Pooled analysis of variance
Presence of genetic variability is the basic requirement for developing high yielding hybrids in sunflower breeding programme. Pooled analysis of variance for experimental design shown in table 2, indicated significant differences among genotypes, parents and crosses for all the studied traits confirming that the data is worth for genetic analysis.
The pooled analysis of variance for combining ability due to different source for twelve characters (table 3) revealed that seasonal variation was significant for all the traits except stem diameter, volume weight and seed filling percentage. The mean squares of lines and testers from crosses both determine the GCA were also significant for most of the traits which revealed the prevalence of additive variances and additive gene action. The mean squares of lines x tester interactions were significant for all the traits considered. The significance of lines x tester interactions indicated that SCA is also important in the expression of traits and demonstrated the value of non-additive variances and dominant genes controlling the above traits. Memon et al. (2015), Lakshman et al. (2019) and Hilli et al. (2020) also observed that both additive and non-additive genetic variations were equally important for yield and its contributing traits in sunflower.
Table 2: Pooled Analysis of variance for seed yield and its attributing traits in sunflower.
Source of Variations
|
d.f
|
Days to 50% flowering
|
Plant height (cm)
|
Head diameter (cm)
|
Stem diameter (cm)
|
Days to
Maturity
|
100 seed weight (g)
|
Volume weight (g/100ml)
|
Seed yield (kg/ha)
|
Hull content (%)
|
Seed filling percent
|
Oil content (%)
|
Oil yield (Kg/ha)
|
Replicates
|
1
|
0.65
|
87.08
|
2.94
|
0.05
|
3.02
|
0.05
|
2.66
|
171553.20
|
20.28
|
9.89
|
15.15**
|
49072.42**
|
Season
|
1
|
973.11**
|
6509.30**
|
18.72**
|
0.07**
|
1024.06**
|
16.18**
|
17.86*
|
1000458.85**
|
138.82**
|
0.0002
|
46.07**
|
1566180.65**
|
Genotypes
|
64
|
29.22**
|
1411.20**
|
7.97**
|
0.15**
|
40.95**
|
1.64**
|
27.02**
|
1321399.76**
|
34.35**
|
37.25**
|
42.01**
|
178416.71**
|
Crosses
|
49
|
22.74**
|
558.12**
|
1.05**
|
0.05**
|
34.67**
|
0.69**
|
29.43**
|
147303.15**
|
30.69**
|
37.99**
|
42.65**
|
46769.87**
|
Hybrids
|
36
|
4.66**
|
184.93**
|
0.84**
|
0.04**
|
12.42**
|
0.48**
|
6.71**
|
99531.47**
|
22.14**
|
21.65
|
7.57**
|
15804.85**
|
Parents vs Crosses
|
1
|
21.34**
|
25165.55**
|
204.28**
|
3.74**
|
4.02
|
25.37**
|
35.51**
|
54769267.49**
|
316.93**
|
190.94**
|
469.24
|
5669203.23**
|
Error
|
128
|
1.08
|
47.47
|
0.21
|
0.01
|
1.70
|
0.08
|
3.29
|
36192.46
|
0.92
|
1.77
|
0.22
|
4299.63**
|
** Significant at P ≤ 0.01
*Significant at P ≤ 0.05
Table 3: Pooled Analysis of variance for combining ability for seed yield and its attributing traits in sunflower.
Source of Variations
|
d.f
|
Days to 50% flowering
|
Plant height (cm)
|
Head diameter (cm)
|
Stem diameter (cm)
|
Days to maturity
|
100 seed weight (g)
|
Volume weight (g/100ml))
|
Seed yield (kg/ha)
|
Hull content (%)
|
Seed filling percent
|
Oil content (%)
|
Oil yield (Kg/ha)
|
Replicates(R)
|
1
|
1.280
|
0.551
|
1.84
|
0.03
|
1.45
|
0.048
|
10.37
|
289205.52
|
29.28**
|
28.74
|
17.81
|
75365.55
|
Season(S)
|
1
|
1003.52**
|
12987.88**
|
1.51**
|
0.002
|
804.01**
|
12.370**
|
4.14
|
9889505.58**
|
140.47**
|
0.05
|
51.69**
|
1550970.81**
|
R X S
|
1
|
0.02
|
3191.21**
|
1.28*
|
0.002
|
1.13
|
0.094
|
53.54**
|
48921.94
|
6.65**
|
0.42
|
17.01**
|
167.21
|
Crosses (C)
|
49
|
22.74**
|
558.12**
|
1.05**
|
0.05**
|
34.67**
|
0.686**
|
29.43**
|
147303.15**
|
30.69**
|
37.99**
|
42.65**
|
46769.87**
|
Lines (L)
|
4
|
80.04**
|
2723.99**
|
1.67
|
0.03
|
111.79**
|
2.301**
|
101.65**
|
341161.03*
|
103.75**
|
131.40**
|
430.24**
|
359201.58**
|
Tester (T)
|
9
|
69.62**
|
1088.27**
|
1.61
|
0.10*
|
89.41**
|
0.790
|
88.19**
|
252230.83*
|
32.48
|
61.86*
|
10.73
|
31771.40
|
Lines X Tester
|
36
|
4.66**
|
184.93**
|
0.84**
|
0.04**
|
12.42**
|
0.481**
|
6.71**
|
99531.47**
|
22.14**
|
21.65**
|
7.57**
|
15804.85**
|
S X C
|
49
|
2.64*
|
132.63**
|
0.42**
|
0.003
|
5.64**
|
0.043
|
1.42
|
24376.23
|
1.14
|
1.31
|
0.18
|
4238.55
|
S X L
|
4
|
3.66
|
124.19
|
0.29
|
0.002
|
1.22
|
0.02
|
11.84**
|
40277.69
|
0.23
|
1.45
|
0.07
|
12637.04**
|
S X T
|
9
|
4.63*
|
168.23
|
0.68
|
0.001
|
9.03
|
0.07
|
0.51
|
42703.38*
|
1.01
|
0.85
|
0.10
|
6221.01*
|
S X LxT
|
36
|
2.03*
|
124.67**
|
0.37*
|
