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COMBINING ABILITY ANALYSIS FOR YIELD AND PHYSIOLOGICAL DROUGHT RELATED TRAITS IN TOMATO (SOLANUM LYCOPERSICUM L.) UNDER MOISTURES STRESS

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8(4): 1537-1544, 2013 (Supplement on Genetics & Plant Breeding) www.thebioscan.in
1537
COMBINING ABILITY ANALYSIS FOR YIELD AND PHYSIOLOGICAL
DROUGHT RELATED TRAITS IN TOMATO (SOLANUM
LYCOPERSICUM L.) UNDER MOISTURES STRESS
ANITA PEDAPATI*, R. V. S. K. REDDY, J. DILIP BABU1, S. SUDHEER KUMAR2 AND N. SUNIL3
*Germplasm Exchange Unit, National Bureau of Plant Genetic Resources, New Delhi - 110 012
1Vegetable Research Station, Dr.Y.S.R.H.U, Rajendranagar, Hyderabad - 500 030
2ANGRAU, Rajendranagar, Hyderabad - 500 030
3DMR Winter nursery, Rajendranagar, Hyderabad - 500 030
e-mail: anita.pedapati@gmail.com
INTRODUCTION
Tomato (Solanum lycopersicum L.) is one of the widely grown
vegetable crops cultivated for its fleshy fruits in the world.
Tomato is protective supplementary food and considered as
important commercial and dietary vegetable crop. As it is short
duration crop and gives high yield, it is important from
economic point of view and hence area under its cultivation
is increasing day by day. In India tomato ranks second among
vegetables in area and production, which is grown over an
area of 9,33,250 ha with annual production of 193,77,440
MT and productivity of 20.8MT/ha (Indian Horticulture
Database 2012-13).
To meet the ever increasing demand for this vegetable crop,
there is a need for development of hybrids and varieties with
improvement in yield, quality and resistance to different biotic
and abiotic stresses. Plants are exposed to a range of
environmental stresses and have to adapt physiologically to
them as the local environment changes. Insufficient availability
of water i.e., drought, is presumably the most common stress
experienced by plants. Drought is one of the main factors for
the yield loss in plants. Drought is the major inevitable and
recurring feature of semi-arid tropics. Drought tolerance is the
ability of plants to survive water deficit stress and to maintain
plant growth under water deficit conditions (Nahar and
Gretzmacher, 2011). Moreover in recent years, due to
dramatic change in climatic conditions from the effect of global
warming, drought stands as first problem for the crop
production. Breeders and biotechnologist are much focused
on development of drought resistant or tolerant crops. Drought
resistant crop plants would provide a great benefit to the global
market. Especially arid and semi-arid areas of the planet would
benefit the most from such an invention (Roberto Gaxiola,
2006).
During the course of the last century, tomato varietal
improvement programme has been based on various standard
breeding methods. Tomato improvement occurred due to
increasing exploitation of exotic resources and introgression
of new valuable genes into the tomato gene-pool (Shende et
al., 2012). Tomato breeders prefer hybrid breeding to varietal
breeding, not only because it is comparatively easier to
incorporate desirable characteristics in F1 hybrid but also the
right of the bred hybrid is protected in terms of parental lines.
Identification and selection of flexible parental lines are
required to be used in any hybridisation programme to
produce genetically modified and potentially rewarding
germplasm by assembling fixable gene effects more or less in
a homozygous line. Information pertaining to different types
of gene action, relative magnitude of genetic variance, and
combining ability estimates are important and vital parameters
to mould the genetic makeup of tomato crop. This important
information could prove an essential strategy to tomato
ABSTRACT
Eighteen parents were crossed in line X tester fashion comprising 15 lines and 3 testers to estimate combining
ability in tomato for fruit yield, yield components and drought tolerant traits. F1 and parents were evaluated
under stress (10 days and 15 days irrigation interval) and irrigated conditions. For fruit yield per plant, the top five
crosses EC310301 X EC164654 (251.33), EC 251578 X EC 164654 (304.82), IC249512 X IC249503 (381.70),
EC162516 X IC249503 (468.85) and EC164845 X IC249505 (571.92) having high and positively significant sca
effects under irrigated normal condition. Whereas, in stressed condition IC249512 X IC249503 (258.06), IC249512
X EC164654 (260.16), EC310301 X EC164654 (314.06), EC162516 X IC249505 (388.34) and EC164845 X
IC249505 (469.54) having high and positively significant sca effects. Based on results, the genotypes EC251578,
IC249512, EC162516, EC249503 and EC164654 recorded high positive gca effects. IC249512, EC164845,
EC249505 and EC164654 are ideal choice for yield under stressed condition. IC249512 was good performer for
most of the traits in both irrigated and stressed conditions. Three parents EC162516, EC249505 and EC168096
are identified as good general combiners with high yield potential in drought environment. So, these lines are
reliable for further drought tolerance breeding.
KEYWORDS
Tomato
Drought
Combining ability
Yield
Received on :
17.09.2013
Accepted on :
06.12.2013
*Corresponding
author
1538
ANITA PEDAPATI et al.,
breeders in the screening of better parental combinations for
further enhancement.
There are several techniques for the evaluation of varieties or
strains in terms of their combining ability especially line x
tester analysis is one of them. This technique was developed
by Kempthorne in 1957. Keeping in view with the above
problem, the present investigation is taken up with the following
objectives: To study the general and specific combining ability
of parents and crosses for yield and yield contributing
characters and to study the relative performance of parents
and F1
s for various characters under stress and irrigated
conditions.
MATERIALS AND METHODS
Tomato is generally grown under irrigated conditions, and its
cultivation as a rainfed crop has gained importance particularly
in semi-arid region. It is therefore very important to obtain
information on the drought resistance mechanisms and
incorporate drought tolerant traits in breeding programme for
crop improvement. Hence, this experiment was undertaken
during 2011-2013 at Vegetable Research Station,
Dr.Y.S.R.H.U, Rajendranagar, Hyderabad. Field imposed
irrigation treatments with an interval of 10 days and 15 days
irrigation interval (DII)
The 45 F1
s obtained were evaluated along with parents and
commercial checks for yield, yield contributing various
characters under stress and irrigated conditions. Plants
uprooted carefully with the help of crow bar without causing
damage to the root portion. Roots were washed thoroughly
with water and the root and shoot portions were separated.
