Barley Genetics Newsletter 37: 24-28 (2007)

**Genetic Architecture for Yield and Quality Component Traits Over Two
Environments in Barley (*Hordeum vulgare* L.)**

# Ambresh Kumar Verma, S.R. Vishwakarma and P.K. Singh

# 

> Department of Genetics and Plant Breeding
>
> Narendra Deva University of Agriculture and Technology,
>
> Kumarganj, Faizabad, (UP) 224 229, INDIA.
>
> e-mail: ambreshv@gmail.com

**Abstract**

Triple test-cross analysis involving three testers K-560, Narendra Jau-3
and their hybrid K-560 x Narendra Jau-3, were cross to 15
strains/varieties of barley to estimate the epistatic, additive and
dominance components of genetic variance. Modified triple test-cross was
done for eleven metric traits in two \[normal fertile soil (E~1~) and
saline sodic soil (E~2~)\] environments. Epistasis was evident for all
the characters under study in both environments except plant height in
E~2~, protein content in E~1~ and lysine content in both conditions. The
i type epistasis was significant for seed yield per plant in E~1~ only,
while j and l type epistasis were significant for most of the traits.
Additive (D) component was important in all cases in both conditions
except number of effective tillers per plant in E~1~ and lysine content
in E~1~ & E~2~ where as non fixable dominance (H) component were
significant for all the characters in both conditions except number of
effective tillers per plant in E~1~, length of main spike in E~2~ and
lysine content in both environments. The most of the traits showed
partial dominance and directional element, F was non- significant for
all the traits, suggesting ambidirectional nature of dominance.

**Key words:** barley, modified triple test-cross, genetic variation,
protein content, seed yield

**Introduction**

To enable present barley varieties acceptable in the international
market, there is need to develop better quality genotypes suitable for
making product with consumer acceptability. Thus there is an urgent need
to improve grain quality as well as develop better quality genotypes for
suitable processing industry. The consumer acceptability of genotype is
affected by chemical constituent of the grains. It is therefore,
desirable to access basic physiochemical characteristics of the grains
so that these can be combined with high yield. The information about
nature and magnitude of genetic components of variance for yield and
quality characters is essential for planning an efficient breeding
programme in any crop. The modified triple test-cross analysis of
(Ketata *et al*., 1976) provide efficient detection and estimation of
epistatic variance along with unbiased estimates of additive and
dominance component of genetic variance in determining the inheritance
of eleven traits in barley using modified triple test-cross (TTC)
analysis.

**Materials and Methods**

Two barley pure lines, viz. testers K-560, Narendra Jau-3 and their
hybrid (K-560 x Narendra Jau-3) were cross to 15 lines (Kedar, RD-2552,
Narendra Jau-1, Narendra Jau-2, Narendra Jau-4, RD-2035, BL-2, BH-512,
Ratna, Jagrati, DL-88, Azad, K-603, NDB-1173 and RD-2624) of barley to
develop a set of 45 crosses. The experimental materials consisting of 3
testers, 15 lines, 30 single crosses and 15 three-way crosses were
evaluated in randomized block design with three replications during
*rabi* 2004-05 in two viz. normal fertile soil (E~1~) and saline sodic
(E~2~) condition at Genetics and Plant Breeding Research Farm of
Narendra Deva University of Agriculture & Technology, Kumarganj ,
Faizabad, U.P. India. Each entry was shown in a 3 m long single row
plant with 10 cm spacing within and 25 cm between rows. Observations
were recorded on five randomly selected competitive plants for eleven
quantitative traits (Table 1). The pelshenke vale, protein content and
lysine content were estimated by the method of (Pelshenke, 1933;
Lowery's, 1951; and Felker *et al*.; 1978) respectively. Character means
were used for modified triple test- cross analysis (Ketata *et al*.,
1976).

