International Journal of Agriculture and Crop Sciences.
Available online at www.ijagcs.com
IJACS/2013/5-13/1427-1431
ISSN 2227-670X ©2013 IJACS Journal
Determination of Gene Action and Heritability for
Some Biometrical Traits in Lentil (Lens culinaris
Medik) Using F2:3 Families
Mitra Vanda*1, Mahmoud Khodambashi1, Saadollah Houshmand1, Behrouz Shiran1,
Reza Amiri-Fahlian2
1. Department of Plant Breeding, Faculty of Agriculture, Shahrekord University, Shahrekord, Islamic Republic of
Iran.
2. Department of Agronomy and Plant Breeding, Faculty of Agriculture, Yasouj University, Yasouj - Islamic
Republic of Iran.
* Corresponding author email: [email protected]
1
ABSTRACT: Information on genetic parameters and heritability is useful to plan selection criteria for
yield improvement in crop plants. In order to estimate genetic parameters and heritability in lentil,
120 F2:3 families of a cross between the lines 'L-3685' and 'Lc74-1-5-1' were evaluated under field
conditions, at Shahrekord University Research Farm, in 2012. Days to flowering, days to maturity,
plant height, leaf area, pods per plant, seeds per plant, 100-seed weight and seed yield per plant
were recorded. The simple additive-dominance model using two-parameter model based on m and
[a] fitted for all traits, indicating that both of the parameters, m and [a] (additive gene effect), were
highly significant for all studied characters. Variance components analysis showed that additive
component of variance (VA) was highly significant for all evaluated traits. Relatively high heritability
was observed for days to flowering (0.54) and days to maturity (0.59). Low heritability of seeds per
pod, pods per plant and seed yield per plant showed that environmental factors strongly influence
these characters. Since heritability of such characters will be improved as generations advance, it
could be concluded that selection for improving yield and its components should be practiced in
more advanced generations.
Key words: Gene Effect, Heritability, Lentil, Seed Yield.
INTRODUCTION
Lentil (Lens culinaris Medik) (2n = 14) is a highly nutritious food legume cultivated for its grain. High
protein content (22-34.6%) along with significant concentration of limiting amino acid; lysine, and its fast
cooking characteristics, make it as an important part of diet in different parts of the world, especially west, south
and southeast Asia. This crop is valued for its role in the cropping system, as it needs few inputs and has
beneficial effects on the soil fertility, because of symbiotic nitrogen fixation (Kumar et al., 2011). Seed yield is
the primary objective in most lentil breeding programs. Grain yield is a complex character and is the product of
many yield components. Selection for yield components has been suggested as a solution for further advance
in increasing yield. So, having the existing genetic variations and gene action, and their heritability, assumes to
be important (Falconer, 1960). Understanding inheritance of the yield components is necessary for the
intelligent choice of breeding procedures for developing high-yielding varieties (Azizi et al., 2006).
There are different analysis methods to estimate genetic basis of quantitative variability of the selected
plant characters. One of the best methods for the estimation of genetic parameters is the generation mean
analysis, in which epistatic effects could also be estimated (Mather and Jinks, 1982; Kearsey and Pooni, 1996).
Heritability, in the narrow and broad-sense, is important for plant breeders, since the effectiveness of selection
depends on additive portion of genetic variance in relation to total variance.
Aher et al. (2006) using generation mean analysis in three crosses of pigeon pea showed that additive,
dominance, and both the additive and dominance component of gene effects were significant for pods per
plant.
The importance of additive component compared to dominant-additive portion of the genetic model was
reported by Checa et al. (2006) to determine the inheritance of climbing capacity based on plant height (PH)
Intl J Agri Crop Sci. Vol., 5 (13), 1427-1431, 2013
and internode length (IL) in common bean (Phaseolus Vulgaris). They used 6 evaluated generations at 2
growth stages (40 and 70 days after planting) and broad-sense heritability varied from 62.3% to 85.6% for PH
and from 66.5% to 83.7% for IL.
