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Environment & Ecology 33 (1B) : 421—425, January—March 2015 Website: environmentandecology.com ISSN 0970-0420

Variability Parameters, Correlation and Path Analysis in Wheat Varieties for Yield and its Components

Y. Kumar, R. A. S. Lamba, Vinod Kumar, Balbir Singh

Received 18 May 2014; Accepted 28 June 2014; Published online 19 July 2014

Abstract The present investigation was undertaken to study the variability parameters, correlation and path coefficient analysis for 10 metric traits in 17 wheat varieties under normal sown irrigated condition at CCS HAU, Regional Research Station, Bawal (Haryana) during rabi of 2012-13. Significant genotypic differences were observed for all the traits studied indicating considerable amount of variation among varieties for each trait. Phenotypic and genotypic coefficients of variation were highest in number of grains per spike followed by grain yield, harvest index, biological yield, 1000-grain weight and plant height. Moderate to high heritability in broad sense estimated for all the traits except number of tillers per meter row which exhibited low heritability. Moderate to high heritability coupled with high genetic advance as per cent of mean was

Y. Kumar*, R. A. S. Lamba, V. Kumar CCS Haryana Agricultural University, Regional Research Station, Bawal 123501, India B. Singh Krishi Vigyan Kendra, Bawal 123501, India e-mail : [email protected] *Correspondence

observed for number of grains per spike, harvest index, grain yield, 1000-grain weight and plant height indicating the importance of these traits in selection and crop improvement. Grain yield was significant and positively correlated with harvest index and 1000grain weight. Path coefficient analysis revealed that harvest index and biological yield had highest positive direct effect on grain yield (kg/plot). Hence, main emphasis should be given on harvest index, biological yield and 1000-grain weight in breeding program. Keywords Variability parameters, Correlation, Path analysis, Component traits, Wheat.

Introduction Wheat (Triticum aestivum L.) is the second most important cereal crop of India after rice, occupies an area of 29.65 million hectares with the production and productivity of 92.46 million tons and 3119 kg ha–1, respectively [1]. Information of genetic variability in the genetic system of a particular crop is sought as prerequisite with any crop improvement program. Although increased grain yield is the ultimate goal of the plant breeders, grain yield itself is a product of interaction of many component traits which influence it directly or indirectly. Therefore, variability existing within each component trait must be exploited by selection to realize maximum gain in grain yield. Correlation and path coefficient analysis together give a clear cut picture of interrelationship and relative contribution of independent characters on dependent vari-

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Table 1. Estimates of genetic variability parameters for different characters in wheat. Coefficients of variation (%) Phenotypic Genotypic (PCV) (GCV)

Characters

Mean ± SE (d)

Range

Plant height (cm) Spike length (cm) Days to heading Days to maturity No. of tillers per meter row No. of grains per spike 1000-grain weight (g) Harvest index (%) Biological yield (kg/plot) Grain yield (kg/plot)

98.28 ± 3.08 10.56 ± 0.45 97.82 ± 0.92 140.65 ± 0.94 175.80 ± 10.40 56.28 ± 2.30 31.12 ± 0.35 34.82 ± 1.39 9.41 ± 0.53 3.26 ± 0.24

81.00–127.00 9.00–13.73 93.00–106.00 138.0–145.0 132.0–208.0 45.20–76.20 24.20–36.20 22.78–48.05 7.50–12.00 1.98–4.15

able which enables a plant breeder to apply suitable selection procedures for crop improvement. Keeping this in view, the present investigation was undertaken to estimate variability parameters, correlation and path coefficient analysis in 17 wheat varieties for yield and its components under normal sown irrigated conditions.