These root and shoot parts were allowed to dry in an oven at
80ºC till constant dry weights were obtained and root to shoot
dry weight ratio was calculated
Stomatal diffusive resistance (SDR) was recorded at 60 days
after transplanting between 11.00 hr and 12.00 hrs using LI
6400 XT portable photosynthesis system and expressed in
seconds per centimeter. To measure the RWC, the leaves were
sampled at fixed time of the day. Fully opened physiologically
functional leaf from top was selected. Fresh weight of the
samples was recorded by detaching the petiole. The leaf
samples were kept in water for overnight to attain turgidity.
The turgid weight of sample was recorded. After oven drying
at 72ºC for 48 hours, dry weight of sample was recorded (Bars
and Weatherly, 1962). The relative leaf water content (RWC)
was estimated and expressed in per cent by using the equation
given below
Leaf area was measured by taking five leaves from each sample
plant were taken and the leaf area was measured with the CI-
202 portable laser leaf area meter and mean value was
expressed in square centimetres. Specific leaf weight (SLW),
differs significantly among the genotypes under moisture stress.
Specific leaf weight were estimated in sq.cm and was measured
with leaf area meter, then the leaf samples were dried in hot air
oven at 80oC for 48 hours and the weight was recorded in
milligrams. Specific leaf weight was calculated by using the
formula
Table 1: Analysis of variance for combining ability for 22 traits under control, 10 days and 15 days moisture stress treatments
S. Source df Fruit yield (g) Shoot dry weight (g) Root dry weight (g) RDW/ SDW
no Control 10 days 15 days Control 10 days 15 days Control 10 days 15 days Control 10 days 15 days
1. Replication 2 9118.6 10635.00 59126 0.30 0.03 0.66 1.35 3.35 1.86 0.002 0.003 0.001
2. Parents 17 28127.4 84120.47 85344 1537.00** 1511.00** 1495.45** 145.12** 185.88** 196.86** 0.040** 0.048** 0.056**
3. Parents (Line) 14 21025.9 84714.67 57064 1777.43** 1739.05** 1719.84** 149.28** 198.84** 211.90** 0.042** 0.052** 0.061**
4. Parents (Testers) 2 28970.7 81154.00 48714 32.34* 15.05** 10.36** 4.93* 7.61** 10.26** 0.004 0.010** 0.013**
5. Line VS Tester 1 125872.0** 81748.00 554524** 1180.38** 1310.09** 1324.24** 367.34** 361.02** 359.61** 0.088** 0.067** 0.072**
6. F1’s 44 257149.1** 243398.80** 168766** 1495.06** 1511.84** 1493.30** 183.61** 185.88** 190.87** 0.120** 0.143** 0.170**
7. Parents VS Hybrids 1 27712.0 50592.00 106960** 40.39** 0.16 12.27** 7.79** 13.73** 28.00** 0.001 0.037** 0.076**
8. Error 124 27752.6 68152.25 84569 10.50 0.03 0.05 1.56 0.20 0.04 0.002 0.000 0.000
Table 1: Cont......
S. No.Source df SDR (sec/cm) Relative Water content Leaf area (sq.cm) Specific leaf weight (mg/sq.cm)
Control 10 days 15 days Control 10 days 15 days Control 10 days 15 days Control 10 days 15 days
1. Replication 2 0.3 0.57 0.01 4.0 3.36 3.76 0.2 0.24 0.29 5504.7 27164.00 19596.00
2. Parents 17 68.7** 67.83** 69.51** 381.0** 360.80** 340.76** 2110.5** 2084.33** 2096.37** 16915.6 32506.98 41286.59
3. Parents (Line) 14 21.8** 22.35** 22.17** 422.6** 397.24** 370.29** 2267.8** 2234.06** 2247.38** 20121.1 36019.24 31533.14
4. Parents (Testers) 2 7.6** 9.22** 17.10** 273.2** 279.79** 294.81** 40.6** 37.66* 40.00** 2221.2 10466.00 59034.33*
5. Line VS Tester 1 847.7** 821.74** 837.12** 14.8** 12.68 19.24** 4048.5** 4081.32** 4095.01** 1427.0 27420.00 142330.00**
6. F1’s 44 25.7** 24.79** 24.64** 225.6** 232.51** 225.71** 2047.1** 2091.42** 2148.86** 27061.0** 30875.27 84868.84**
7. Parents VS Hybrids 1 69.5** 91.96** 121.87** 194.6** 140.63** 132.28** 12.6 220.94** 1084.69** 2808.0 184336.00** 347920.00**
8. Error 124 0.005 0.03 0.17 1.0 1.66 1.96 0.8 0.14 0.17 11891.2 22000.50 25417.70
Dry weight of the leaf in
milligrams
Specific leaf weight (mg/sq.cm) =
Area of the leaf in sq.cm.
1539
COMBINING ABILITY ANALYSIS FOR YIELD AND PHYSIOLOGICAL DROUGHT
Combining ability was estimated based on the method of
Kempthorne (1957). The estimates of general and specific
combining ability effects (gca and sca) and their variances
were obtained by using covariance of half sibs and full sibs.
RESULTS
The analysis of variance (ANOVA) for combining ability
revealed the existence of significant variation for eight
characters, representing a wide range of variability among the
genotypes. Highly significant variation due to gca as well as
sca indicated the importance of additive as well as non-additive
types of gene action of inheritance for all the traits except the
number of fruits per plant were presented in Table 1. The
ANOVA revealed that the parents as well as crosses exhibited
significant differences for all the traits studied except for fruit
yield and specific leaf weight, (10 and 15 DII), whereas parents
vs crosses exhibited significant differences for 8 traits (control),
in 10 days irrigation interval except for yield and SDW. The
effects of lines were found to be significant for all the traits
studied except for specific leaf weight, fruit yield per plant,
specific leaf weight (10 DII) fruit yield per plant, specific leaf
weight(15 days irrigation interval). Whereas the effects of testers
were non significant for average yield per plant, RDW/SDW
and specific leaf weight (control), number of fruits per plant,
fruit yield per plant, specific leaf weight (10 DII), fruit yield per
plant (15 DII) .
The interaction effects (Lines X Testers) were found to be
significant for all the traits except for specific leaf weight
(control). Further, the mean sum of squares attributed to the
male and female parents of hybrids provide a measure of their
gca and the interaction between the male and female parents
provide a measure of sca. In general, the hybrids were early in
maturity and high yielding compared to the parents, which is
desirable and exploited for development of high yielding
hybrids.