**Results and Discussion**

The triple test-cross (TTC) analysis revealed that significant epistasis
was present for all the characters in both environments except plant
height in E~2~ , protein content in E~1~ and lysine content in both
conditions (Table 1). The partitioning of epistasis in to i and j and l
types showed that additive x additive (i) interaction was significant
for seed yield per plant in normal fertile soil condition only. The j
and l type epistasis was significant for all the characters in both the
environments except days to maturity and protein content in E~1~ while
lysine content in both environments. Existence of significant epistasis
in inheritance of seed yield and some other yield components in barley
was reported by others also (Gorshkova and Gorodov, 1981). Greater
importance of j and l type epistasis than i component was reported
earlier by (Singh, *et al*., 1984; Tripati and Singh, 1983; Verma and
Yunus, 1986.). On the contrary, (Nanda, *et al*., 1982) reported i type
epistasis to be more important than j and l type epistasis, and (Singh,
1980) reported equal importance of these two sub components. The
estimates of the components of genetic variance, additive (D), dominance
(H) and F components and the degree of dominance (H/D^0.5^) are given in
Table 2. The additive (D) component was important in all cases in both
conditions except number of effective tillers per plant in E~1~ and
lysine content in E~1~ & E~2~ where as non fixable dominance (H)
component was significant for all the characters in both condition
except number of effective tillers per plant in E~1~, length of main
spike in E~2~ and lysine content in both environments. The estimates of
D were higher than H for most of the traits, which suggested partial
dominance. The directional element of dominance, F was non-significant
for all the characters in both environments indicated presence of
ambidirectional dominance, and alleles with increasing and decreasing
effects appear to be dominant and recessive to the same extent. The
significant of additive component for seed yield and quality component
traits, except number of effective tillers per plant and lysine content
indicates that substantial improvement in yield status can still be
achieved by following conventional breeding procedure in barley. The
significant contribution of additive x additive type epistasis for seed
yield suggested that this component should not be ignored while
predicting the recombinants extractable from segregating generations.
Further results provided evidence of j and l type epistasis for most of
the traits studied. However, in autogamus crops like barley, where
commercial exploitation of hybrid has started, this type of epistasis is
of more use.

**References**

Felker, C.; Libanauskas, C.K.; Wainer, G. 1978. Estimation of lysine in
foods. Crops Sci. 18:480-490.

Gorshkova, V.A.; Gorodova, V.T. 1981. Use of top crosses in studying
breeding material of spring barley. Biological Lelektsiyai Semeno Vod
Zorm Culture 47:54.

Ketata, H.; Smith, E.L.; Edwards, L.H.; McNew, R.W. 1976. Detection of
epistatic, additive and dominance variance in winter wheat (*Triticum
aestivum* L.). Crop Sci. 16:1- 4.

Lowry's, O.H.; Roserbrough, N.J.; Farr, A.L.; Randall, R.J. 1951.
Protein measurement with the folin phenol reagent. J. Biol. Chem.
193:265-278.

Nanda, G.S.; Singh, P.; Gill, K.S. 1982. Epistasis, additive and
dominance variation in triple test cross of bread wheat. Theor. Appl.
Genet. 62:49-52.

Pelshenke, P.A. 1933. A short method for determination of gluten quality
of wheat. Cereal Chem. 10-90.

Singh, G.; Nanda, G.S.; Gill, K.S. 1984. Inheritance of yield and its
components in five crosses of spring wheat. Indian J. agric. Sci.
54:943-949.

Singh, S. 1980. Detection of component of genetic variance and genotype
x environment interaction in spring wheat. J. agric. Sci. Camb.
95:67-72.

Tripathi, I.D.; Singh, M. 1983. Triple test-cross analysis in three
barley populations under saline alkaline soil conditions. J. agric. Sci.
Camb. 101:117-121.

Verma, S.S.; Yunus,M. 1986. Role of epistasis in the analysis of genetic
component of variance in bread wheat. Indian J. agric. Sci. 56:687-689.

Table 1. ANOVA (mean square) of triple test-cross to test epistasis for
eleven characters in barley under

normal fertile soil (E~1~) and saline sodic soil condition (E~2~)

