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Genetic diversity and correlation studies in chickpea (Cicer arietinum L.) based on morphological traits
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The present study was conducted to evaluate the selection criteria in 48 chickpea germplasm accessions using correlation, path analysis, principal component analysis and cluster analysis based on fourteen morphological traits. These traits included seven vegetative traits (viz., plant height, plant width, number of basal primary branches per plant, number of apical primary branches per plant, number of basal secondary branches per plant, number of apical secondary branches per plant and number of tertiary branches per plant), one flowering trait (days to fifty per cent flowering) and six yield related traits (days to maturity, number of pods per plant, number of seeds per pod, number of seeds per plant, hundred seed weight and single plant yield). Basic descriptive statistics showed normal distribution for six morphological traits. However significant and positive skewness were observed for plant width (1.15), number of apical primary branches per plant (1.68), number of basal secondary branches per plant (1.18), number of tertiary branches per plant (1.86), days to maturity (0.91), number of seeds per pod (0.78), number of seeds per plant (0.72) and hundred seed weight (1.48). ANOVA revealed that significant genotypic variation existed for most of the traits. Traits such as plant width (0.346), number of pods per plant (0.788), number of seeds per pod (0.055), number of seeds per plant (0.675) and hundred seed weight (0.477) exhibited significant positive correlation with single plant yield whereas a strong negative association was exhibited by days to fifty per cent flowering (-0.418) and days to maturity (-0.331). Correlation among component traits revealed a strong negative association of hundred seed weight with seeds per pod (-0.36). Path analysis specified that the highest positive direct effect on single plant yield was exerted by number of pods per plant (0.86) and hundred seed weight (0.589). Principal component analysis (PCA) revealed that the first five components with Eigen values more than one contributed to a maximum of 77.58 per cent of the variability. PC1 contributed 26.59 per cent of the total variation and the traits contributing to maximum variation in first component included plant width (0.712), number of pods per plant (0.692), number of seeds per plant (0.621), number of apical secondary branches per plant (0.54) and plant height (0.538). The Wards method of hierarchical cluster analysis grouped the accessions into two major clusters. Cluster I comprised of genotypes with high mean values for hundred seed weight (20.65) whereas cluster II, showed superior contribution for number of pods per plant (40.27), number of seeds per pod (1.06), number of seeds per plant (42.52) and single plant yield (6.88g). The grouping of chickpea germplasm based on various agro-morphological traits would be useful to identify the promising genotypes for effective utilization in future breeding programmes.
EJPB, ISPB, CPBG - Tamil Nadu Agricultural University
Title: Genetic diversity and correlation studies in chickpea (Cicer arietinum L.) based on morphological traits
Description:
The present study was conducted to evaluate the selection criteria in 48 chickpea germplasm accessions using correlation, path analysis, principal component analysis and cluster analysis based on fourteen morphological traits.
These traits included seven vegetative traits (viz.
, plant height, plant width, number of basal primary branches per plant, number of apical primary branches per plant, number of basal secondary branches per plant, number of apical secondary branches per plant and number of tertiary branches per plant), one flowering trait (days to fifty per cent flowering) and six yield related traits (days to maturity, number of pods per plant, number of seeds per pod, number of seeds per plant, hundred seed weight and single plant yield).
Basic descriptive statistics showed normal distribution for six morphological traits.
However significant and positive skewness were observed for plant width (1.
15), number of apical primary branches per plant (1.
68), number of basal secondary branches per plant (1.
18), number of tertiary branches per plant (1.
86), days to maturity (0.
91), number of seeds per pod (0.
78), number of seeds per plant (0.
72) and hundred seed weight (1.
48).
ANOVA revealed that significant genotypic variation existed for most of the traits.
Traits such as plant width (0.
346), number of pods per plant (0.
788), number of seeds per pod (0.
055), number of seeds per plant (0.
675) and hundred seed weight (0.
477) exhibited significant positive correlation with single plant yield whereas a strong negative association was exhibited by days to fifty per cent flowering (-0.
418) and days to maturity (-0.
331).
Correlation among component traits revealed a strong negative association of hundred seed weight with seeds per pod (-0.
36).
Path analysis specified that the highest positive direct effect on single plant yield was exerted by number of pods per plant (0.
86) and hundred seed weight (0.
589).
Principal component analysis (PCA) revealed that the first five components with Eigen values more than one contributed to a maximum of 77.
58 per cent of the variability.
PC1 contributed 26.
59 per cent of the total variation and the traits contributing to maximum variation in first component included plant width (0.
712), number of pods per plant (0.
692), number of seeds per plant (0.
621), number of apical secondary branches per plant (0.
54) and plant height (0.
538).
The Wards method of hierarchical cluster analysis grouped the accessions into two major clusters.
Cluster I comprised of genotypes with high mean values for hundred seed weight (20.
65) whereas cluster II, showed superior contribution for number of pods per plant (40.
27), number of seeds per pod (1.
06), number of seeds per plant (42.
52) and single plant yield (6.
88g).
The grouping of chickpea germplasm based on various agro-morphological traits would be useful to identify the promising genotypes for effective utilization in future breeding programmes.
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