Khodambashi et al. (2012) reported low narrow-sense heritability for seed yield per plant, pod length,
seeds per pod and 100-seed weight, and a moderate one for other traits in Lentil. Average dominance ratio was
more than unity for seed yield per plant, number of primary and secondary branches, pod length, and 100-seed
weight, showing the high importance of dominance gene effect, controlling these traits.
Low heritability for days to flowering, seed yield, biological yield, harvest index, days to maturity,
hundred seed weight, pods per plant and plant height was observed by Bicer and Sarkar (2010) in lentil. Ashraf
et al. (2008) observed high heritability coupled with moderate to high genetic advance for plant height (90.8%,
16.29), pods per plant (86.20%, 25.53), hundred seed weight (83.50%, 35.67), and seed yield per plant
(91.80%, 35.84), in F generation. Also, they reported such a situation for days to flowering (96.9%, 25.08),
6
hundred seed weight (89.0%, 25.56) and seed yield per plant (94.0%, 37.01) in M generation. The traits
6
mentioned above were found to be under the control of additive genes.
Hooda et al. (2000) studied Parental, F1, F2 and F3 generations of 2 crosses of pigeon pea cultivars (Ms
Prabhat (DT) × Manak) and (DT × H82-1) for seed yield/plant and other 6 yield-related characters over 2 years.
The additive and dominance gene effects were highly significant in both the crosses and years, using Hayman
5-parameter model, while the joint scaling test (JST) showed additive gene effects in DT × Manak for days to
50% flowering, days to maturity, plant height and 100-seed weight, and in DT × H82-1 for 100-seed weight in
both years. Duplicate epistasis was indicated for all the characters in both two crosses and years by Hayman
model, but only for days to maturity in DT × Manak and for pods per plant in DT × H82-1 by JST model. Younis
et al. (2008) found high heritability for traits like flowering days (99.70%), seed yield (97.10%), biological yield
(96.50%), harvest index (96.20%), maturing days (95.90%), hundred seed weight (93.80%), pods per plant
(88.40%) and plant height (80.30%). In general, all the traits except number of primary branches per plant had
high heritable variation. Pods per plant, hundred seed weight and seed yield per plant could be used as
selection criteria suggested by Sarwar et al. (2004).
Aims of this study were estimation and evaluation of means and variance components, to take
information about the gene effects for corresponding traits, and estimate heritability of agro-morphological traits
using F2:3 families analysis with more details and emphasis on components of environmental variation as part of
phenotypic variance, with the assumption that having more detailed information of the environmental variance
is better to aiding the planning of effective experimental design to improve the plants.
MATERIALS AND METHODS
Plant material and data collection
Quantitative genetics of seed yield and other agronomic characters of lentil were studied using a
population of 120 F2:3 families obtained from a cross between L-3685 (a small seeded line as female parent)
and Lc74-1-5-1 (a bold seeded line as male parent), and three check cultivars at Shahrekord University
Research Farm, Shahrekord, Iran. Plants were cultivated in 2 meter long rows with 30 and 20 cm space
between and within the rows, respectively. Days to flowering, days to maturity, plant height, leaf area, pods per
plant, seeds per plant, 100-seed weight and seed yield per plant were evaluated.
Statistical analysis
Data collected from check cultivars were subjected to analysis of variance (ANOVA) using a
randomized complete block design. F3 generation analysis for all corresponding traits was conducted using one
way ANOVA. Weighted least squares (WLS) were used in multiple variable regression method to estimate the
parameters of means and variance generations, and their standard errors (SE). As suggestion of Kearsey and
Pooni, (1996) the models were started with the least parameters (m in mean analysis and VE in the variance
analysis) and the other parameters were added when the 2 was significant.
For computing the h2 (heritability), only statistically significant components of variance were used
(Kearsey and Pooni, 1996). The full model matrix was used for means analysis as: wti yi = wti (m + [a] X1i + [d]
X2i), where wti was weight of ith generation; the ratio of family size (ni) of the ith generation per its variance
(s2i).The parameter m was phenotypic average of the two parents, and [a] was the net balance of additive
genetic effects over all the genes. The parameter [d] was the net balance of the dominance effects, which
indicated the direction of dominance of the majority, and X1i and X2i are the coefficients of additive and
dominance effects (Table 1) for ith generation as described by Amiri Fahliani et al. (2010).