<table style="width:100%;">
<colgroup>
<col style="width: 13%" />
<col style="width: 7%" />
<col style="width: 4%" />
<col style="width: 7%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 7%" />
<col style="width: 6%" />
<col style="width: 7%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 7%" />
</colgroup>
<tbody>
<tr class="odd">
<td>Sources of variation</td>
<td><p>Environ-</p>
<p>ments</p></td>
<td>d.f.</td>
<td>Days to maturity</td>
<td>Plant height (cm)</td>
<td>No. of effective tillers /plant</td>
<td>Length of main spike (cm)</td>
<td><p>Grains per</p>
<p>spike</p></td>
<td><p>Seed yield/ plant</p>
<p>(g)</p></td>
<td><p>1000 seed weight</p>
<p>(g)</p></td>
<td>Pelshenke value (minutes)</td>
<td><p>Protein</p>
<p>content</p>
<p>(%)</p></td>
<td><p>Lysine</p>
<p>content</p>
<p>(%)</p></td>
<td><p>Husk</p>
<p>content</p>
<p>(%)</p></td>
</tr>
<tr class="even">
<td rowspan="2">‘i’ Type epistasis</td>
<td rowspan="2"><p>E<sub>1</sub></p>
<p>E<sub>2</sub></p></td>
<td rowspan="2">1</td>
<td>7.20</td>
<td>3.99</td>
<td>0.17</td>
<td>10.86</td>
<td>428.76</td>
<td>22.36*</td>
<td>9.16</td>
<td>2121.80</td>
<td>0.61</td>
<td>0.75</td>
<td>5.83</td>
</tr>
<tr class="odd">
<td>369.80</td>
<td>220.81</td>
<td>8.28</td>
<td>3.64</td>
<td>366.35</td>
<td>300.13</td>
<td>0.793</td>
<td>1355.77</td>
<td>2.11</td>
<td>1.49</td>
<td>1.12</td>
</tr>
<tr class="even">
<td rowspan="2">‘j+I’ type pistasis</td>
<td rowspan="2"><p>E<sub>1</sub></p>
<p>E<sub>2</sub></p></td>
<td rowspan="2">14</td>
<td>37.53</td>
<td>34.78**</td>
<td>8.13**</td>
<td>1.64**</td>
<td>206.09**</td>
<td>81.08**</td>
<td>25.28**</td>
<td>315.23**</td>
<td>4.40</td>
<td>0.56</td>
<td>205.13**</td>
</tr>
<tr class="odd">
<td>74.66**</td>
<td>43.17**</td>
<td>11.57**</td>
<td>1.21**</td>
<td>307.31**</td>
<td>169.98**</td>
<td>23.90*</td>
<td>330.28**</td>
<td>7.46**</td>
<td>0.97</td>
<td>131.66**</td>
</tr>
<tr class="even">
<td rowspan="2">Total epistasis</td>
<td rowspan="2"><p>E<sub>1</sub></p>
<p>E<sub>2</sub></p></td>
<td rowspan="2">15</td>
<td>35.51*</td>
<td>32.73**</td>
<td>7.60**</td>
<td>2.25**</td>
<td>220.93**</td>
<td>77.16**</td>
<td>24.20**</td>
<td>435.66**</td>
<td>4.15</td>
<td>0.57</td>
<td>191.84**</td>
</tr>
<tr class="odd">
<td>94.33**</td>
<td>55.01</td>
<td>11.35**</td>
<td>1.37**</td>
<td>311.24**</td>
<td>178.65**</td>
<td>22.36*</td>
<td>398.64**</td>
<td>7.10**</td>
<td>0.90</td>
<td>122.96**</td>
</tr>
<tr class="even">
<td rowspan="2">‘i’ type epistasis x blocks</td>
<td rowspan="2"><p>E<sub>1</sub></p>
<p>E<sub>2</sub></p></td>
<td rowspan="2">2</td>
<td>1.80</td>
<td>1.00</td>
<td>4.34**</td>
<td>2.71**</td>
<td>107.19**</td>
<td>5.59</td>
<td>2.29**</td>
<td>530.45**</td>
<td>0.15</td>
<td>0.19</td>
<td>1.46</td>
</tr>
<tr class="odd">
<td>92.45**</td>
<td>55.20*</td>
<td>2.07**</td>
<td>0.91**</td>
<td>91.59*</td>
<td>75.03**</td>
<td>0.198</td>
<td>338.94**</td>
<td>0.527</td>
<td>3.73</td>
<td>0.28</td>
</tr>
<tr class="even">
<td rowspan="2">‘j+I’ type epistasis x blocks</td>
<td rowspan="2"><p>E<sub>1</sub></p>
<p>E<sub>2</sub></p></td>
<td rowspan="2">28</td>
<td>15.64</td>
<td>7.92</td>
<td>0.14</td>
<td>0.43</td>
<td>24.12</td>
<td>3.34</td>
<td>0.18</td>
<td>32.68</td>
<td>9.62</td>
<td>1.28</td>
<td>2.03</td>
</tr>
<tr class="odd">
<td>2.53</td>
<td>14.17</td>
<td>0.32</td>
<td>0.15</td>
<td>23.78</td>
<td>0.723</td>
<td>12.15</td>
<td>11.18</td>
<td>0.71</td>
<td>1.80</td>
<td>0.31</td>
</tr>
<tr class="even">
<td rowspan="2">Total epistasis x blocks</td>
<td rowspan="2"><p>E<sub>1</sub></p>
<p>E<sub>2</sub></p></td>
<td rowspan="2">30</td>
<td>14.72</td>
<td>7.46</td>
<td>0.14</td>
<td>0.55</td>
<td>29.66</td>
<td>3.49</td>
<td>0.32</td>
<td>36.86</td>
<td>10.00</td>
<td>2.42</td>
<td>1.99</td>
</tr>
<tr class="odd">
<td>8.53</td>
<td>16.91</td>
<td>0.43</td>
<td>0.20</td>
<td>28.30</td>
<td>5.68</td>
<td>11.36</td>
<td>33.03</td>
<td>0.69</td>
<td>2.68</td>
<td>0.49</td>
</tr>
</tbody>
</table>

\*, \*\* Significant at 5% and 1% probability levels, respectively.