General combining ability
The summery of the gca effects of the parents (Table 2 and 3)
revealed that, the line EC251578, IC249512, EC162516 and
the tester EC249503 and EC164654 exhibited highly
significant and positive gca effects and are adjudged as good
general combiners for fruit yield per plant. Under 10 DII among
the lines, IC249512, EC251578 and EC164845 recorded
significant positive gca effects. Under 15 DII among the lines,
IC249512 and EC164845 recorded significant positive gca.
Among the testers positive significant gca effect was revealed
by EC164654.
GCA effects differed according to the stress and non stress
conditions the lines, NS537and EC162516, IC249512,
EC635525 and IC249513 recorded significant positive gca
effects for shoot dry weight. Among the testers positive
significant gca effect was displayed by EC164654, while under
10 DII, EC162600, NS 537, and EC162516 recorded
significant positive gca effects while among the testers positive
significant gca effect was exhibited by IC249505 for shoot dry
weight. The line which exhibited highest significant positive
gca effect under 15 DII was EC162600, NS 537 and EC162516
while, among the testers positive significant gca effect was
exhibited by IC249505. This implied that among the testers,
Table 2: Estimates of gca effects for lines and testers for fruit yield (g), shoot dry weight (g), root dry weight (g) and RDW/SDW traits in tomato under irrigation (control) and drought
stress (10 and 15 days irrigation interval) conditions
Source Fruit yield (g) Shoot dry weight (g) Root dry weight (g) RDW/SDW
Control 10 days 15 days Control 10 days 15 days Control 10 days 15 days Control 10 days 15 days
EC251578 339.74** 295.59** 47.31 -12.34** -12.27** -12.45** -9.82** -9.75** -10.02** -0.19** -0.21** -0.23**
NS537 -154.57** -39.98 -98.33 36.54** 36.61** 36.41** 8.67** 8.59** 8.48** -0.05** -0.05** -0.05**
EC162516 254.18** -77.62 -67.33 23.03** 22.79** 22.49** 10.31** 10.13** 10.01** 0.03** 0.03* 0.03**
EC164845 53.00 176.72* 164.79* -5.54** -5.25** -5.23** -3.35** -3.43** -3.42** -0.06** -0.07** -0.07**
IC249512 324.77** 358.97** 329.37** -19.70** -19.55** -19.69** -6.62** -6.69** -6.82** -0.04** -0.05** -0.06**
EC165952 -99.06 -13.33 1.60 -11.20** -11.23** -11.11** 1.92** 1.96** 1.86** 0.12** 0.13** 0.13**
EC164665 -220.14** -132.28 -143.98 -24.42** -24.64** -24.35** 1.25** 1.21** 1.07** 0.40** 0.44** 0.46**
IC249511 20.83 -269.05** -81.82 6.44** 6.52** 6.61** 9.41** 10.45** 10.50** 0.13** 0.15** 0.16**
EC168096 -58.07 -20.19 20.44 -13.49** -14.30** -14.16** -4.94** -4.98** -5.26** -0.04** -0.04** -0.05**
EC164677 -20.68 18.57 -46.16 -21.67** -21.36** -20.81** -8.72** -8.36** -8.52** -0.10** -0.09** -0.12**
EC162600 -53.54 51.10 2.73 46.09** 46.52** 45.86** 0.58 0.47** 0.35** -0.17** -0.17** -0.17**
EC310301 -323.66** -386.89** -257.88** -25.16** -25.12** -25.15** -8.39** -8.54** -8.39** -0.04** -0.06** -0.07**
EC635525 -0.14 106.09 11.59 15.77** 15.96** 15.87** 3.38** 3.23** 3.61** -0.04** -0.04** -0.03**
IC249513 -67.96 -88.87 61.63 7.77** 7.54** 7.55** 2.89** 2.81** 3.01** -0.01 -0.01 -0.01
EC241148 5.29 21.18 56.02 -2.13** -2.23** -1.83** 3.45** 2.89** 3.53** 0.07** 0.05** 0.07**
SEi 43.31 73.92 75.79 0.05 0.05 0.06 0.23 0.08 0.05 0.004 0.00 0.003
EC164654 10.77** 44.63 7.61 1.07** 0.58 0.38** 0.91** 1.05** 1.08** 0.00 0.01 0.01
IC249503 32.21** 13.92 -56.98 -3.03** -3.42** -3.78** -0.77** -0.81** -0.84** 0.02 0.03** 0.03**
IC249505 -42.98** -58.56* 49.37 1.96** 2.84** 3.39** -0.14 -0.24** -0.24** -0.03 -0.04** -0.04**
SE 16.37 27.94 28.65 0.02 0.02 0.02 0.09 0.03 0.03 0.002 0.00 0.001
1540
ANITA PEDAPATI et al.,
favourable genes for Shoot dry weight is present in IC249505.
Among the lines, NS537, EC162516, IC249511, EC241148,
IC249513 and EC635525 exhibited significant positive gca
effects. Whereas, among testers EC164654 recorded positive
gca effect for root dry weight. Under 10 DII among the lines,
IC249511, EC162516 and NS537 recorded significant positive
gca effects while, among the testers positive significant gca
effect was exhibited by EC164654 thus indicating their good
general combining ability for root dry weight. Under 15 DII
among the lines, IC249511, EC162516 and NS537 recorded
significant positive gca effects. Among the testers positive
significant gca effect was exhibited by EC164654, thus
indicating their good general combining ability for root dry
weight.
Each and every line exhibited significant positive and negative
gca effect except IC249153. In this experiment, none of the
testers are significant for RDW/SDW. Under 10 DII among the
lines, EC164665, IC249511 and EC165952 recorded
significant positive gca effects. Among the testers positive
significant gca effect was exhibited by IC249503. Under 15
DII among the lines, EC164665, IC249511 and EC165952
recorded significant positive gca effects while, among the
testers positive significant gca effect was exhibited by IC249503
for RDW/SDW.
All the lines and testers are highly significant in both positive
and negative gca effect for stomatal diffusive resistance analysis.
Under 10 DII among the lines, IC249513, EC168096 and
EC164665 recorded significant positive gca effects while,
among the testers positive significant gca effect was exhibited
by IC249505 (0.18) for stomatal diffusive resistance. Under
15 DII among the lines, IC249513, EC168096 and EC164665
recorded significant positive gca effects while, among the
testers positive significant gca effect was exhibited by IC249503
for stomatal diffusive resistance.