Materials and Methods The experimental material consisted of 17 wheat varieties namely, WH 1080, WH 1081, PBW 621, WH 1021, WH 1105, WH 1025, HD 2851, PBW 373, PBW 550, WH 1098, DBW 17, HD 2967, C 306, WH 711, PBW 343, WH 542 and RAJ 3765. The material was evaluated in randomized block design with three replications at CCS HAU, Regional Research Station, Bawal (Haryana) during rabi of 2012-13. Each variety was grown in six rows with a plot size of 5 × 1.20 m2. Recommended package of practices were followed to raise the crop. The observations were recorded for 10 metric traits viz., plant height (cm), spike length (cm), number of tillers per meter row, number of grains per spike, days to heading, days to maturity, 1000-grain weight (g), harvest index (%), biological yield (kg/ plot) and grain yield (kg/plot). Five randomly selected competitive plants from each plot per replication were recorded for all the traits under study except of days to heading, days to maturity, biological yield and grain yield which were recorded on plot basis. Harvest index was calculated as per formula given by Donald

10.44 9.20 3.89 1.36 8.50 16.18 10.84 15.53 10.92 16.15

9.71 7.54 3.72 1.08 4.43 15.38 10.75 14.74 8.46 13.47

Heritability (bs) (%) 86.51 67.15 91.33 63.83 27.20 90.44 98.42 90.12 60.02 69.59

Genetic advance (% mean) 18.61 12.72 7.33 1.78 4.76 30.14 21.98 28.82 13.50 23.15

and Humblin [2]. The mean performance of each variety was employed for statistical analysis. Analysis of variance to test the significance for each character was carried out as per methodology given by Panse and Sukhatme [3]. Genotypic and phenotype coefficients of variation (GCV and PCV) were calculated by formula given by Burton [4], heritability in broad sense (h2) by Burton and Vane [5] and genetic advance given by Johnson et al. [6]. Correlation and path coefficients were worked out as per method suggested by AlJibouri et al. [7] and Dewey and Lu [8], respectively. Results and Discussion Significant differences were observed among the varieties for all the characters studied indicating considerable amount of variability among them. The estimates of genetic variability parameters for all the characters are presented in Table 1. In general, the results revealed wide range for all the traits under study. Phenotypic coefficients of variation (PCV) were greater than genotypic coefficients of variation (GCV) for all the characters which reflect the influence of environment on the expression of traits. Phenotypic and genotypic coefficients of variation were highest in number of grains per spike followed by grain yield, harvest index, biological yield, 1000-grain weight and plant height indicating availability of sufficient genetic variability and thus exhibited scope for genetic improvement through selection. However, days to

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Table 2. The estimates of genotypic correlation coefficients among 10 characters in wheat. *, ** Significant at 0.05 and 0.01 level, respectively.

Characters

Plant height (cm)

Spike length (cm)

Plant height (cm) 1.000 Spike length (cm) 0.380** 1.000 Days to heading 0.212 0.111 Days to maturity 0.332* 0.200 No. of tillers per 0.249 0.606** meter row No. of grains -0.261 -0.362** per spike 1000-grain wt. (g) -0.206 -0.174 Harvest index (%) -0.399** 0.018 Biological yield 0.075 0.296* (kg/plot) Grain yield (kg/plot) -0.374** 0.242

Days to heading

1.000 0.807** 0.648** -0.021

Days No. of No. of 1000- Harvest Biological to tillers per grains per grain wt. index yield maturity meter row spike (g) (%) (kg/plot)

1.000 0.539** -0.137

1.000 -0.151

1.000

-0.384** -0.530** -0.536** -0.135 -0.622** -0.665** -0.598** 0.018 0.433** 0.704** 0.760** -0.187 -0.409** -0.316*

heading and maturity exhibited least genotypic and phenotypic coefficients of variation. Similar findings were also reported by Sharma et al. [9] and Tripathi et al. [10] in bread wheat. Moderate to high heritability in broad sense estimated for all the traits except number of tillers per meter row which exhibited low heritability. These results are in agreement with the findings of Ali and Shakor [11] and Singh et al. [12] for higher magnitudes and Abinasa et al. [13] and Kotal et al. [14] for moderate estimates of heritability. High heritability indicated that the characters were less influenced by the environment. The estimates of heritability are more advantageous when expressed in terms of genetic advance. Moderate to high heritability coupled with high genetic advance as per cent of mean was observed for number of grains per spike, harvest index, grain yield, 1000-grain weight and plant height indicating the importance of these traits in selection and crop improvement. These results support the findings of Ali and Shakor [11]. Dawit et al. [15] observed low heritability with low genetic advance for number of tillers per plant. The estimates of genotypic correlation coefficients among 10 traits are depicted in Table 2. The grain yield was significant and positively correlated with harvest index and 1000-grain weight; and positively with spike length and biological yield. These