0.001
|
5.28**
|
0.03
|
0.48
|
18027.61
|
1.27
|
1.40
|
0.21
|
2809.76
|
Error
|
98
|
1.15
|
41.21
|
0.20
|
0.007
|
2.04
|
0.083
|
3.21
|
44015.29
|
0.88
|
1.32
|
0.17
|
5078.78
|
** Significant at P ≤ 0.01
*Significant at P ≤ 0.05
Table 4: Estimates of general combining ability effects of lines for seed yield and its attributes in sunflower
Lines
|
Days to 50% flow
ering
|
Plant height (cm)
|
Head diameter (cm)
|
Stem diameter (cm)
|
Days to maturity
|
100 seed weight (g)
|
Volume weight (g/100ml)
|
Seed yield (Kg/ha)
|
Hull content (%)
|
Seed filling percent
|
Oil content (%)
|
Oil yield (Kg/ha)
|
ARG-2-1-2
|
-1.670**
|
4.088**
|
0.270**
|
0.0001
|
2.580 **
|
0.363 **
|
0.473
|
93.574 **
|
-0.969 **
|
1.686 **
|
2.571 **
|
83.189 **
|
MUT-2-8-3-2
|
0.155
|
4.430**
|
-0.075
|
-0.005
|
0.670 **
|
0.046
|
1.019 **
|
-60.981
|
-0.190
|
0.523 **
|
-3.967 **
|
-98.022 **
|
E002
|
-0.995**
|
-5.713**
|
-0.035
|
-0.008
|
-0.630 **
|
-0.211 **
|
-1.869 **
|
-50.603
|
1.465 **
|
0.377 *
|
0.444 **
|
-12.490
|
ARG 3
|
0.530**
|
-11.390**
|
-0.272**
|
-0.029 *
|
0.795 **
|
-0.225 **
|
-1.446 **
|
-88.253 **
|
1.745 **
|
-3.101 **
|
-2.688 **
|
-83.452 * *
|
ARG-6-3-1-4
|
1.980**
|
8.585**
|
0.113
|
0.041 **
|
1.745 **
|
0.027
|
1.822 **
|
106.263 **
|
-2.051 **
|
0.515 **
|
3.640 **
|
110.775 **
|
SE ±
|
0.170
|
1.015
|
0.071
|
0.013
|
0.226
|
0.046
|
0.283
|
33.172
|
0.148
|
0.182
|
0.065
|
11.268
|
** Significant at P ≤ 0.01
*Significant at P ≤ 0.05
Table 5: Estimates of general combining ability effects of testers for seed yield and its component traits in sunflower.
Testers
|
Days to 50% flowering
|
Plant height (cm)
|
Head diameter (cm)
|
Stem diameter (cm)
|
Days to maturity
|
100 seed weight (g)
|
Volume weight (g/100ml)
|
Seed yield (Kg/ha)
|
Hull content (%)
|
Seed filling percent
|
Oil content (%)
|
Oil yield (Kg/ha)
|
GKVK-3
|
3.480**
|
-1.608
|
-0.100
|
0.042 *
|
3.695 **
|
0.232 **
|
2.071 **
|
88.047
|
-0.088
|
1.654 **
|
-0.605 **
|
13.298
|
RHA-6D-1
|
0.880**
|
1.233
|
0.135
|
-0.003
|
1.845 **
|
-0.080
|
0.245
|
-89.587
|
-1.053 **
|
1.047 **
|
0.870 **
|
-11.862
|
RHA-95-C-1
|
1.730**
|
13.943**
|
0.545**
|
0.106 **
|
2.095 **
|
0.184 **
|
0.703
|
72.991
|
-0.261
|
1.277 **
|
0.942 **
|
44.960 **
|
LTRR-822
|
1.730**
|
5.662**
|
0.055
|
0.054 **
|
1.145 **
|
0.021
|
-3.152 **
|
13.824
|
-2.018 **
|
-0.755 **
|
0.088
|
8.946
|
M17-R
|
-2.120**
|
-3.093**
|
-0.410**
|
-0.074 **
|
-2.805 **
|
-0.440 **
|
3.166 **
|
-133.831 **
|
-0.646 **
|
-0.732 **
|
0.210 *
|
-42.453 **
|
MR-1
|
-1.270**
|
0.663
|
0.125
|
0.052 **
|
-0.855 **
|
-0.117
|
0.145
|
105.547 *
|
0.367
|
1.182 **
|
0.279 **
|
41.580 *
|
RHA-272-II
|
-1.470**
|
-1.077
|
0.235*
|
-0.002
|
-1.955 **
|
0.198 **
|
-0.505
|
-159.909 **
|
2.121 **
|
-3.848 **
|
-1.152 **
|
-77.819 **
|
X-15-NB-10
|
-0.070
|
0.093
|
-0.070
|
0.028
|
-0.105
|
-0.092
|
-3.161 **
|
-75.009
|
1.113 **
|
1.187 **
|
0.201 *
|
-24.241
|
GKVK-2
|
-1.520**
|
-0.068
|
-0.355**
|
-0.116 **
|
-1.955 **
|
0.023
|
1.745 **
|
-0.842
|
1.451 **
|
-1.760 **
|
0.281 **
|
6.896
|
RHA-93
|
-1.370**
|
-15.748
|
-0.160
|
-0.086 **
|
-1.105 **
|
0.073
|
-1.256 **
|
178.769 **
|
-0.984 **
|
0.748 **
|
1.115 **
|
40.695 *
|
SE±
|
0.240
|
1.435
|
0.101
|
0.019
|
0.319
|
0.064
|
0.401
|
46.912
|
0.210
|
0.257
|
0.092
|
15.936
|
** Significant at ≤ 0.01
* Significant at ≤ 0.05
General combining ability effects
Combining ability of a line/strain to produce superior progenies upon hybridization with other lines/strains is an important criteria to select parents for developing superior new hybrids. To reduce the crop growth period, lesser number of days to flowering and maturity is preferred. The sunflower growers require short duration hybrids, because such hybrids reduce the incidence of insect-pest, disease attack and adverse environmental effects (Memon et al. 2015). For days to 50% flowering and days to maturity only line E002 exhibited significant negative gca effect (table 4) for both these traits while among testers highest significant negative gca effect was recorded by M17-R (table 5) for both the traits followed by GKVK 2 and RHA-272-II. Thus the lines E002 and testers M17-R, GKVK 2 and RHA-272-II were found to be good general combiners for earliness. Therefore, these lines could be used in the synthesis of early maturing hybrids. Meena et al. (2013) and Azad et al. (2016) have also identified good general combiners for early flowering.