Under 10 DII among the lines, EC310301, EC635525 and
EC162600 are judged as good general combiners for relative
water content while, in testers positive significant gca effect
was exhibited by IC249505 for relative water content. The
lines, EC310301, EC162600 and EC635525 recorded
significant positive gca effects. Among the testers positive
significant gca effect was exhibited by IC249505 for relative
water under 15 DII.
The highest significant positive gca effect was noticed in
EC162516, EC168096, EC164677 and EC635525 for leaf
area. Among the testers positive significant gca effects were
exhibited by EC164654 and IC249505. Under 10 DII among
the lines, EC164677, EC162516, EC168096 recorded
significant positive gca effects whereas, in testers positive
significant gca effect was exhibited by IC249505 for leaf area.
Under 15 DII among the lines, EC164677, EC162516 and
EC168096 recorded significant positive gca effects. Among
the testers positive significant gca effect was exhibited by
IC249505 thus indicating their good general combining ability
for leaf area.
For the trait, specific leaf weight comparing the gca effects of
lines, it was evident that the only two lines viz., NS537 and
EC162600 expressed positive and significant gca effects
whereas, in tester, IC249503 exhibited significant and positive
Table 3: Estimates of gca effects for lines and testers for stomatal diffusive resistance (sec/cm), relative water content, leaf area (sq.cm) and specific leaf weight (mg/sq.cm) traits in tomato
under irrigation (control) and drought stress (10 and 15 days irrigation interval) conditions
Source Stomatal diffusive resistance (sec/cm) Relative water content (%) Leaf area (sq.cm) Specific leaf weight (mg/sq.cm)
Control 10 days 15 days Control 10 days 15 days Control 10 days 15 days Control 10 days 15 days
EC251578 -3.69** -3.66** -3.39** -7.71** -8.84** -7.82** -14.58** -13.77** -15.17** -2.58 -9.41 30.98
NS537 -2.02** -2.03** -1.91** -9.11** -9.71** -9.83** -15.61** -15.15** -14.86** 96.42** 43.84 60.95
EC162516 0.36** 0.36** 0.19 1.65** 2.47** 1.95** 43.76** 44.09** 44.37** -73.16* -94.04* -114.46*
EC164845 -2.57** -2.62** -2.70** -0.33 0.52 -0.61 -16.82** -17.00** -16.70** -32.19 -22.06 -59.44
IC249512 -3.35** -3.29** -2.76** -9.87** -9.22** -9.59** -8.25** -7.93** -7.98** 9.10 7.13 20.56
EC165952 0.25** 0.26** 0.16 -2.03** -1.94** -2.20** -20.06** -19.61** -18.83** -1.08 17.61 11.80
EC164665 2.18** 2.25** 2.27** 6.89** 6.12** 6.23** -22.21** -22.69** -22.09** -91.82** -66.50 -74.39
IC249511 -1.87** -1.82** -1.99** -3.30** -3.36** -3.45** -23.67** -24.07** -24.44** 15.03 -77.84 -87.41
EC168096 3.94** 3.84** 3.89** -7.75** -7.72** -7.51** 38.83** 38.25** 38.54** -9.95 -7.47 20.32
EC164677 -1.85** -1.75** -1.81** -0.24 -1.24** -0.61 51.48** 52.98** 53.15** 40.39 104.99* 104.66*
EC162600 2.10** 1.89** 1.96** 8.41** 8.75** 9.16** -3.36** -3.73** -3.46** 73.71* 6.41 -11.58
EC310301 -0.72** -0.79** -0.82** 9.98** 10.76** 9.52** -1.87** -2.45** -3.15** 15.02 -4.38 -34.06
EC635525 0.32** 0.46** 0.23** 8.81** 9.17** 9.12** 10.66** 10.61** 10.23** -75.99** -64.06 31.38
IC249513 4.96** 4.92** 4.82** 3.25** 2.58** 3.63** 1.30 0.20 -0.11 -10.25 108.91* -10.26
EC241148 1.95** 1.98** 1.86** 1.35** 1.66** 2.02** -19.60** -19.73** -19.51** 47.35 56.86 110.96*
SEi 0.06 0.04 0.09 0.28 0.39 0.41 0.29 0.11 0.12 24.91 37.41 45.73
EC164654 -0.47** -0.20** 0.05 -0.70** -0.64* -1.01** 2.65** 1.17** -0.37** -37.15** 4.19 61.19**
IC249503 -0.10* 0.18** 0.49** -5.33** -5.28** -4.97** -2.99** -4.31** -5.78** 21.06** 46.38** 115.02**
IC249505 0.58** 0.02 -0.54** 6.02** 5.92** 5.97** 0.34* 3.14** 6.15** 16.09 -50.57** -176.21**
SE 0.02 0.02 0.03 0.11 0.15 0.15 0.11 0.04 0.05 9.42 14.14 17.28
1541
COMBINING ABILITY ANALYSIS FOR YIELD AND PHYSIOLOGICAL DROUGHT
gca effect. Under 10 DII among the lines, IC249513, EC164677
and EC241148 recorded significant positive gca effects.
Among the testers positive significant gca effect was exhibited
by EC164654 for specific leaf weight. Under 15 DII among
the lines, EC241148 and EC164677 recorded significant
positive gca effects while, in testers positive significant gca
effect was exhibited by IC249503 for specific leaf weight. From
the studies on gca effects and their relative performance, it
may be said that all the desirable characters were not present
in any one single parent.
Based on combining ability results, the genotypes EC251578,
IC249512, EC162516, EC249503 and EC164654 recorded
high positive gca effects. IC249512, EC164845, EC249505
and EC164654 are ideal choice for yield under stressed
condition. IC249512 was good performer for most of the traits
in both irrigated and stressed conditions. Besides high yield,
IC249512 is a very poor performer for stomatal diffusive
resistance and shoot dry weight under irrigated conditions.
Three parents EC162516, EC249505 and EC168096 are
identified as good general combiners with high yield potential
in drought environment. So, these lines are reliable for further
drought tolerance breeding.
Specific combining ability
The SCA effects for hybrids pertaining to different traits are
given in Table 4 and 5. In the present study, best cross
combinations involved good x good, good x poor and even
poor x poor SCA effects. The SCA effects signify the role of
non-additive gene action in the expression of a trait and this is
due to dominance variance and epistatic variances. It shows
the highly specific combining abilities leading to the higher
performance of some specific cross combinations and that is
the reason why it is related to a particular cross. High SCA
effects may arise not only in crosses involving high combiners
but also in those involving low combiners.
