Genetic Variability and Heritability
treatment. For the control site, the materials were grown in the rice field with shallow flooding.
The materials grown were P
1
, P
2
, F1, F
2
, BCP
1
, and BCP
2
. The number population used in each site were 40 plants of the parents and 50 plants of the F
1
; 60 of BCP
1
and BCP
2
; and 320 of F
2
population. The materials were grown with the arrangement of 25 cm x 25 cm of spacing.
In the stagnant flooding site, the plants were situated at the 2-3 cm of water depth from 0 to 7 days after transplanting DAT. The water then were increased
twice a week at a rate of 1.43 cm day
-1
during early vegetative stage from 7 to 21 DAT; and three times a week at a rate of 2.14 cm day
-1
during the late vegetative stage from 21 to 35 DAT. Then, a water depth of 50
– 80 cm will be maintained from 35 DAT until maturity Kato et. al 2014, modified. The gradual increase in
water depth is typical of the long-term stagnant floods in some areas of tropical Asia Singh et al. 2011.
Response of population to stagnant flooding stresses was evaluated based on agronomic traits. The observed traits were plant height, number of productive
tiller, weight of 100 grain, flowering date, length of panicle, and grain yield per plant. Grain yield per plant of P1, P2, and F1 was estimated by calculating grain
yield per plot were corrected with number of productive tillers per hills on all of members of each P1, P2, and F1.
4.2.3 Statistical analysis 4.2.3.1 Generation mean analysis
There are six genetic components on a completely di-genic model; they are mean m, effect of additive gene d, and effect of dominant gene h, interaction
of additive x additive number i, interaction of additive x dominant number j, and interaction of dominant x dominant number l Singh and Chaudary 1979. Genetic
model testing is combination of six genetic components so that there are eight models to be tested. Eight models include of 1 two genetic components model
m[d]; 2 three genetic components model m[d] [h] as additive dominant model; 3 four genetic component model m[d] [h] [i], m[d] [h] [j], m[d] [h] [l], and
4 five genetic components model m[d] [h] [i] [j] , m[d] [h] [i] [l] , and m[d] [h] [j] [l] .
First step for genetic model testing is scaling test. Scaling test estimate gene action and model genetic by testing several generation separately. Scaling test used
three-parameter A=2B
1
– P
1
– F
1
, B = 2B
2
– P
2
– F
1
, C = 4F
2
– 2 F
1
– P
1
– P
2
to explain conformity of additive dominant. If scaling test is not significantly different
t t
table 0.05;~
= 1.96, it identified that the gene action is additive dominant. If scaling test showed any significant different, the gene action is inter-allelic or
epistasis. Joint scaling test is used to obtain appropriate interaction model. Joint scaling test estimate gene action and model genetic by testing several generation
simultaneously. It is allow to estimate genetic model fit test. Six-parameter used in joint scaling test that are m = ½ P
1
+ ½ P
2
+ 4F
2
– 2B
1
– 2B
2
; d = 6B
1
+ 6B
2
– 8F
2
- F
1
– 1 ½ P
1
– 1 ½ P
2
; aa = 2B
1
+ 2B
2
– 4F
2
; ad = 2B
1
– P
1
– 2B
2
+ P
2
; dd = P
1
+ P
2
+ 2F
1
+ 4F
2
– 4B
1
– 4B
2
. Appropriate genetic model is determined based on X
2
X
2tabel α = 0.05; db = n-3
, with n is number of generation. Mather and Jink 1982. Heritability estimation can be obtained by the formula of Roy 2000 with
calculation of additive variance D, dominant variance H, and environment
variance E. The variance component can be used to estimate variance of population through Singh and Chaudhary formula 1979 as follows: E
=
� � +� � +�
; = 4�
− � � − � � ; = 4� � + 4� � −
4� − ; ℎ
��
=
� ��
=
�+
+ �+
; ℎ
��
=
�� ��
=
�
+ �+
B
1
, B
2
= BCP1, BCP2; VG = variance of genetic; VP = variance of phenotype; VA = variance of additive; h
2 bs
= broad sense heritability; h
2 ns
= narrow sense heritability. Heritability is high if h
2
0.50, medium if 0.2 ≥ h
2
≥ 0.50, and low if h
2
0.2 Halloran et al. 1979. All statistical analyses were performed with SAS version 9 software. The
SAS listing program for scaling test and joint scaling test analysis were developed by Gusti N Adhi-Wibawa Unpublished, listed in Appendix 3.