As reduced plant height promotes resistant to lodging, there is also a huge interest in the development of semi-dwarf hybrids. The most prominent negative effect of the GCA for plant height was found in the CMS lines in ARG 3 (-11.390) and for the same traits among the testers in RHA-93 (-15.748), hence, the lines and testers with negative gca effects can be used in hybridization programme to synthesize medium stature plants. For head diameter, line ARG-2-1-2 (0.270) exhibited significant positive gca effects while line ARG 3 (-0.272) exihibited significant negative gca effect while among testers, only RHA-95-C-1 (0.545) and RHA 272-II (0.235) exhibited significant positive gca effect. Riaz et al. (2017) have also reported similar results and inferred that these identified lines and testers with positive gca effect could be used in further breeding programme to synthesis hybrids with large head size thus intern contributing to increased yield. For stem diameter lines ARG-6-3-1-4 (0.041) exhibited highest significant positive effect and ARG 3 (-0.029) exhibited significant negative gca effect. Testers RHA-95-C-1 (0.106) followed by MR-1 (0.052) exhibited highest significant positive gca effect as also observed in the studies of Lakshman et al. (2019) indicating the preponderance of additive effect in the inheritance of this character.
The seed weight of a genotype serves as an indicator to the expression of an end product i.e., seed yield as it is an important character contributing to seed yield. Lines ARG-2-1-2 (0.363) exhibited highest significant positive gca effect while testers viz., GKVK 3 (0.232), RHA 272-II (0.198) and RHA-95-C-1 (0.184) registered significant positive gca effect indicating their high utility in the breeding programme. For volume weight lines ARG-6-3-1-4 (1.822) and MUT-2-8-3-2 (1.019) exhibited significant positive gca effect. Three testers expressed significant positive gca effect, highest being manifested by M17-R (3.166) followed by GKVK 3 (2.071) and GKVK-2 (1.745). Hence, these lines and testers showing positive gca effects could be used in hybridization programme to develop hybrids with high seed weight and volume weight. Patil et al. (2012) have also reported good general combiners for these yield attributing traits.
The gca effects for seed yield varied both in magnitude and direction among both lines and testers. Lines ARG-6-3-1-4 (106.263) and ARG-2-1-2 (93.574) expressed significant positive gca effects while, ARG 3 (-88.253) exhibited significant negative gca effect. Among testers gca effects ranged from 178.769 (RHA 93) to -159.909 (RHA 272-II). Only one tester recorded positive gca effect and two recorded negative gca effects. It was interesting to note that the line ARG-6-3-1-4 is good general combiners for most of the yield contributing characters, showing that a positive association exists between seed yield and its attributes such as plant height, stem diameter, head diameter and volume weight. Hence, ARG-6-3-1-4 could also be used in breeding for development of hybrids with higher seed yield. In earlier reports, Salem and Ali (2012), Memon et al. (2015) and Chahal et al. (2019) have also reported good general combiners for seed yield. Patil et al. (2012) in their study observed significant gca effects for hull content. In our results also lines ARG-6-3-1-4 (-2.051) and ARG-2-1-2 (-0.969) exhibited significant negative gca effect which is desirable. Four of the ten testers registered significant negative gca effect, highest being recorded by LTRR 822 (-2.018) followed by RHA 6D-1 (-1.053) and M17-R (-0.646). Parents showing negative gca for this trait can be considered to develop hybrids having low hull content. For seed filling percentage lines ARG-2-1-2 (1.686), MUT-2-8-3-2 (0.523), ARG-6-3-1-4 (0.515) and E002 (0.377) exhibited significant positive gca. whereas, line ARG 3 (-3.101) exhibited significant negative gca effect. All the testers, recorded significant gca effect, with six being positive and four being negative. Highest positive being recorded by GKVK 3 (1.654) followed by RHA-95-C-1 (1.277). Lakshman et al. (2019) have reported similar results for seed filling percentage inferring that the lines and tester having positive significant gca effects appeared to transmit the increasing alleles with additive effects.
As Sunflower is an oilseed crop, oil is the ultimate end product and hence, increase in oil content is of prime most important. All the lines tested expressed significant gca effects of which three of them were positive and two of them were negative. The line ARG-6-3-1-4 (3.640) manifested the highest positive significant gca effect followed by ARG-2-1-2 (2.571) and E002 (0.444). Seven testers registered significant positive gca effect. The testers RHA-93 (1.115) followed by RHA 95-C-1 (0.942) and RHA 6D-1 (0.870) were the best general combiners for oil yield. Similar findings for oil content were reported by Azad et al. (2016) and Attia et al. (2020). Oil yield is a derivative trait of oil content and seed yield. Good general combiners for this trait have been identified in earlier works of Lakshman et al. (2019) and Hilli et al. (2020). In the present study except ARG 3, all lines exhibited significant gca effect, highest significant positive gca effect is being manifested by ARG-6-3-1-4 (110.775) followed by ARG-2-1-2 (83.189). Among the testers, highest significant positive gca being manifested by RHA-95-C-1 (44.960) followed by MR-1 (41.580) and RHA-93 (40.695). On the contrary, highest negative gca effect registered by RHA 272-II (-77.819) followed by M17-R (-42.453). Kaya and Atakisi (2004) reported that superior hybrids were obtained by crossing CMS females and restorer males with high GCA and SCA effects. On the similar lines, ARG-6-3-1-4 and ARG-2-1-2 and testers RHA-95-C-1, MR-1 and RHA-93 with high positive GCA estimates can be desirable parents to be used for developing sunflower hybrids with improved oil yield.