SCA effects also differed according to the stress and non-
stress environments. The higher positive sca effects were
exhibited by EC164845 X IC249505. Under stringent
irrigation conditions (10 DII) the sca effects IC249512 X
IC249503 recorded highest sca effects. In case of 15 DII, the
sca effects significant positive sca effects obtained in EC164845
X IC249505 for fruit yield per plant. For shoot dry weight the
sca effects ranged from -19.97 (IC249511 X IC249503) to
12.98 (IC249511 X IC249505). The higher positive sca effects
were exhibited by IC249511 X IC249505. Under stringent
irrigation conditions (10 DII) the sca effects ranged from -19.92
(IC249511 X IC249503) to 12.96 (IC249511 X IC249505).
Twenty one crosses expressed positive sca effects viz.
IC249511 X IC249505 followed by EC164677 X IC249503
and IC249511 X EC164654. At 15 DII, the sca effects ranged
from -19.96 (IC249511 X IC249503) to 12.96 (IC249511X
IC249505).
The sca effects for root dry weight were positive significant in
EC164665 X IC249503. The sca effects ranged from -8.53
(EC241148 X IC249503) to 15.34 (EC164665 X IC249503).
Under stringent irrigation conditions (10 DII) the sca effects
ranged from -8.84 (IC249511 X IC249503) to 15.43
(EC164665 X IC249503). At 15 DII, The significant positive
sca effects obtained in EC164665 X IC249503 (15.63).
The higher positive sca effects for RDW/SDW were exhibited
by EC164665 X IC249503 followed by EC241148 X
EC164654 and IC249513 X IC249505. Under stringent
irrigation conditions (10 DII) at 15 DII, the sca effects ranged
from -0.51 (EC164665 X IC249505) to 0.83 (EC164665 X
IC249503). Estimates of the SCA effects for Stomatal diffusive
resistance are presented in Table 4. The higher positive sca
effects were exhibited by EC168096 X IC249503 followed by
EC635525 X IC249505 and NS537 X IC249505. Under
stringent irrigation conditions (10 DII) the highest sca effects
showed in EC168096 X IC249503 (5.14) followed by
EC635525 X IC249505 and IC249513 X EC164654. At 15
DII, the sca effects ranged from -2.72 (EC168096 X IC249505)
to 5.26 (EC168096 X IC249503). The significant negative sca
effects obtained in 14 crosses, whereas thirteen crosses
expressed positive sca effects viz. EC168096 X IC249503
followed by EC635525 X IC249505 and IC249513 X
EC164654.
EC164665 X IC249503 shows significant positive sca for
relative water content in irrigation as well as stress conditions.
The estimates of sca effects were positive significant for the
trait leaf area were exhibited by EC310301 X IC249503 under
normal and stringent irrigation conditions (10 DII). For specific
leaf weight the higher positive sca effects were exhibited by
IC249511 X IC249503 over normal irrigation condition. Under
stringent irrigation conditions (10 DII) only one cross expressed
positive sca effects viz. EC164677 X IC249503. The highest
significant positive sca effect was recorded by only in one
cross at 15 days irrigation condition. The high SCA effects of
these crosses may be due to complementary type of gene
effects.
DISCUSSION
The parents differed markedly in their ability to yield under
moisture stress conditions. For fruit yield per plant, the top
five crosses EC310301 X EC164654 (251.33), EC 251578 X
EC 164654 (304.82), IC249512 X IC249503 (381.70),
EC162516 X IC249503 (468.85) and EC164845 X IC249505
(571.92) having high and positively significant sca effects under
irrigated normal condition in the order of merit mentioned.
Whereas, in stressed condition IC249512 X IC249503
(258.06), IC249512 X EC164654 (260.16), EC310301 X
EC164654 (314.06), EC162516 X IC249505 (388.34) and
EC164845 X IC249505 (469.54) having high and positively
significant sca effects.
The analysis of quantitative inheritance was also an equally
important objective to gain knowledge regarding the nature
and magnitude of gene action, which has prime bearing on
choice of most appropriate and efficient breeding procedure.
Information regarding nature of gene action will be highly
helpful in the development of efficient breeding programme.
General combining ability is attributed to additive × additive
gene action and is fixable in nature. On the other hand, specific
combining ability is attributed to non-additive gene action
which may be due to dominance or epistasis or both and is
non-fixable nature. The presence of non-additive genetic
variance is the primary justification for initiating the hybrid
breeding programme. Combining ability analysis, therefore,
was done to generate information on gca effects of parents
1542
Table 4: Estimates of sca effects for lines and testers for fruit yield (g), shoot dry weight (g), root dry weight (g) and RDW/SDW in tomato under irrigation (control) and drought stress
(10 and 15 days) conditions
Source Fruit yield per plant (g) Shoot dry weight (g) Root dry weight (g) RDW/SDW
Control 10 days 15 days Control 10 days 15 days Control 10 days 15 days Control 10 days 15 days
EC251578 X EC 164654 304.82** 97.64 59.00 0.66** 0.78** 0.61** -1.45** -1.48** -1.73** -0.03* -0.03* -0.03*
EC251578 X IC249503 66.67 161.45 -42.99 0.62** 0.71** 0.80** 0.49 0.56** 0.88** -0.02 -0.03* -0.02*
EC251578 X IC249505 -371.48** -259.09* -16.01 -1.29** -1.49** -1.40** 0.95** 0.92** 0.85** 0.05** 0.05** 0.06**