Grain yield (kg/plot)

-0.158

-0.097

1.000 0.696** -0.228

1.000 -0.376**

0.586**

0.831**

1000 0.194

1.000

results showed close resemblance with the report of Ali and Shakor [11] for harvest index and 1000-grain weight; and spike length and biological yield of Sharma et al. [9]. The significant negative association of grain yield with plant height, days to heading and maturity suggest that early heading and maturing dwarf genotypes may result in higher grain yield. These results are in agreement with the findings of Bhushan et al. [16] in wheat. Iftikhar et al. [17] and Singh et al. [18] reported negative association of tillers per plant and number of grains per spike with grain yield which support our findings. Significant and positive correlations were also observed for plant height with spike length and days to maturity; spike length with number of tillers per meter row and biological yield; days to heading and maturity with number of tillers per meter row and biological yield; number of tillers per meter row with biological yield; and 1000-grain weight with harvest index, thereby indicating that these traits may be improved simultaneously. Some authors reported significant positive correlation of plant height with spike length and days to maturity; spike length with tillers per plant and biological yield [19], days to heading and maturity with tillers per plant [17, 18] and biological yield [16]; tillers per plant with biological yield [19]; and 1000-grain weight with harvest index [11]. The significant positive association of days to heading was recorded with maturity, also reported by Khan et al. [20].

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Table 3. Direct (diagonal) and indirect effects of different characters on grain yield in wheat at genotypic level. Residual effect: 0.007, rg=genotypic correlation, *, ** Significant at 0.05 and 0.01 level, respectively.

Characters

Plant height (cm)

Spike length Days to (cm) heading

Plant height (cm) -0.022 0.006 Spike length (cm) -0.008 0.016 Days to heading -0.005 0.002 Days to maturity -0.007 0.003 No. of tillers per -0.006 0.010 meter row No. of grains per spike 0.006 -0.006 1000-grain wt. (g) 0.005 -0.003 Harvest index (%) 0.009 0.000 Biological yield -0.002 0.005 (kg/plot)

No. of No. of 1000- Harvest Days to tillers per grains per grain wt. index maturity meter row spike (g) (%)

Biorg with logical Grain yield yield (kg/plot) (kg/plot)

-0.016 -0.008 -0.073 -0.059 -0.047

0.012 0.007 0.029 0.036 0.019

0.030 0.074 0.079 0.066 0.122

-0.001 -0.002 0.000 -0.001 -0.001

-0.006 -0.005 -0.012 -0.017 -0.017

-0.415 0.019 -0.647 -0.692 -0.622

0.038 0.149 0.218 0.355 0.383

-0.374** 0.242 -0.409** -0.316* -0.158

0.002 0.028 0.046 -0.032

-0.005 -0.019 -0.024 0.025

-0.018 -0.065 -0.073 0.093

0.005 -0.001 0.000 -0.001

-0.004 0.031 0.022 -0.007

0.018 0.725 1.041 -0.392

-0.094 -0.115 -0.190 0.504

-0.097 0.586** 0.831** 0.194

Significant negative association were observed for plant height with harvest index; spike length with number of grains per spike; days to heading, maturity and number of tillers per meter row with 1000-grain weight and harvest index; biological yield with harvest index. Similar findings were also reported for plant height with harvest index [19]; spike length with grains per spike [21]; days to heading and maturity with 1000-grain weight [18, 22]; tillers per plant with harvest index [10] and 1000-grain weight [21]; and harvest index with biological yield [10]. Similar to our finding, Singh et al. [18] reported negative association of days to heading and maturity with harvest index.

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