Specific combining ability effects
The relative performance of any cross combination is expressed as specific combining ability and is denoted in terms of sca effects and SCA variance. The SCA variance denotes non additive or dominance portion of variance and generally non fixable on selfing but can be exploited in hybrid combination. Out of 50 crosses, only 5 hybrids recorded the desirable significant negative sca effects and 3 hybrids exhibited significant positive sca effects for days to 50% flowering (Table 6). The crosses which exhibited highest significant negative sca effects for earliness are MUT-2-8-3-2 x M-17-R (-1.805) followed by ARG-6-3-1-4 x GKVK-3 (-1.730) and ARG-2-1-2 x GKVK-2 (-1.580). The parents of best specific combinations, MUT-2-8-3-2 x M-17-R (Table 7) were of low x low general combiners indicating the involvement of non-additive gene action and over dominance in the expression of this trait. With respect to days to maturity, 17 out of 50 crosses manifested significant sca effects, of which the highest negative sca effect was manifested by ARG 3 x GKVK-2 (-2.545), followed by ARG 3 x LTRR-822 (-2.395) and ARG-2-1-2 x RHA 6D-1 (-2.220). Ghaffari et al. (2020) also obtained similar results and concluded that crosses showing negative significant sca effects possess dominant or over dominant type of genes with decreasing effect hence may be exploited for earliness in sunflower.
For plant height, best crosses which exhibited high negative sca effect were ARG-6-3-1-4 x GKVK-3 (-15.125) followed by ARG-6-3-1-4 x RHA 6D-1 (-12.465) and ARG 3 x GKVK-2 (-10.265). Bhoite et al. (2018) also reported good specific combiners for plant height. Head diameter in case of sunflower is an important yield attributing character since there is a positive correlation of head size with number of seeds per head and in turn with seed yield. The hybrid MUT-2-8-3-2 x GKVK-3 (1.160) topped the list of crosses which showed highest significant positive sca effects followed by ARG-6-3-1-4 x GKVK-2 (0.728) and ARG-6-3-1-4 x MR-1 (0.648). Preponderence of non-additive gene action for this trait was also observed by Parameshwarappa et al. (2008) and Machikowa et al. (2011). Ten out of 50 hybrids showed significant sca effect for stem diameter, of which five were in positive and five were in negative direction. The hybrid ARG-6-3-1-4 x GKVK-2 (0.246) expressed significant positive sca effect followed by MUT-2-8-3-2 x GKVK-3 (0.141) and ARG 3 x RHA 6D-1 (0.138). Contrary to this, cross ARG 3 x GKVK-2 (-0.254) exhibited highest significant negative sca effects followed by ARG-6-3-1-4 x RHA-6D-1 (-0.227). However, the magnitude of sca effects among the hybrids was very low for this trait. These results are in confirmation with those observed in the studies of Shankar et al. (2007).
Eight cross combinations showed significant positive sca effects for 100 seed weight. Of these, ARG-2-1-2 x RHA 6D-1 (0.535), ARG-6-3-1-4 x GKVK-3 (0.525) and MUT-2-8-3-2 x X-15-NB-10 (0.456) were the best specific combiners. Of the top three ranked hybrid for the trait two crosses involved at least one parent with low gca effect i.e., these crosses were of high x low or low x high type of specific combinations suggesting the involvement of non-additive gene action in the inheritance of this trait. Patil et al. (2017) reported good specific combiners for 100 seed weight and also reported existence of non additive gene action in the inheritance of this trait. The cross combination E002 x X-15-NB-10 (2.816) was the best specific combiner for volume weight followed by MUT-2-8-3-2 x MR-1 (2.157) and MUT-2-8-3-2 x LTRR-822 (2.049). All the three best crosses involved at least one parent with low gca effects, clearly suggesting the involvement of non-additive gene action in the inheritance of the trait. Similar results were obtained by Chandra et al. (2011) and Lakshman et al. (2019).
With respect to seed yield, sca ranged from − 258.81 to 404.04 with the best specific combiner being MUT-2-8-3-2 x GKVK-3 (404.036), followed by ARG-2-1-2 x LTRR-822 (295.926) and E002 x M-17-R (254.425). A large reservoir of variability was evident as could be inferred from the range as well as magnitude and direction of sca effects for this character. In the first two top crosses viz., MUT-2-8-3-2 x GKVK-3 and ARG-2-1-2 x LTRR-822, at least one parent with high and other parent with low gca effects were present. This could be attributed to the involvement of non-additive gene action. However, it was interesting to note that in the third cross viz., E002 x M-17-R both the parents with low gca effects were involved suggesting preponderence of over dominance and epitasis. Dhillon and Tyagi (2016) also reported good specific combiners for seed yield in sunflower.
Thirty five out of 50 crosses showed significant sca effects for hull content, of which ARG-2-1-2 x RHA-93 (-4.646) topped the list of hybrids expressing significant negative sca effect followed by ARG-6-3-1-4 x M-17-R (-3.588) and ARG-2-1-2 x X-15-NB-10 (-3.501). In contrary, cross MUT-2-8-3-2 x X-15-NB-10 (3.731) and ARG-6-3-1-4 x GKVK 3 (3.648) exhibited highest significant negative sca effects. Bhoite et al. (2018) reported desired negative specific combiners for this trait. With respect to seed filling percentage, fourteen and thirteen crosses exhibited significant positive and negative sca effects, respectively. The cross, MUT-2-8-3-2 x RHA 272-II (5.329), ARG-2-1-2 x LTRR-822 (3.556) and ARG-2-1-2 x X-15-NB-10 (2.718) were the best specific combiners for seed filling percentage. Meena et al. (2013) and Sharma and Shadakshari (2021) also reported good specific combiners for seed filling percentage.