The MSs in the ANOVA are independent (orthogonal), but 2s are not. Thus, models are fitted to MSs
(Kearsey and Pooni, 1996). Therefore, in ANOVA table of F3 generation (Table 4) the 'between families' and
'within families' sources of variation mean squares had expectations
+r
and , respectively, where r is
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Intl J Agri Crop Sci. Vol., 5 (13), 1427-1431, 2013
equal to the number of individuals per family. Using the expectations of
(Kearsey and Pooni, 1996), then:
MSw=
= VA + VD + VE
MSB=
and
given for F3 generation
= ( VA + VD + VE) + r (VA + VD + VEC)
=
VA +
VD + VE + r VEC
Where VA is the additive component of genetic variance, VD is the dominant component of genetic
variance, and VE is environmental variance resulted from differences between individuals within families, and
VEC = VEg is equal to environmental variance arising from differences between replications of each nonsegregating genotype; pure line parents and checks (Amiri Fahliani et al., 2010).
Table 1. The generations, their additive-dominance model and the coefficients were used in
the model.
Generation
P1
P2
F3
Parameters
[a]
1
-1
0
m
1
1
1
[d]
0
0
0.25
Table 2. Expectation of sources of variation in terms of the additive genetic and
environmental components, and the coefficients of variance components used in regression.
Parameters
VEC
Source
VE
MSB
1
r
MSW
MSBCs
1
1
0
r
VA
0.5
0
Estimation of all the genetic and environmental components of variation was not possible for
conducting goodness of fit test, also as there were 4 parameters VA, VD, VEC and VE and only 4 statistics,
,
,
and
, in which
computed based on means of variances of 'between replications' and
computed based on means of 'within replications' of parents and controls. It is therefore necessary to ignore
one parameter and, because there is bound to the environmental variation (VE and VEC), VD is set to zero
(Kearsey and Pooni, 1996).
Computing
and
was based on interpretation derived from MSB, and MSW when there was
not any genetic segregation or in other words using pure lines as parents and control varieties. Therefore, for
non-segregating families in which the individuals within each family were derived from single plant, it could be
interpreted that:
MSBCs =
+r
= VE + r VEC, and
MSWCs =
= VE
Thus, to estimate components of variance of existing generations the full model: wtiVi =
wti(VAX1i+VEX2i+VECX3i) was used, where wti is weight of the ith division which is equal to degrees of freedom of
2
the corresponding division i divided by 2(Vi) , and Vi is the variance of ith division. Xis are coefficients of
corresponding variance components as shown in Table 2.
ANOVA and matrix operations and other statistical calculations were conducted using EXCEL software
(Microsoft office, 2003). Test of goodness of fit was conducted for full model of variance analysis using 2
distribution (df = 1, and = 0.05); three parameters based on 4 Statistics or sources. As there were just 3
different generation means including F2:3 families and the parents, so test of goodness of fit for means analysis
was conducted for 2-parameter model.
RESULTS AND DISCUSSION
The means and standard errors of the parents and F2:3 families are given in Table 3. There were
significant differences between parents in most of the traits. However P1 (L-3685) was superior than P2 (Lc741-5-1) for plant height, days to maturity, number of pods per plant and number of seeds per plant, mean values
of other characteristics were higher in P2. The mean of the F2:3 families fell within the range of the parental
values; however some of the families showed considerable transgressive segregation for all of the traits.
The analysis of variance and estimated variance components showed significant differences between
genotypes for all studied traits.