NS537 X EC164654 49.25 149.57 -45.36 2.03** 2.12** 1.91** 2.53** 2.14** 2.08** 0.02 0.02 0.02*
NS537 X IC249503 -122.29* -119.38 35.82 -2.06** -2.01** -1.93** 1.99** 2.02** 2.05** 0.01 0.01 0.00
NS537 X IC249505 73.04 -30.19 9.54 0.04 -0.11 0.03 -4.53** -4.16** -4.13** -0.03* -0.02 -0.02*
EC162516 X EC164654 -393.04** -312.35** -276.43 0.25** 0.81** 0.90** -4.26** -4.52** -4.46** -0.06** -0.07** -0.07**
EC162516 X IC249503 468.85** 18.30 -111.90 2.36** 1.72** 1.96** 4.43** 4.48** 4.49** 0.03* 0.04** 0.03*
EC162516 X I C249505 -75.81 294.05* 388.34** -2.61** -2.54** -2.86** -0.18 0.04 -0.03 0.03* 0.03* 0.04**
EC164845 X EC164654 -225.24** -200.09 -208.66 -0.17** -0.31** -0.38** -0.54 -0.79** -0.68** 0.00 -0.01 0.00
EC164845 X IC249503 -346.68** -236.28* -260.88* 1.13** -0.28** -0.15 0.13 0.30* 0.04 -0.03* -0.02 -0.03*
EC164845 X IC249505 571.92** 436.37** 469.54** -0.97** 0.58** 0.53** 0.41 0.49** 0.64** 0.03* 0.02 0.03*
IC249512 X EC164654 124.67* -49.07 260.16* 1.44** 1.10** 0.86** -1.22** -1.21** -1.43** -0.04** -0.04** -0.04**
IC249512 X IC249503 381.70** 598.26** 258.06* 4.13** 5.06** 5.29** 0.41 0.38* 0.43** -0.05** -0.06** -0.07**
IC249512 X IC249505 -506.37** -549.19** -518.22** -5.57** -6.17** -6.15** 0.81* 0.84** 1.01** 0.09** 0.10** 0.11**
EC165952 X EC164654 93.66 89.72 188.04 2.38** 2.72** 2.62** 4.11** 3.85** 3.90** 0.09** 0.09** 0.10**
EC165952 X IC 249503 -10.97 87.20 2.41 -0.14** -0.38** -0.19 -6.24** -6.05** -6.23** -0.19** -0.19** -0.21**
EC165952 X IC249505 -82.69 -176.92 -190.45 -2.24** -2.35** -2.44** 2.14** 2.19** 2.33** 0.09** 0.10** 0.11**
EC164665 X EC164654 -25.14 68.68 -33.21 -3.98** -3.91** -4.00** -7.12** -7.35** -7.55** -0.25** -0.28** -0.32**
EC164665 X IC249503 110.02 89.39 178.10 1.90** 2.13** 2.01** 15.34** 15.43** 15.63** 0.67** 0.74** 0.83**
EC164665 X IC249505 -84.88 -158.07 -144.88 2.09** 1.78** 1.99** -8.22** -8.08** -8.07** -0.42** -0.46** -0.51**
IC249511 X EC164654 240.35** -27.90 121.33 6.99** 6.95** 7.00** 3.11** 5.14** 5.16** -0.01 0.02 0.03*
IC249511 X IC249503 -30.92 -50.74 -14.16 -19.97** -19.92** -19.96** -7.79** -8.84** -8.85** 0.02 0.01 0.00
IC249511X IC249505 -209.43** 78.64 -107.17 12.98** 12.96** 12.96** 4.69** 3.70** 3.69** -0.01 -0.03** -0.03*
EC168096 X EC164654 -14.16 -136.75 -114.20 -2.04** -3.29** -3.30** 0.73* 0.94** 1.02** 0.05* 0.08** 0.09**
EC168096 X IC249503 -35.64 127.06 116.94 3.93** 4.70** 4.89** -2.13** -2.03** -2.23** -0.12 -0.13** -0.15**
EC168096 X IC249505 49.81 9.69 -2.74 -1.89** -1.41** -1.59** 1.40** 1.09** 1.21** 0.06** 0.05** 0.06**
EC164677 X EC164654 -134.73* 130.82 -147.65 -6.02** -5.98** -4.62** -1.22** -0.63** -0.93** 0.03* 0.06** 0.03*
EC164677 X IC249503 27.27 -101.76 83.58 7.98** 8.01** 7.65** 0.50 0.07 0.47** -0.07** -0.10** -0.08**
EC164677 X IC249505 107.46 -29.06 64.07 -1.96** -2.04** -3.03** 0.72* 0.56** 0.46** 0.04* 0.04** 0.05**
EC162600 X EC164654 -101.81 25.40 -79.80 5.26** 5.01** 5.68** 0.47 0.17 0.41** 0.00 -0.01 0.00
EC162600 X IC249503 79.83 -10.58 51.43 -0.56* 0.09 -1.18** 0.05 0.19 0.11 -0.02 -0.03** -0.03*
EC162600 X IC249505 21.97 -14.82 28.38 -4.70** -5.10** -4.50** -0.52 -0.36* -0.52** 0.02 0.04** 0.04**
EC310301 X EC164654 251.33** 229.90* 314.06** -2.36** -2.39** -2.21** -0.22 -0.82** -0.98** 0.04** 0.02 0.01
EC310301 X IC249503 -486.57** -546.23** -463.00** 0.83** 0.67** 0.88** 0.90** 1.14** 1.24** 0.01 0.02 0.03*
EC310301 X IC249505 235.24** 316.33* 148.95 1.53** 1.73** 1.33** -0.69* -0.32 -0.26* -0.05** -0.04** -0.04**
EC635525 X EC164654 -121.89* -96.20 11.32 -3.65** -3.30** -4.37** 1.57** 1.73** 1.27** 0.04** 0.04** 0.04**
EC635525 X IC249503 -76.65 1.08 -90.79 -0.33** -0.38* -0.42** 2.70** 2.47** 3.15** 0.02 0.01 0.02*
EC635525 X IC249505 198.54** 95.12 79.48 3.98** 3.68** 4.79** -4.28** -4.21** -4.42** -0.07** -0.06** -0.07**
IC249513 X EC164654 -204.03** -74.73 -65.43 -1.44** -1.10** -1.03** -3.03** -3.15** -2.32** -0.04** -0.05** -0.03*
IC249513 X IC249503 41.00 -3.86 109.31 -0.34** -0.85** -0.97** -2.26** -1.88** -2.30** -0.06** -0.05** -0.07**
IC249513 X IC249505 163.03* 78.59 -43.88 1.78** 1.95** 2.00** 5.30** 5.03** 4.62** 0.10** 0.10** 0.10**
EC241148 X EC164654 155.95** 105.35 16.85 0.65** 0.77** 0.35** 6.54** 5.97** 6.25** 0.15** 0.14** 0.16**
EC241148 X IC249503 -65.62 -13.90 148.10 0.54** 0.73** 1.32** -8.53** -8.22** -8.87** -0.21** -0.22** -0.25**
EC241148 X IC249505 -90.33 -91.46 -164.95 -1.18** -1.50** -1.67** 1.99** 2.26** 2.62** 0.07** 0.08 0.09**
SE 61.260 104.530 107.180 0.070 0.060 0.090 0.330 0.120 0.070 0.010 0.004 0.004
ANITA PEDAPATI et al.,
1543
Table 5: Estimates of sca effects for lines and testers for stomatal diffusive resistance (sec/cm), relative water content, leaf area (sq.cm) and specific leaf weight (mg/sq.cm) in tomato under
irrigation (control) and drought stress (10 and 15 days) conditions
Source Stomatal diffusive resistance (sec/cm) Relative water content (%) Leaf area (sq.cm) Specific leaf weight (mg/sq.cm)
Control 10 days 15 days Control 10 days 15 days Control 10 days 15 days Control 10 days 15 days
EC251578 X EC 164654 0.20* 0.20* -0.09 -3.93** -5.63** -5.35** -1.95** -1.42** -4.51** 23.71 11.30 -18.48
EC251578 X IC249503 -0.33** -0.30** -0.44** 1.09** 1.70* 2.56** -1.37** -0.98** 0.76 4.26 -10.73 55.34