Highly significant sca effects for oil content were observed in thirty nine crosses, of which nineteen and twenty crosses expressed positive and negative significant sca effects, respectively. The hybrids E002 x X-15-NB-10 (2.520), MUT-2-8-3-2 x GKVK-3 (2.070) and ARG-2-1-2 x RHA-93 (1.961) topped the list of crosses expressing significant positive sca effects. The best specific combination E002 x X-15-NB-10 was having parents with low combining ability which indicated the involvement of non-additive gene action and also existence of over dominance and epitasis in the inheritance of this trait. With reference to oil yield, hybrids viz., MUT-2-8-3-2 x GKVK-3 (171.895) followed by ARG-2-1-2 x LTRR-822 (98.581) and MUT-2-8-3-2 x RHA-93 (72.726) were the best specific combiners among 50 hybrids. Top ranking hybrids had atleast one parent with low combining ability type of parental combinations suggesting the action of non additive gene in the inheritance of this trait. Non additive gene action for oil content and oil yield was also reported by Azad et al. (2016) and Hilli et al. (2020). None of the hybrids were good specific combiners for all the characters studied. However, the cross combination MUT-2-8-3-2 x GKVK 3 was found to be good specific combiner for stem diameter, 100 seed weight, seed yield, seed filling percentage, oil content and oil yield hence it can be tested in large scale yield trials over locations and seasons to confirm its potentiality for commercial cultivation. As these hybrids are based on diverse cytosterile sources, even their on par performance with PET 1 cytoplasm based hybrids will be sufficient enough so that the cytoplasmic base of sunflower hybrids can be expanded.
Variance due to general and specific combining ability effects
The ratio of GCA to SCA is used to indicate the predominance of non-additive gene action in the inheritance of the traits. The results revealed that, among the twelve characters studied, characters viz., days to 50% flowering, plant height, days to maturity and volume weight there was preponderance of additive gene action as indicated by greater than unity GCA to SCA ratio (Table 8), while remaining characters viz., head diameter, stem diameter, 100 seed weight, seed yield, hull content, seed filling percent, oil content and oil yield manifested a higher magnitude of SCA variance as compared to GCA variance. Similar to the present findings, non-additive gene actions were documented for head diameter (cm), stem diameter (cm), 100 seed weight (g), seed yield (kg/ha), hull content (%), seed filling percent, oil content (%), and oil yield (kg/ha) by Bhoite et al. (2018) and Hilli et al. (2020).
Proportional contribution of lines, testers and line x tester interaction for the performance of hybrids
The data on the proportional contribution of lines, testers and line x tester interaction for twelve quantative traits revealed that the line x tester interaction contributed more for the performance of hybrids for most of the characters such head diameter, stem diameter, 100 seed weight, seed yield, hull content, seed filling percent, oil content and oil yield (Table 9). However, for days to 50% flowering, days to maturity and volume weight contribution of the testers was more when compared to lines and line x tester interaction. Shankar et al. (2007) observed similar results and emphasized that due care needs to be excised while selecting the inbreds/lines to be used as parents for hybridization and to safely use these sources to broaden the genetic base of CMS source so that this valuable oilseed crop can be safeguarded from any eventuality of biotic and abiotic threats in future.
