Generation Mean Analysis for Yield, its Components and Quality Characteristics
in Four Crosses of Egyptian Cotton (Gossypium barbadense L.)
U.A. Abd El-Razek
The objective of the present investigation was to estimate genetic variance
components and type of gene action controlling yield, its components and quality
characteristics of some cotton crosses, by means of the six populations (P1,
P2, F1, F2, BC1 and BC2)
of the four cotton crosses. Results revealed that the estimated mean effects
(m) were highly significant for all traits in all crosses, indicated that these
traits were quantitatively inherited. Additive and dominant gene effects were
highly significant for No. of bolls/plant, boll weight in the fourth cross,
2.5% span length in the second cross, fiber fineness in the first and fourth
crosses, with lager of dominance effects in magnitude than additive ones. Dominance,
additivexdominance and dominancexdominance were at least significant for No.
of bolls/plant in the first cross, seed and lint cotton yields in the first
and second crosses, boll weight in the fourth cross, 2.5% span length and fiber
fineness in the first cross and fiber strength in the second cross, indicated
that these traits were greatly affected by dominance and their non-allelic interactions.
Narrow-sense heritability and genetic advance were low in most cases due to
the opposite directions of dominance and dominancexdominance effects resulted
in lower overall dominance variance. It could be concluded that heterosis over
mid and better parent were highly significant in all crosses for No. of bolls/plant,
seed and lint cotton yields/plant with low inbreeding depression.
Received: July 19, 2012;
Accepted: November 01, 2012;
Published: February 02, 2013
Cotton (Gossypium barbadense L.) is one of the most important fiber
crops all over the world. In Egypt, its importance is derived from being one
of the main sources of foreign currency as well as the principle raw material
for the national textile industry and one of the important sources of edible
oil (El-Saeidy et al., 2003). The total cultivate
began to decline in the last decade, which requires working to increase the
production of unit area to compensate the shortfall in the cultivated area.
Knowledge of genetic diversity and relationships among breeding materials is
essential to the plant breeders for improving the crop (Abd
El-Haleem et al., 2010).
Gamble (1962) reported that epistatic gene effects
are present in sufficient magnitude in quantitative traits which may alter the
breeders account for the breeding method which must be followed. If the additive
genetic variance is of major importance, the intra-population selection will
be considered as the most effective procedure for gathering the favorable genetic
constitutions. If dominance variance especially over-dominant is predominant,
then the hybrid program for commercial purpose may be the appropriate choice.
Therefore, the estimation of gene action and the inheritance of the traits especially
seed yield is an interesting procedure for the breeders in order to formulate
the most efficient breeding method to bring about the maximum improvement of
the attribute in question. Both additive and non-additive genetic effects control
seed cotton yield (Kalsy and Garg, 1988; Tyagi,
1988; Deshpande and Baig, 2003). However, McCarty
et al. (2004) reported additivexadditive epistatic effects for the
inheritance of seed cotton yield and Basbag et al.
(2008) reported heterotic effects in some cotton crosses. Pathak
(1975) used six populations (P1, P2, F1,
F2, BC1 and BC2) of five upland cotton (Gossypium
hirsutum L.) crosses to evaluate genetic effects for fiber traits.
Improvement in textile processing has led to increased emphasis on breeding
cotton for improved fiber properties. Fiber fineness determines the texture
of cotton fiber. Cotton fiber may be classified as soft and silky or coarse
Cotton breeding program based on the genetic information of traits needs to
be improved (Rahman and Malik, 2008). Therefore, the
present study aimed to obtain useful information about gene action of yield
and quality characters as well as the extent of hybrid vigour, heritability
and genetic advance in the four cotton crosses.
MATERIALS AND METHODS
The experiments reported herein were carried out during 2007, 2008 and 2009
seasons. The four initial crosses Giza 45xPima S7, Giza 88xPima S7,
Giza 90xSuvin and Giza 88xSuvin which designated in the text as first, second,
third and fourth cross, respectively. Pedigree, origin and characteristics of
the parental varieties are shown in Table 1.