All the possible models were fitted for the traits of interest and those models which showed significant
gene actions were selected (Table 4). The estimated mean effects (m), which reflect the contribution due to
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Intl J Agri Crop Sci. Vol., 5 (13), 1427-1431, 2013
over-all mean plus the locus effects and interaction of the fixed loci was found to be highly significant (P< 0.01)
for all studied characteristics, indicted that these traits were quantitatively inherited. From the obtained results it
could be detected that additive [a] gene effect was highly significant (P< 0.01) for all characteristics (Table 4);
indicating the importance of additive effect for their inheritance.
Table 3. Means and standard errors of the lentil characters for P1 (L-3685), P2 (LC74-1-5-1) and F2:3 lentil families
Plant
height
(cm)
34.4
±3.36
28.7
±2.54
29.90
±4.40
Generation
P1 (L-3685)
P2 (Lc74-1-5-1)
F2:3 families
Leaf area
2
(cm )
Days to
maturity
Days to
flowering
100-seed
weight(g)
seeds
per plant
pods per
plant
2.33
±0.64
5.65
±0.65
3.91
±0.90
107
±2.21
102.3
±2.00
103.20
±4.27
72.5
±1.14
77.3
±2.11
74.30
±4.39
2.14
±0.22
3.21
±0.25
2.57
±0.41
84.71
±9.203
43.9
±7.71
180.82
±81.15
51.9
±5.80
30.4
±4.83
61.32
±44
Seed yield
per plant
(g)
3.87
±0.47
3
±0.49
2.72
±1.96
Table 4. Means analysis of 2-parameter model for the evaluated traits and their ± standard errors in F2:3 lentil families.
Parameter
m
[a]
2
(df=1)
Plant
height
(cm)
30.22**
±0.36
2.58**
±0.81
ns
2.60
Leaf area
2
(cm )
Days to
maturity
Days to
flowering
100-seed
weight(g)
seeds per plant
pods per plant
3.93**
±0.08
1.66**
±0.02
ns
0.12
103.62**
±0.33
2.25**
±0.61
ns
2.85
74.50**
±0.32
2.34**
±0.57
ns
0.49
2.59**
±0.03
0.52**
±0.07
ns
1.46
75.32**
±2.33
28.39**
±2.45
ns
2.24
43.74**
±1.44
11.22**
±1.54
ns
2.82
Seed yield
per plant
(g)
3.18**
±0.11
0.44**
±0.13
ns
3.62
** and ns mean highly significant (P < 0.01) and non-significant respectively.
In all traits the chi-square ( 2) values, were non-significant. This showed that the simple additivedominance model using 2-parameter model based on m and [a] fitted for all traits.
The parameter [d] was not significant for all of the evaluated traits when 3-parameter model analysis
was used (data not shown). In fact, according to previously cited literature, there was no reason to expect that
the traits will be affected by other gene effects (Kearsey and Pooni, 1996).
The results of the estimates for the variance model and narrow sense heritability values based on
ANOVA method and 2-parameter model are presented in tables 5 and 6 respectively. Variance components
analysis showed that additive (VA) and environmental (VE) components of variance were highly significant for all
of the evaluated traits based on both of the tow different computations methods. In all traits the chi-square ( 2)
values were found non-significant (Tables 5 and 6). Thus, the two-parameter model based on VA and VE was
adequate for our obtained information in variance analysis. The high magnitude of additive variance for most of
the traits indicated the relative importance of fixable type of gene action in their inheritance. The presence of
higher magnitude of additive gene action for seeds per pod and plant height has also been reported by Kumar
et al. (2011) in lentil and Sharma et al. (2008) in peas. The preponderance of additive component of genetic
variance for the expression of days to flowering, days to maturity, plant height, pods per plant and seeds per
plant indicates the possibility of improvement of these traits through pedigree method of selection procedure.
But the existence of substantial amount of non-additive components indicates the use of diallel
selective/biparental mating or recurrent selection for improvement of the trait (Sood et al., 2007).
Table 5. Variance components, their ± Standard error, and narrow sense heritability resulting from ANOVA of F3 families based on
Kearsey method (Kearsey and Pooni, 1996).