Table 6: Estimates of specific combing ability effects of crosses for seed yield and its attributing traits sunflower.
Hybrids
|
Days to 50% flowering
|
Plant height (cm)
|
Head diameter (cm)
|
Stem diameter (cm)
|
Days to maturity
|
100 seed weight (g)
|
Volume weight (g/100ml)
|
Seed yield (Kg/ha)
|
Hull content (%)
|
Seed filling percent
|
Oil content (%)
|
Oil yield (Kg/ha)
|
ARG-2-1-2 x GKVK-3
|
-0.330
|
0.048
|
-0.335
|
-0.019
|
-0.570
|
-0.119
|
-0.020
|
-244.963 *
|
0.491
|
-2.268 **
|
-1.104 **
|
-104.931**
|
ARG-2-1-2 x RHA 6D-1
|
-0.230
|
-0.793
|
0.530 *
|
0.109 *
|
-2.220 **
|
0.535 **
|
0.589
|
6.281
|
0.928
|
-0.087
|
0.681 **
|
11.969
|
ARG-2-1-2 x 95-C-1
|
-0.330
|
-0.002
|
-0.030
|
-0.040
|
-1.970 **
|
0.413 **
|
-0.377
|
62.870
|
-0.784
|
1.233 *
|
-1.073 **
|
6.120
|
ARG-2-1-2 x LTRR-822
|
-0.080
|
-3.123
|
0.060
|
0.011
|
0.980
|
0.217
|
1.416
|
295.926 **
|
-2.097 **
|
3.556 **
|
-0.457 *
|
98.581 **
|
ARG-2-1-2 x M-17-R
|
1.770 **
|
-10.118 **
|
-0.475 *
|
0.010
|
0.930
|
-0.220
|
-0.305
|
-180.030
|
1.424 **
|
1.058
|
0.771 **
|
-57.825
|
ARG-2-1-2 x MR-1
|
0.420
|
3.178
|
-0.060
|
0.051
|
0.230
|
-0.350 *
|
0.741
|
-145.797
|
0.924
|
-2.747 **
|
1.047 **
|
-30.002
|
ARG-2-1-2 x RHA 272-II
|
0.620
|
-0.283
|
0.080
|
-0.015
|
2.580 **
|
0.074
|
-0.504
|
136.325
|
1.335 **
|
0.863
|
-1.429 **
|
16.296
|
ARG-2-1-2 x X-15-NB-10
|
0.470
|
7.347 *
|
-0.165
|
-0.012
|
1.480 *
|
-0.633 **
|
-1.746
|
-98.575
|
1.393 *
|
-2.081 **
|
0.155
|
-34.101
|
ARG-2-1-2 x GKVK-2
|
-1.580 **
|
5.183
|
0.220
|
-0.073
|
-0.670
|
-0.038
|
0.771
|
99.481
|
1.030 *
|
-1.739 **
|
-0.550 **
|
23.351
|
ARG-2-1-2 x RHA-93
|
-0.730
|
-1.438
|
0.175
|
-0.018
|
-0.770
|
0.122
|
-0.563
|
68.481
|
-4.646 **
|
2.213 **
|
1.961 **
|
70.540
|
MUT-2-8-3-2 x GKVK-3
|
-0.405
|
1.830
|
1.160**
|
0.141 **
|
-0.820
|
0.395 **
|
0.626
|
404.036 **
|
-2.191 **
|
1.932 **
|
2.070 **
|
171.895 **
|
MUT-2-8-3-2 x RHA 6D-1
|
0.945
|
3.665
|
-0.025
|
-0.056
|
0.530
|
-0.453 **
|
0.427
|
-205.830
|
1.754 **
|
-1.804 **
|
-1.771 **
|
-94.955 **
|
MUT-2-8-3-2 x 95-C-1
|
-0.905
|
-1.970
|
-0.585 *
|
0.015
|
-1.220
|
0.268
|
-0.376
|
-0.352
|
0.0001
|
-2.994 **
|
0.285
|
-0.152
|
MUT-2-8-3-2 x LTRR-822
|
-0.905
|
-0.765
|
-0.045
|
-0.031
|
-2.020 **
|
-0.041
|
2.049 *
|
-130.075
|
-1.973 **
|
0.704
|
-1.271 **
|
-67.103
|
MUT-2-8-3-2 x M-17-R
|
-1.805 **
|
-7.210 *
|
-0.405
|
-0.070
|
-0.570
|
-0.565 **
|
-1.094
|
-258.808 *
|
-2.120 **
|
-4.747 **
|
-0.128
|
-77.874 *
|
MUT-2-8-3-2 x MR-1
|
-0.155
|
-8.965 **
|
-0.390
|
-0.032
|
0.230
|
-0.076
|
2.157 *
|
65.703
|
-0.023
|
0.746
|
-0.562 **
|
3.896
|
MUT-2-8-3-2 x RHA 272-II
|
0.545
|
5.175
|
-0.200
|
0.017
|
0.580
|
0.241
|
0.637
|
65.881
|
3.398 **
|
5.329 **
|
0.312
|
34.445
|
MUT-2-8-3-2 x X-15-NB-10
|
-0.355
|
-4.945
|
0.380
|
-0.082
|
-0.520
|
0.456 **
|
-1.847 *
|
99.037
|
3.731 **
|
-1.058
|
-0.732 **
|
20.172
|
MUT-2-8-3-2 x GKVK-2
|
3.095 **
|
7.265 *
|
-0.135
|
0.027
|
2.830 **
|
-0.463 **
|
-1.723
|
-225.130 *
|
-3.062 **
|
0.714
|
0.579 **
|
-63.050
|
MUT-2-8-3-2 x RHA-93
|
-0.055
|
5.920
|
0.245
|
0.072
|
0.980
|
0.236
|
-0.857
|
185.537
|
0.485
|
1.176 *
|
1.217 **
|
72.726 *
|
E002 x GKVK-3
|
0.745
|
10.748 **
|
0.070
|
0.031
|
0.230
|
-0.212
|
-0.485
|
-135.508
|
-1.006 *
|
-1.744 **
|
0.631 **
|
-28.960
|
E002 x RHA 6D-1
|
-0.905
|
5.708
|
-0.240
|
0.037
|
-1.670 *
|
-0.065
|
-1.437
|
3.403
|
-0.401
|
1.428 *
|
0.326
|
4.908
|
E002 x 95-C-1
|
-0.255
|
1.447
|
0.200
|
0.048
|
-0.170
|
-0.020
|
0.328
|
14.270
|
1.410 **
|
0.575
|
-2.151 **
|
-37.474
|
E002 x LTRR-822
|
0.495
|
-0.372
|
0.065
|
0.019
|
2.280 **
|
-0.089
|
-2.098 *
|
-72.397
|
0.062
|
-2.250 **
|
1.218 **
|
-4.715
|
E002 x M-17-R
|
-0.405
|
1.658
|
0.305
|
-0.125 **
|
-1.520 *