The crosses were developed in 2007 season at the Faculty of Agriculture farm,
Tanta University. In 2008 season, F1 plants were selfed and backcrossed
to each parent to obtain the F2, BC1 and BC2
for each cross. In parallel, the hybrid seeds were obtained by crossing each
two parents of each cross as F1 seeds.
The six populations; P1, P2, F1, F2,
BC1 and BC2 of each cross were sown at the experimental
farm, Faculty of Agriculture, Tanta University during 2009 season as follows:
two ridges for each patent and F1's, seven ridges for BC's and twelve
ridges for the F2 plants. Two, seven and twelve ridge plots were
used to reduce intergenotypic competition between generations and to sample
adequately the genetic variability within generations.
Each ridge of one side comprised of 20 hills spaced at 20 cm apart and 60 cm
wide. Hills were thinned later leaving one plant per each hill. All cultural
practices were followed for the ordinary cotton fields in the area.
Data were recorded on an individual guarded plant of the six populations for
each cross where 20, 20, 25, 200, 120 and 120 plants were chosen from P1,
P2, F1, F2, BC1 and BC2
of each cross, respectively, to collect the following traits:
||No. of bolls/plant
||Boll weight in grams
||Seed cotton yield (g)/plant
||Lint cotton yield (g)/plant
||Lint percentage which calculated as lint cotton yield/seed cotton yieldx100
||2.5% span length
|| Pedigree, origin and main characteristics of the parental
Statistical and genetic analysis: To determine the presence or absence
of non- allelic interactions, scaling test as outlined by Mather
(1949) was used. The quantities A, B, C and D and their variances have been
calculated to test adequacy of the additive-dominance model in each case. Where:
The standard error of A, B, C and D is worked out by taking square root of
respectively variances. The t-values are calculated by dividing the effects
of A, B, C and D by the respectively standard error. The calculated t-values
were compared with tabulated value of t at 5% levels of probability in each
test, the degrees of freedom (df) is sum of (df) of various generation involved.
The significance of A and B scales indicate the presence of all types of non-allelic
gene interactions. The significance of C scale suggests (dd) types of epistasis.
The significance of D scale reveals (aa) gene interactions, significance of
C and D scale indicates (aa) and (dd) type of gene interactions (Singh
and Narayanan, 1993).
Genetic analysis of generation means to give estimates of the types of gene
effects were obtained using the relationships given by Gamble
Jinks and Jones (1958) however, used following formulae
to estimate m, a and d components in the absence of non-allelic interactions:
where, Their variances have been computed using following formulae:
||SE (m) = ,
SE [ d] =
and SE [h] =
||t(m) = m/SE(m), t[d] = d/SE[d] and t[h] = h/SE[h]
Broad+sense heritability (H2) for F2¯ generation
was estimated based on the equation:
The genetic variance (Vg) and environmental (Ve) were
estimated according to Mansur et al. (1993) as
are the number of plants of P1, P2 and F1 generations
in each cross, respectively.
Narrow-sense heritability (h2) for F2¯ generation
was estimated as proposed by Warner (1952).
The Phenotypic (PCV%) and Genotypic (GCV%) coefficient of variation were estimated
as formulae developed by Burton (1952).
The expected genetic advance from selection (Ga) was calculated
as the formulae proposed by Johnson et al. (1955),
using the selection differential (k) equal 2.06 for 5% selection intensity and
heritability in narrow sense.
The predicted genetic advance where the expected genetic gain upon selection
was expressed as percentage of F2 mean (Ga%) was calculated
following Miller et al. (1958).
The amount of heterosis was expressed as the percentage deviation of F1
mean performance from mid-parent and better parent. Inbreeding depression was
calculated as the difference between the F1 and F2 means
as a percentage of F1. The "t" test was used to determine the significance
of these deviations where the standard error (SE) was calculated as follows:
where, the t is the deviation/SE at the corresponding degrees of freedom.
