Study of Morphological and Yield Atributing Characters in Indigenous Rice (Oryza Sativa L.) of Bastar
Journal Title: International Journal of Agricultural Science and Research (IJASR) - Year 2017, Vol 7, Issue 4
Abstract
The present study was carried out to study ninety four rice accessions, along with checks, on the basis of sixteen qualitative and twenty qualitative characters. Analysis of variance for quantitative characters showed differences for different characters. High coefficient of variation in the entire genotypes was observed for grain yield per plant (27.4 %), number of effective tillers per plant (22.37 %), test weight (21.14 %) and kernel length breadth ratio (20.59 %). Correlation analysis revealed positive and highly significant correlation of total number of filled grains per panicle, total number of grains per panicle, plant height and number of effective tiller per plant; harvest index, test weight, flag leaf length and days to maturity had positive highly significant correlation with grain yield per plant. Principal Component Analysis revealed, out of 20, only seven principal components (PCs) exhibited more than 1.00 eigen value, and showed about 77.42 % variability among the traits studied. So, these 7 PCs were given due importance for further explanation. Component matrix revealed that the PC1 was mostly related to quality characters while PC2, PC3, PC4, PC5, PC6 and PC7 mostly associated with yield related traits. Cluster analysis performed by UPGMA method using Euclidean distance as dissimilarity measure divided the 97 genotypes of rice into ten clusters. The cluster III constituted of 48 genotypes, forming the largest cluster followed by cluster VI (22 genotypes), cluster V (10 genotypes), cluster II (5 genotypes) and cluster VIII (4 genotypes), cluster I, IV and VII (two genotypes each), cluster IX and X had (only one genotypes each). Quality analysis performed for 97 rice genotypes revealed wide range of genetic variability for most of the quality traits.
Authors and Affiliations
Vipin Kumar Pandey, Sonali Kar
Keywords
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