EC251578 X IC249505 0.13 0.11 0.53** 2.85** 3.93** 2.79** 3.31** 2.41** 3.75** -27.97 -0.56 -36.86
NS537 X EC164654 -0.43** -0.57** -0.45** 3.12** 4.49** 4.97** 1.00* -0.11 0.16 48.06 65.06 108.09
NS537 X IC249503 -0.94** -0.69** -0.92** 5.68** 3.62** 3.24** -6.38** -4.71** -4.62** -141.07** -150.43** -159.37**
NS537 X IC249505 1.37** 1.26** 1.37** -8.80** -8.12** -8.21** 5.38** 4.82** 4.46** 93.01* 85.37 51.28
EC162516 X EC164654 0.93** 0.97** 1.17** -0.24 -1.61* -3.77** 10.66** 10.66** 10.88** -30.52 -88.55 -72.48
EC162516 X IC249503 1.12** 0.81** 0.77** -3.42** -1.24 0.28 6.16** 6.15** 6.25** 13.77 30.68 -9.66
EC162516 X IC249505 -2.04** -1.79** -1.94** 3.66** 2.85** 3.50** -16.82** -16.82** -17.13** 16.76 57.87 82.15
EC164845 X EC164654 0.23* 0.18* 0.44** 2.11** 4.04** -0.17 -7.70** -8.31** -8.14** -33.05 -72.58 -75.63
EC164845 X IC249503 -0.30** -0.15 -0.27* -2.58** -3.54** -0.43 -7.97** -7.89** -7.73** 21.40 50.61 11.93
EC164845 X IC249505 0.07 -0.03 -0.17 0.47 -0.50 0.60 15.67** 16.20** 15.87** 11.65 21.97 63.70
IC249512 X EC164654 0.11 -0.03 -0.63** 0.92* 1.71* 1.48* 2.49** 2.88** 3.29** -52.41 -87.77 -53.78
IC249512 X IC249503 0.32** 0.24** 0.67** 4.06** 3.90** 3.86** 4.77** 4.16** 3.47** 73.84 86.73 62.33
IC249512 X IC249505 -0.43** -0.21** -0.04 -4.99** -5.61** -5.35** -7.26** -7.05** -6.75** -21.44 1.04 -8.55
EC165952 X EC164654 0.06 0.25** 0.28* 0.07 1.21* 0.18 4.75** 4.52** 5.59** 116.44** 101.90 147.42
EC165952 X IC 249503 -0.36** -0.29** -0.24* 2.86** 1.83* 2.71** -5.70** -5.25** -5.59** -110.07** -97.53 -152.85*
EC165952 X IC249505 0.31** 0.04 -0.04 -2.93** -3.05** -2.88** 0.95* 0.73** 0.00 -6.37 -4.36 5.43
EC164665 X EC164654 0.01 0.03 0.06 -4.14** -5.49** -4.23** -2.29** -3.43** -2.52** 112.02** 77.63 94.27
EC164665 X IC249503 -0.20* -0.07 -0.18 5.71** 6.29** 5.01** 2.29** 2.94** 2.77** -62.61 -23.22 -51.81
EC164665 X IC249505 0.18 0.03 0.12 -1.57** -0.80 -0.78 0.00 0.49* -0.25 -49.40 -54.41 -42.46
IC249511 X EC164654 0.66** 0.62** 0.60** -1.77** -1.33* -1.49* -3.32** -4.24** -5.42** -47.10 -4.91 4.05
IC249511 X IC249503 -0.87** -1.02** -0.92** 0.46 -0.04 0.10 3.85** 4.29** 5.00** 191.43** 36.03 13.47
IC249511 X IC249505 0.20* 0.40** 0.32* 1.31** 1.37* 1.39* -0.53 -0.05 0.42* -144.33** -31.12 -17.51
EC168096 X EC164654 -2.47** -2.57** -2.55** -1.23** 0.10 1.41* 5.77** 6.49** 6.77** -16.79 -24.38 14.36
EC168096 X IC249503 5.10** 5.14** 5.26** 1.17** 0.11 -1.27 3.15** 1.94** 1.97** 27.08 16.92 1.83
EC168096 X IC249505 -2.62** -2.57** -2.72** 0.07 -0.21 -0.14 -8.93** -8.43** -8.74** -10.29 7.46 -16.20
EC164677 X EC164654 0.04 0.02 0.14 1.46** -0.10 0.22 9.10** 11.91** 12.01** -103.37** -140.26** -201.24**
EC164677 X IC249503 -0.22* -0.36** -0.29* 2.22** 2.84** 3.25** 2.43** 1.34** 1.42** 153.91** 235.23** 291.61**
EC164677 X IC249505 0.18 0.34** 0.16 -3.68** -2.74** -3.47** -11.53** -13.25** -13.43** -50.54 -94.97 -90.37
EC162600 X EC164654 0.45** 0.47** 0.64** 1.93** 3.29** 2.92** -7.07** -6.59** -6.38** 37.72 17.61 1.67
EC162600 X IC249503 -0.85** -0.88** -1.07** -1.55** -2.63** -1.99** -1.31** -1.00** -0.90** 57.29 -10.31 -16.43
EC162600 X IC249505 0.40** 0.40** 0.44** -0.38 -0.66 -0.93 8.38** 7.59** 7.28** -95.01* -7.30 14.76
EC310301 X EC164654 0.21** 0.29** 0.15 1.43** 1.23* 1.54* -16.92** -16.87** -16.77** -38.72 -18.98 -59.76
EC310301 X IC249503 -0.31** -0.32** -0.29* -4.62** -3.70** -5.29** 19.56** 19.67** 18.91** -16.96 -14.50 1.54
EC310301 X IC249505 0.10 0.03 0.14 3.19** 2.47** 3.74** -2.64** -2.80** -2.14** 55.67 33.47 58.22
EC635525 X EC164654 -1.78** -1.70** -1.82** 2.33** 0.89 2.84** -8.54** -8.72** -9.90** 51.09 76.95 197.67
EC635525 X IC249503 -2.22** -2.37** -2.29** -3.63** -1.82** -3.70** -0.11 -0.47 0.43* -85.97 -70.10 -90.49
EC635525 X IC249505 3.99** 4.07** 4.11** 1.30** 0.93 0.86 8.65** 9.19** 9.48** 34.88 -6.85 -107.18
IC249513 X EC164654 1.36** 1.36** 1.51** -0.89* -1.31* 0.49 16.06** 14.53** 15.32** -27.02 72.56 -33.93
IC249513 X IC249503 0.03 0.11 0.13 -3.89** -4.21** -5.08** -23.29** -23.07** -24.20** -54.07 7.33 -8.51
IC249513 X IC249505 -1.39** -1.46** -1.65** 4.78** 5.51** 4.59** 7.23** 8.54** 8.87** 81.08 -79.89 42.44
EC241148 X EC164654 0.43** 0.47** 0.55** -1.14** -1.50* -1.03 -2.05** -1.31** -0.37 -40.08 14.44 -52.22
EC241148 X IC249503 0.01 0.15 0.10 -3.57** -3.11** -3.27** 3.94** 2.87** 2.07** -72.22 -86.72 51.06
EC241148 X IC249505 -0.44** -0.62** -0.64** 4.71** 4.61** 4.30** -1.88** -1.56** -1.70** 112.30** 72.28 1.16
SE 0.080 0.060 0.120 0.400 0.560 0.570 0.410 0.160 0.170 35.23 52.910 64.670
COMBINING ABILITY ANALYSIS FOR YIELD AND PHYSIOLOGICAL DROUGHT
1544
and sca effects of crosses which would help in selection of
better parents and cross combinations for their further use in
hybrid breeding programme. This will also provide the
information regarding the type and magnitude of gene action,
which will help in choice of the breeding method to be
employed for the improvement of desired traits (Muhammad
et al., 2009).
Combining ability effects reveal the genetic worth of parents
and hybrids. The gca effects are fixable, while sca effects are
non-fixable. In the present investigation, combining ability
analysis revealed that there were significant differences in the