RESULTS AND DISCUSSION
The data presented in Table 2 revealed the mean performance
of the six generations and variance of mean advanced from the four crosses of
cotton for the traits in view. These data used to calculate the salling test
and six parameters as Gamble procedure. At least one of the scales was significant
in the four crosses for all studied traits, except lint percentage in the second
and third crosses boll weight in the first and second crosses seed index in
the first cross; 2.5% span length, fiber fineness and fiber strength in the
third and fourth crosses, where all scales were not significant. However, the
significance of any one of the scale reveals the presence of non- allelic interaction
as pointed out in Table 3. Hence, for non expected traits
additive- dominance model was not sufficient to explain most the genetic variation
for the expression of these traits. This show that epistatic effects were contributed
to the inheritance of these traits in the crosses pointed out and this might
suggest that, the inheritance of these traits is complex and polygenic (Warnock
et al., 1998). On the other side, the insignificant of all scales
for the excepted traits mentioned, indicating a simple additive-dominance model
was adequate for estimating the genetic components of variance of these traits.
This indicates that, selection could be practiced effectively in F2
generation for improving theses traits. However, additive gene effects were
highly significant in all cases, except lint percentage in the second cross
and fiber strength in the fourth cross, indicating that the additive genes were
more important than dominant ones in controlling the inheritance of these traits.
The estimated mean effects (m), which reflects the contribution due to over-all
mean plus the locus effects and interaction of the fixed loci was found to be
highly significant for all studied traits in all crosses, indicted that these
traits were quantitatively inherited. From the obtained results (Table
3), it could be detected that, additive [d] and dominant [h] gene effects
were highly significant for number of bolls/plant and boll weight in the cross
IV, 2.5% span length in the cross II, fiber fineness in the cross I and IV,
indicating that both additive and dominance were important for the inheritance
of these traits.
It could be observed that dominance effects are several times larger than additive
one and this might indicate that dominance gene effects play the major role
in controlling the genetic variation of most studied traits. These results are
in the same trend with those reported by Abd El-Haleem et
al. (2010) and Karademir and Gencer (2010).
|| Analysis of the six generations advanced from four crosses
of cotton for yield, its components and some technological characteristics
|| Estimates of scalling test and type of gene action of four
cotton for nine traits
|*,**Significant at 0.05 and 0.01 levels of probability, respectively
However, the three quality characters i.e., 2.5% span length, fiber fineness
and fiber strength could be excepted from the latest conclusion, where additive
gene effects were highly significant in most crosses and lager in magnitude
than dominant ones, which reflect the great importance of additive genes in
the inheritance of these traits.
Jagtap (1986) stated that when additive effects are
lager than non-additive ones, it is suggested that selection in early segregating
generations would be effects, while if the non-additive portion are lager than
additive one, the improvement of the characters need intensive selection through
later generation. These conclusion are in the same line with those found by
Dhillon and Singh (1980), Singh
et al. (1983), Lin and Zhao (1988), Mert
et al. (2003), Murtaza (2005) and Esmail
With regard to the negative values observed in most cases either with main
effects; [d] and [h] or the non-allelic interactions; [i], [j] and [l], these
might indicate that, the alleles responsible for less values traits were over
dominant over the alleles controlling high value. However, it could be detected
that the effects of additive and dominant genes were in the opposite direction,
where its signs were not similar. This was true for all traits in all crosses,
except No. of bolls/plant in the first cross, seed cotton yield/plant in the
third cross, lint cotton yield/plant in the third and fourth crosses, seed index
and 2.5% span length in the fourth cross and fiber strength in the first, second
and fourth crosses.