# 

# 

# 

# Table 2. Estimates of additive (D) and dominance (H) components of variance, parameter F, and degree of dominance (H/D)^0.5^ 

#  in barley under normal fertile soil (E~1~) and saline sodic soil (E~2~ ) condition 

<table style="width:100%;">
<colgroup>
<col style="width: 10%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 8%" />
<col style="width: 8%" />
<col style="width: 6%" />
<col style="width: 8%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 8%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 8%" />
</colgroup>
<tbody>
<tr class="odd">
<td>Sources of variation</td>
<td><p>Environ-</p>
<p>ments</p></td>
<td><p>Days to</p>
<p>maturity</p></td>
<td><p>Plant</p>
<p>height</p>
<p>(cm)</p></td>
<td><p>Number</p>
<p>o f</p>
<p>effective</p>
<p>tillers /</p>
<p>plant</p></td>
<td>Length of main spike (cm)</td>
<td><p>Grains per</p>
<p>spike</p></td>
<td><p>Seed</p>
<p>yield/</p>
<p>plant</p>
<p>(g)</p></td>
<td><p>1000 seed</p>
<p>weight</p>
<p>(g)</p></td>
<td>Pelshenke value (minutes)</td>
<td><p>Protein</p>
<p>content</p>
<p>(%)</p></td>
<td><p>Lysine</p>
<p>content</p>
<p>(%)</p></td>
<td><p>Husk</p>
<p>content</p>
<p>(%)</p></td>
</tr>
<tr class="even">
<td rowspan="2">D</td>
<td rowspan="2"><p>E<sub>1</sub></p>
<p>E<sub>2</sub></p></td>
<td>25.51**</td>
<td>429.12**</td>
<td>4.67</td>
<td>4.70**</td>
<td>520.15**</td>
<td>67.72**</td>
<td>17.21**</td>
<td>250.46**</td>
<td>16.77**</td>
<td>1.63</td>
<td>125.83**</td>
</tr>
<tr class="odd">
<td>40.72**</td>
<td>150.58**</td>
<td>2.64**</td>
<td>2.60**</td>
<td>239.90**</td>
<td>50.43**</td>
<td>22.74**</td>
<td>190.35**</td>
<td>14.75**</td>
<td>1.90</td>
<td>78.26**</td>
</tr>
<tr class="even">
<td rowspan="2">H</td>
<td rowspan="2"><p>E<sub>1</sub></p>
<p>E<sub>2</sub></p></td>
<td>20.09**</td>
<td>20.06**</td>
<td>3.11</td>
<td>1.46**</td>
<td>167.30**</td>
<td>33.78**</td>
<td>12.57**</td>
<td>374.09**</td>
<td>4.89**</td>
<td>0.86</td>
<td>77.24**</td>
</tr>
<tr class="odd">
<td>37.45**</td>
<td>45.28**</td>
<td>4.41**</td>
<td>0.76</td>
<td>224.90**</td>
<td>69.57**</td>
<td>10.56**</td>
<td>237.02**</td>
<td>8.30**</td>
<td>0.65</td>
<td>57.05**</td>
</tr>
<tr class="even">
<td rowspan="2">(H/D)<sup>0.5</sup></td>
<td rowspan="2"><p>E<sub>1</sub></p>
<p>E<sub>2</sub></p></td>
<td>0.60</td>
<td>0.22</td>
<td>0.82</td>
<td>0.56</td>
<td>0.57</td>
<td>0.71</td>
<td>0.85</td>
<td>1.22</td>
<td>0.54</td>
<td>0.74</td>
<td>0.83</td>
</tr>
<tr class="odd">
<td>0.96</td>
<td>0.55</td>
<td>1.29</td>
<td>0.54</td>
<td>0.81</td>
<td>1.17</td>
<td>0.68</td>
<td>1.12</td>
<td>0.75</td>
<td>0.58</td>
<td>0.85</td>
</tr>
<tr class="even">
<td rowspan="2">F</td>
<td rowspan="2"><p>E<sub>1</sub></p>
<p>E<sub>2</sub></p></td>
<td>0.28</td>
<td>0.18</td>
<td>0.31</td>
<td>0.03</td>
<td>0.02</td>
<td>0.04</td>
<td>0.26</td>
<td>-0.08</td>
<td>-0.06</td>
<td>-0.25</td>
<td>0.20</td>
</tr>
<tr class="odd">
<td>0.10</td>
<td>-0.02</td>
<td>0.15</td>
<td>0.12</td>
<td>0.11</td>
<td>-0.10</td>
<td>0.20</td>
<td>-0.27</td>
<td>0.01</td>
<td>-0.05</td>
<td>0.19</td>
</tr>
</tbody>
</table>

\*, \*\* Significant at 5% and 1% probability levels, respectively.