Abstract

An experiment was conducted to evaluate 49 spring wheat (Triticum aestivum L.)  genotypes of diverse origin by estimating genetic parameters viz. variability, character association, path coefficient, cluster and principle component analysis (PCA) for yield and spot blotch disease resistance during 2011 -2012 and 2012 - 2013. Highest phenotypic coefficient of variation (PCV) was observed for area under disease progress curve (AUDPC) (29.15%), plot yield (12.94%) and 1000-kernel weight (11.63%). The highest plot yield (g) was observed in genotypes WH1132 and WH 1131. Grain yield per plot (g) was significantly and positively associated with the 1000-kernel weight (g) (0.82*) and grain per spike (number) (0.79*). Path-coefficient analysis expressed that the maximum positive direct effect on yield showed by grain per spike (number) observed via 1000-kernel weight (g) and days to 75% flowering (days) while negative direct effects showed by 1000-kernel weight (g), AUDPC, days to maturity (days) and plant height (cm). All the 49 spring wheat genotypes were grouped into six distinct clusters. The genotypes of cluster II represented higher yield and disease resistance potential. Out of the major four principal components (PCs), three principal components (PC1, PC2 and PC3) accounted for 79.86% with proportionate values of 45.90, 18.73 and 15.23%, respectively. The third principal component has high positive component value for the days to 75% flowering, the plant height, the AUDPC and the 1000-kernel weight. The breeding objective of the present experiment is to identify genetically diverse wheat genotypes for developing high yielding and disease resistant variety for Eastern Gangetic Plains of India.     Key words: AUDPC, cluster analysis, dendrogram, genetic advance, yield, PCA and PCV.

Highlights

  • Wheat (Triticum aestivum L.) is the largest grown and second prominent produced cereal crops worldwide after maize (Zea mays L.) with 697.8 million tonnes every year (Anonymous, 2013; Velu and Singh, 2013)

  • Observations were recorded for seven quantitative traits viz. days to 75% flowering, days to maturity, plant height, 1000kernel weight. (g), grain per spike, area under disease progress curve (AUDPC value) and plot yield (g) through random sampling method

  • L.) genotypes were analyzed for genetic studies viz., the genetic variability, the character association, the cluster analysis and principal component analysis (PCA) for examined yield components and spot blotch resistance

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Summary

Full Length Research Paper

L.) genotypes for yield and spot blotch resistance in Eastern Gangetic Plains of India. Highest phenotypic coefficient of variation (PCV) was observed for area under disease progress curve (AUDPC) (29.15%), plot yield (12.94%) and 1000-kernel weight (11.63%). Grain yield per plot (g) was significantly and positively associated with the 1000-kernel weight (g) (0.82*) and grain per spike (number) (0.79*). Pathcoefficient analysis expressed that the maximum positive direct effect on yield showed by grain per spike (number) observed via 1000-kernel weight (g) and days to 75% flowering (days) while negative direct effects showed by 1000-kernel weight (g), AUDPC, days to maturity (days) and plant height (cm). The third principal component has high positive component value for the days to 75% flowering, the plant height, the AUDPC and the 1000-kernel weight.

INTRODUCTION
International License
MATERIALS AND METHODS
Genetic advance
RESULTS AND DISCUSSION
Genetic divergence analysis
The mean performance of the cluster genotypes for
Cluster VI
The cluster IV has eight genotypes accounting for
Full Text
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