|
0.300 *
|
1.825 *
|
254.425 *
|
1.818 **
|
1.370 *
|
-1.579 **
|
57.106
|
E002 x MR-1
|
0.495
|
-4.298
|
-0.030
|
-0.039
|
0.530
|
0.312 *
|
-1.912 *
|
-9.952
|
0.327
|
-0.035
|
-0.465 *
|
-11.184
|
E002 x RHA 272-II
|
-1.055
|
-5.383
|
-0.190
|
-0.135 **
|
-0.870
|
-0.019
|
0.278
|
40.225
|
-1.262 **
|
-4.392 **
|
1.276 **
|
38.730
|
E002 x X-15-NB-10
|
-0.205
|
-1.753
|
0.015
|
0.076
|
-0.220
|
-0.101
|
2.816 **
|
-26.619
|
-2.401 **
|
2.718 **
|
2.520 **
|
38.415
|
E002 x GKVK-2
|
0.745
|
-5.293
|
-0.075
|
0.055
|
1.130
|
0.264
|
-0.072
|
76.992
|
0.173
|
2.438 **
|
-0.072
|
25.695
|
E002 x RHA-93
|
0.345
|
-2.463
|
-0.120
|
0.035
|
0.280
|
-0.371 *
|
0.759
|
-144.841
|
1.280 **
|
-0.110
|
-1.704 **
|
-82.519 *
|
ARG 3 x GKVK-3
|
1.720 **
|
2.500
|
0.358
|
0.035
|
2.555 **
|
-0.589 **
|
-1.159
|
104.920
|
-0.943 *
|
1.901 **
|
0.080
|
36.993
|
ARG 3 x RHA 6D-1
|
0.320
|
3.885
|
0.348
|
0.138 **
|
4.405 ***
|
0.098
|
-0.583
|
126.998
|
1.142 *
|
1.403 *
|
-0.433 *
|
32.683
|
ARG 3 x 95-C-1
|
0.470
|
-6.375 *
|
0.262
|
-0.021
|
1.155
|
-0.231
|
0.289
|
-74.469
|
1.998 **
|
1.120
|
1.176 **
|
-5.127
|
ARG 3 x LTRR-822
|
0.470
|
-0.820
|
-0.147
|
-0.050
|
-2.395 **
|
-0.103
|
-1.127
|
-28.635
|
2.177 **
|
0.400
|
-0.600 **
|
-22.813
|
ARG 3 x M-17-R
|
-0.180
|
4.985
|
0.442
|
0.136 *
|
-0.445
|
0.228
|
0.246
|
104.909
|
2.466 **
|
1.710 **
|
1.052 **
|
56.169
|
ARG 3 x MR-1
|
-1.280 *
|
-0.420
|
-0.167
|
-0.038
|
-1.895 **
|
-0.095
|
-0.604
|
-9.802
|
-1.647 **
|
-0.480
|
-0.056
|
-6.531
|
ARG 3 x RHA 272-II
|
-0.830
|
3.345
|
-0.027
|
0.061
|
-1.545 *
|
-0.095
|
0.041
|
-87.402
|
-2.341 **
|
-2.137 **
|
1.047 **
|
-4.180
|
ARG 3 x X-15-NB-10
|
0.020
|
1.300
|
-0.223
|
0.002
|
0.355
|
0.220
|
1.932 *
|
-13.969
|
-3.501 **
|
-0.019
|
-0.361
|
-7.055
|
ARG 3 x GKVK-2
|
-1.530 **
|
-10.265 **
|
-0.738 **
|
-0.254 **
|
-2.545 **
|
0.210
|
0.391
|
-4.802
|
0.394
|
-1.052
|
0.622 **
|
8.440
|
ARG 3 x RHA-93
|
0.820
|
1.865
|
-0.107
|
-0.009
|
0.355
|
0.355 *
|
0.572
|
-117.747
|
0.256
|
-2.848 **
|
-2.528 **
|
-88.579 *
|
ARG-6-3-1-4 x GKVK-3
|
-1.730**
|
-15.125 **
|
-1.253 **
|
-0.187 *
|
-1.395
|
0.525 **
|
1.038
|
-128.486
|
3.648 **
|
0.178
|
-1.678 **
|
-74.997 *
|
ARG-6-3-1-4 x RHA 6D-1
|
-0.130
|
-12.465 **
|
-0.613 **
|
-0.227 **
|
-1.045
|
-0.116
|
1.004
|
69.148
|
-3.424 **
|
-0.941
|
1.197 **
|
45.395
|
ARG-6-3-1-4 x 95-C-1
|
1.020
|
6.900 *
|
0.153
|
0.001
|
2.205 **
|
-0.430**
|
0.136
|
-2.319
|
-2.624 **
|
0.064
|
1.763 **
|
36.633
|
ARG-6-3-1-4 x LTRR-822
|
0.020
|
5.080
|
0.068
|
0.051
|
1.155
|
0.016
|
-0.240
|
-64.819
|
1.831 **
|
-2.411 **
|
1.109 **
|
-3.950
|
ARG-6-3-1-4 x M-17-R
|
0.620
|
10.685 **
|
0.132
|
0.049
|
1.605 *
|
0.257
|
-0.672
|
79.504
|
-3.588 **
|
0.609
|
-0.116
|
22.424
|
ARG-6-3-1-4 x MR-1
|
0.520
|
10.505 **
|
0.648 **
|
0.058
|
0.905
|
0.209
|
-0.382
|
99.847
|
0.419
|
2.514 **
|
0.036
|
43.821
|
ARG-6-3-1-4 x RHA 272-II
|
0.720
|
-2.855
|
0.338
|
0.072
|
-0.745
|
-0.202
|
-0.452
|
-155.030
|
-1.130 *
|
0.337
|
-1.206 **
|
-85.290 *
|
ARG-6-3-1-4 x X-15-NB-10
|
0.070
|
-1.950
|
-0.008
|
0.017
|
-1.095
|
0.058
|
-1.156
|
40.126
|
0.778
|
0.440
|
-1.582 **
|
-17.430
|
ARG-6-3-1-4 x GKVK-2
|
-0.730
|
3.110
|
0.728 **
|
0.246 **
|
-0.745
|
0.026
|
0.633
|
53.459
|
1.465 **
|
-0.361
|
-0.579 **
|
5.565
|
ARG-6-3-1-4 x RHA-93
|
-0.380
|
-3.885
|
-0.193
|
-0.079
|
-0.845
|
-0.342 *
|
0.089
|
8.570
|
2.624 **
|
-0.431
|
1.054 **
|
27.831
|
SE±
|
0.536
|
3.210
|
0.226
|
0.042
|
0.714
|
0.144
|
0.896
|
104.899
|
0.470
|
0.575
|
0.205
|
35.633
|
** significant at P ≤ 0.01 * significant at P ≤ 0.05
Table 7: Top ranking hybrids with high sca effects in desirable direction for seed yield and its component traits in sunflower.