VA
VE
h
2
n
Plant height
Leaf area
3.98**
±0.72
13.50**
±0.78
0.23
0.13**
±0.02
0.41**
±0.02
0.24
** and
ns
Days to
maturity
8.37**
±1.21
5.72**
±0.75
0.59
Days to
flowering
8.25**
±0.79
6.97**
±1.21
0.54
100-seed
weight
0.033**
±0.01
0.11**
±0.01
0.22
seeds per plant
pods per plant
737.67**
±173.43
5490.36**
±278.28
0.12
193.94**
±48.33
1646.87**
±82.31
0.10
Seed yield
per plant
0.32**
±0.08
2.99**
±0.14
0.12
mean highly significant (P < 0.01) and non-significant respectively.
Comparison of the gained results from the both used different methods of variance component analysis
showed that the results derived from ANOVA method was completely similar to the 2-parameter model of
regression method (Tables 5 and 6). This was not out of suspense, because the 2-parameter model was similar
to ANOVA method with ignoring the dominance and VEC components.
Considering the results of means and variances analysis, the evaluated traits had higher gene
association as they had significant values of [a] and VA.
The magnitude of narrow sense heritability for a highly heritable trait is more than 0.5 and for a medium
heritable it is between 0.2 and 0.5 (Singh, 2005). The high heritability coefficients (>50%) observed for days to
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flowering and days to maturity (Tables 5 and 6) indicating that early generation selection might be successful
even in F3 generation, by directing the selection process for the most promising genotypes. Broad sense
heritability values for days to maturity and days to flowering were noted to be high (Bicer and Sakar, 2010),
moderate to high ( Muehlbauer et al., 1994), and moderate (Kumar and Dubey, 2001). However, low value
(<30%) of heritability was reported by Kumar et al. (2011) for days to 75% maturity and days to 50% flowering.
Table 6. Variance components for 2-parameter model and their ± standard error, goodness of fit and narrow sense heritability for
evaluated traits.
VA
VE
2
n
2
(df=1)
h
Plant height
Leaf area
3.99**
±0.71
13.47**
±0.78
0.23
ns
0.01
0.12**
±0.02
0.41**
±0.02
0.24
ns
0.00
** and
ns
Days to
maturity
8.39**
±1.21
5.70**
±0.74
0.59
ns
0.001
Days to
flowering
6.97**
±0.78
8.24**
±1.21
0.54
ns
0.001
100-seed
weight
0.03**
±0.01
0.11**
±0.01
0.22
ns
0.005
seeds per plant
pods per plant
736.69**
±173.43
5493.88**
±278.27
0.12
ns
0.00
193.81**
±48.33
1647.36**
±82.31
0.10
ns
0.00
Seed yield
per plant
0.36**
±0.08
2.78**
±0.14
0.12
ns
2.01
mean highly significant (P < 0.01) and non-significant respectively.
Bicer and Sakar (2010) noted that seed yield per plant have a very low heritability (0.13) which is
parallel to our findings of low heritability (0.12) for this trait followed by number of seeds per pod and number of
pods per plant (Tables 5 and 6). For the selection of inbred lines, low heritability traits must be selected in more
advanced generations (F6 onwards), because there is an increase in heritability in the course of inbreeding,
owing to the increase of additive genetic variance and decrease of the dominance variance. In other words, for
low heritable traits the contribution of environmental conditions is relatively high (Singh, 2005).
The simple selection procedure in the early segregating generation may not contribute significantly for
the improvement of these traits. The complex genetic behavior particularly additive and dominance components
could be successfully exploited in advanced generations. It is therefore, suggested that selection for the
improvement of such traits, particularly seed yield, should be delayed to the advanced generations of
segregation population.
Based on the presented information in tables 5 and 6, low heritability was obtained for seeds per pod,
pods per plant and seed yield per plant. The low estimates of heritability indicate that there is preponderance of
non-additive gene action and recombinant breeding may thus be useful (Kumar et al., 2011). Also low estimate
of heritability indicates that environmental factors strongly influence the character, and in this situation,
phenotype is not highly correlated with genotype, making selection for the concerned trait difficult.
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