. Purushoama Rao and Sonali Dey

Department of Genetics and Plant Breeding, Nagaland University, SASRD, Medziphema - 797 106 (India) *Corresponding author Email: hpchaturvedi68@gmail.com

ABSTRACT

Understanding the existence of genetic variability in crops is of utmost importance to plant breeders in yield improvement programs. A varietal trail was conducted with nineteen lentil germplasm accessions obtained from the All India Coordinated Research Project on MULLaRP in Rabi-2021. The genotypes were planted in RCBD and the data were collected for 8 morphological traits. Based on the trail, presence of genetic variability among the genotypes, association among yield and yield contributing factors with respect to environmental condition of Nagaland as well as the genetic diversity in the population has been explained. These genotypes exhibited significant variability in respect of days to fifty percent flowering, days to maturity, plant height, plant stand percentage, number of pods per plant, number of branches per plant, seed index and seed yield per plant. Genetic variability studies showed presence of good amount of variation among the twenty genotypes. The highest GCV and PCV were recorded for seed yield per plot followed by number of pods per plant. Medium estimates were obtained for plant stand percentage, plant height, Seed index and number of branches per plant. High heritability coupled with high genetic advance as percent of mean was observed for all the traits in study except for days to 50% flowering and days to maturity. Seed yield per plot was positively and significantly correlated with plant height, Plants stand percentage, number of branches per plant and number of pods per plant. However, path analysis revealed only plant stand percentage, number of branches per plant and number of pods per plant to be the most important traits for yield improvement. Simultaneously, the K-mean clustering and principal coordinate analysis disclosed the existence of moderate to high genetic diversity among the tested genotypes classifying them in four distinct clusters useful for crossing programs.

Key words : Genetic variation, Heritability, Correlation, Path analysis, Genetic diversity, K-means Clustering, Principle component analysis.

Download FullText