In all crosses for all studied traits, it could be observed that the signs
of dominance [h] and dominancexdominance [l] gene effects were opposite, except
seed and lint cotton yield in the cross III; 2.5% span length and fiber strength
in the cross I, suggesting duplicated type of non-allelic interaction in these
Since none of the sings of [h] were similar to the [i] type of epistasis, it
was concluded that no complementary type of interaction was present in the genetic
control of the studied traits. However, dominance [h], additivexdominance [j]
and dominancexdominance [I] which referred as non-additive genetic variance
were at least significant for number of bolls/plant in the cross I, seed and
lint cotton yields in the crosses I and II, boll weight in the cross IV, 2.5%
span length and fiber fineness in the cross I and fiber strength in the cross
II. This would indicate that, these traits were greatly affected by dominance
as main effect and their non-allelic interactions as epistatic effects. These
results are in good agreement with those reported by Bhardwaj
and Kapoor (1998), Esmail et al. (1999),
El-Disouqi and Ziena (2001), Abdul-Hafeez
et al. (2007), Esmail (2007), El-Beially
and Mohamed (2008) and Abd El-Haleem et al. (2010).
However, when epistatic effects were significant for a trait, the possibility
of obtaining desirable segregates through inter-mating in early segregations
by breaking undesirable linkage could be available or it is suggested to adopt
recurrent selection for handling the above crosses for rapid improvement. Abo
El-Zahab and Amein (2000), Dong et al. (2006),
El-Beially and Mohamed (2008) and Hendawy
et al. (2009) came to the same conclusion.
Heterosis over mid-parent and better parent, inbreeding depression, heritability
in broad and narrow-senses, genetic advance, phenotypic and genotypic coefficient
of variations are presented in Table 4. Highly significant
heterosis over mid-parent and better parent was observed in all crosses for
number of bolls/plant, seed and lint cotton yields/plant with low inbreeding
|| The genotypic and phenotypic analysis of four cotton crosses
for nine traits
|*,**Significant at 0.05 and 0.01 levels of probability,
Heterosis over mid-parent, :
Better parent, P: Potence ratio, ID: Inbreeding depression, H2:
Heritability in broad, h2: Narrow-senses, PCV: Phenotypic coefficient
of variance, GCV: Genotypic coefficient of variance
Over-dominance (p<+1) is not only the case of heterotic effects but also
the non-allelic interactions might be mainly caused this heterosis for these
traits. Significant heterotic effects relative mid-parent and better parent
were detected in all crosses for lint percentage, boll weight and seed index,
except the cross II for boll weight, where the two values were not significant,
the cross I for lint percentage and cross VI for seed index, where the values
over better parent were positive but insignificant. However, the heterotic effects
in most cases pointed out were attributed to over dominance, where potency ratio
exceeded the unity (p<+1). The low values of inbreeding depressions reflects
the low reduction in the mean of F2¯ generation due to the direct
effect of homozygosity, this low reduction might be attributed to the low sensitivity
of the present materials to the inbreeding processes. Abdalla
(2007) reported that cotton has a relatively low inbreeding depression.
Narrow-sense heritability estimates were-generally-lower than the corresponding
broad sense heritabilities, indicating the presence of non-additive gene action.
The low h2 estimates which ranged from 1.16-36.86%, suggested that
the inheritance is complex. From six generations of four crosses, environmental,
additive and dominance variances were estimated to calculate heritability and
genetic advance. In most cases, narrow-sense heritability and genetic advance
were very low due to the opposite direction of additive and dominance variances.
Moreover, the opposite directions of dominance and dominancexdominance effects
results in lower overall dominance variance (Table 3). The
genetic gains as a parameter for selection efficiency are related to genetic
variability and selection intensity. Low genetic gains which an expected results
due to the low values of h2 and genotypic (GCV%) and phenotypic (PCV%)
coefficient of variability, indicated that phenotypic effect is mainly controlled
by environmental variation. Therefore, for selection of the best genotype, it
should concentrate mainly on yield components more than yield itself.
From this investigation it could be concluded that (1) dominance gene effects
play the major role in controlling the genetic variance of yield and most of
its components, while additive genes were the predominant for quality characters
(2) heterosis over mid and better parent were highly significant in all crosses
for No. of bolls/plant, seed and lint cotton yields/plant with low inbreeding
depression and (3) narrow-sense heritability and genetic advance were very low
due to the opposite direction of additive and dominance variances.
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