Rank
|
Days to 50% flowering
|
Rank
|
Plant height (cm)
|
1
|
MUT-2-8-3-2 x M-17-R
|
1
|
ARG-6-3-1-4 x GKVK-3
|
2
|
ARG-6-3-1-4 x GKVK-3
|
2
|
ARG-6-3-1-4 x RHA 6D-1
|
3
|
ARG-2-1-2 x GKVK-2
|
3
|
ARG 3 x GKVK-2
|
4
|
ARG 3 x GKVK-2
|
4
|
ARG-2-1-2 x M-17-R
|
5
|
ARG 3 x MR-1
|
5
|
MUT-2-8-3-2 x MR-1
|
Rank
|
Head diameter (cm)
|
Rank
|
Stem diameter (cm)
|
1
|
MUT-2-8-3-2 x GKVK-3
|
1
|
ARG-6-3-1-4 x GKVK-2
|
2
|
ARG-6-3-1-4 x GKVK-2
|
2
|
MUT-2-8-3-2 x GKVK-3
|
3
|
ARG-6-3-1-4 x MR-1
|
3
|
ARG 3 x RHA 6D-1
|
4
|
ARG-2-1-2 x RHA 6D-1
|
4
|
ARG 3 x M-17-R
|
5
|
ARG 3 x M-17-R
|
5
|
ARG-2-1-2 x RHA 6D-1
|
Rank
|
Days to maturity
|
Rank
|
100 seed weight (g)
|
1
|
ARG 3 x GKVK-2
|
1
|
ARG-2-1-2 x RHA 6D-1
|
2
|
ARG 3 x LTRR-822
|
2
|
ARG-6-3-1-4 x GKVK-3
|
3
|
ARG-2-1-2 x RHA 6D-1
|
3
|
MUT-2-8-3-2 x X-15-NB-10
|
4
|
MUT-2-8-3-2 x LTRR-822
|
4
|
ARG-2-1-2 x 95-C-1
|
5
|
ARG-2-1-2 x 95-C-1
|
5
|
MUT-2-8-3-2 x GKVK-3
|
Rank
|
Volume weight (g/100ml)
|
Rank
|
Seed yield(kg/ha)
|
1
|
E002 x X-15-NB-10
|
1
|
MUT-2-8-3-2 x GKVK-3
|
2
|
MUT-2-8-3-2 x MR-1
|
2
|
ARG-2-1-2 x LTRR-822
|
3
|
MUT-2-8-3-2 x LTRR-822
|
3
|
E002 x M-17-R
|
4
|
ARG 3 x X-15-NB-10
|
4
|
MUT-2-8-3-2 x RHA-93
|
5
|
E002 x M-17-R
|
5
|
ARG-2-1-2 x RHA 272-II
|
Rank
|
Hull content (%)
|
Rank
|
Seed filling per-cent
|
1
|
ARG-2-1-2 x RHA-93
|
1
|
MUT-2-8-3-2 x RHA 272-II
|
2
|
ARG-6-3-1-4 x M-17-R
|
2
|
ARG-2-1-2 x LTRR-822
|
3
|
ARG-2-1-2 x X-15-NB-10
|
3
|
ARG-2-1-2 x X-15-NB-10
|
4
|
ARG-6-3-1-4 x RHA 6D-1
|
4
|
ARG-6-3-1-4 x MR-1
|
5
|
MUT-2-8-3-2 x GKVK-2
|
5
|
E002 x GKVK-2
|
Rank
|
Oil content (%)
|
Rank
|
Oil yield (kg/ha)
|
1
|
E002 x X-15-NB-10
|
1
|
MUT-2-8-3-2 x GKVK-3
|
2
|
MUT-2-8-3-2 x GKVK-3
|
2
|
ARG-2-1-2 x LTRR-822
|
3
|
ARG-2-1-2 x RHA-93
|
3
|
MUT-2-8-3-2 x RHA-93
|
4
|
ARG-6-3-1-4 x 95-C-1
|
4
|
ARG-2-1-2 x RHA-93
|
5
|
E002 x RHA 272-II
|
5
|
E002 x M-17-R
|
Table 8: Variance due to general and specific combining ability effects for seed yield and its attributing traits in sunflower.
Characters
|
Variance due to GCA
|
Variance due to SCA
|
GCA/ SCA
|
Days to 50% flowering
|
2.456
|
0.877
|
2.800
|
Plant height (cm)
|
62.160
|
35.930
|
1.730
|
Head diameter (cm)
|
0.048
|
0.158
|
0.304
|
Stem diameter (cm)
|
0.002
|
0.009
|
0.222
|
Days to maturity
|
3.285
|
2.594
|
1.266
|
100 seed weight (g)
|
0.049
|
0.100
|
0.490
|
volume weight (g/100ml)
|
3.057
|
0.875
|
3.494
|
Seed yield (kg/ha)
|
8422.689
|
13879.046
|
0.607
|
Hull content (%)
|
2.241
|
5.314
|
0.422
|
Seed filling (%)
|
3.177
|
5.083
|
0.625
|
Oil content (%)
|
1.850
|
7.344
|
0.252
|
Oil yield (kg/ha)
|
2681.516
|
6346.924
|
0.422
|
Table 9: Proportional contribution of lines, testers and L x T interaction to the total variance among the hybrids.
Sl. No.
|
Characters
|
Lines (L)
|
Testers (T)
|
L x T interaction
|
1
|
Days to 50% flowering
|
28.730
|
56.228
|
15.042
|
2
|
Plant height (cm)
|
39.842
|
35.814
|
24.344
|
3
|
Head diameter (cm)
|
13.012
|
28.252
|
58.736
|
4
|
Stem diameter (cm)
|
3.950
|
35.319
|
60.732
|
5
|
Days to maturity
|
26.322
|
47.364
|
26.314
|
6
|
100 seed weight (g)
|
27.379
|
21.159
|
51.462
|
7
|
volume weight (g/100ml)
|
28.199
|
55.045
|
16.756
|
8
|
Seed yield (kg/ha)
|
18.907
|
31.451
|
49.643
|
9
|
Hull content (%)
|
27.589
|
19.434
|
52.977
|
10
|
Seed filling (%)
|
28.229
|
29.903
|
41.868
|
11
|
Oil content (%)
|
4.622
|
13.035
|
82.344
|
12
|
Oil yield (kg/ha)
|
12.477
|
24.827
|
62.696
|