combining ability of parents and crosses for almost all the
growth, earliness, yield related traits and quality parameters
under consideration. The degree and direction of combining
ability effects varied greatly for different traits and genotypes.
General combining ability helps in the selection of suitable
parents (good general combiners) for hybridization. There were
significant differences in the general combining ability of
parents for all the growth, earliness, yield related traits and
quality parameters under study. High gca effects are related to
additive gene effects or additive × additive effects, which
represent the fixable genetic components of variance, as also
pointed out by Griffing (1956). The high estimates of gca effects
as observed for different attributes of economic importance
may be useful for sorting out outstanding parents with
favorable alleles for different components of yield. It may,
therefore, be suggested that the parents with high gca effects
for a particular character may be used in hybridization
programme for the improvement of that character. These
findings are in consonance with the findings of Pandey et al.
(2006), Katkar et al., (2012). EC164665 X EC164654
combination gives poor X poor GCA effect due to non-additive
gene interaction and non-fixable genetic component for total
yield per plant. This indicated possibly to obtained desirable
transgressive segregants and hybrid vigour from such crosses
by adopting cycle selection or biparental breeding programme
(Ravindra Kumar et al., 2013).
CONCLUSION
The superior general combiners viz., EC251578, IC249512,
EC162516, EC249503 and EC164654 are recommended for
use in breeding programmes to generate genetic variability in
desirable direction for effective selection to improve the
respective traits. Besides high yield, IC249512 is a very poor
performer for stomatal diffusive resistance and shoot dry weight
under irrigated conditions. High performance of these crosses
may be attributed to additive × additive (high × high), additive
× dominance (high × low) or dominance × dominance (low
× low) epistatic interactions. Therefore, the best general
combiner from the parental lines and the best specific
combiners among the crosses may be selected for better
parents and hybrids respectively for improvement of traits
especially drought tolerant and fruit yield in tomato cultivation
under moisture stress conditions.
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productivity and better processing qualities. Sabrao J. Breeding and
Genetics. 44: 302-321.
ANITA PEDAPATI et al.,
... Exotic genotypes produced higher number. of fruits/cluster and number of fruits/plant have great potential to be used in breeding program to improve yield. A wider range of phenotypic variability observed in yield coupled with the high heritability values suggests genetic gain by using these genotypes in the breeding programs aimed at higher yield [25][26][27][28][29]. Allround produced more than 70 fruits per plant, but its yield was found to be less because of the smaller size of fruits ( Table 1). Use of this genotype to increase the number of fruits per plant can be very effective. ...
... A positive and strong correlation was observed in most of the traits, especially correlation of morphological and yield related traits. Our results are supported by the findings of other researchers [27,30,31] who reported strong association among morphological and yield related traits. Path analyses dissects the correlation into direct and indirect effects. ...
... Most of the time that association is attributed to indirect effects. The direct and indirect effects of various yield traits can help to select the most desirable characteristics [27,30,31]. ...
Article
Full-text available
Tomato production in Pakistan faces significant problems of low yields due to various biotic and abiotic stresses primarily because of a narrow genetic base of the cultivars being used. Therefore, Introduction and evaluation of the exotic tomato germplasm has become necessary to acquire elite material to develop future breeding programs. To this end, the present study was conducted for the phenotypic characterization of twenty exotic tomato genotypes along with two locally grown cultivars in semi-arid subtropical climate. Data were collected for morphological, fruit quality and fruit yield traits. A significant (p<0.05) phenotypic variation was observed for all the studied traits. Maximum yield was obtained from “Rober” i.e., 1508.31 g per plant. The maximum shelf life was observed in the Cromco, with the least weight loss (2.45%) and loss in the firmness of fruit (22.61%) in 4 days. Correlation analyses revealed a strong genetic association among morphological and yield related traits. High estimates of the heritability (ranged from 79.77% to 95.01% for different traits), along with a high genetic advance (up to 34%) showed the potential usefulness of these traits and genotypes to develop breeding programs to improve the tomato yield and fruit quality.
... their per se performance are being furnished below. This result getting support from the finding ofHannan et al. (2007b),Kumar et al. (2013),Pedapati et al. (2013) andDagade et al (2015) in tomato crop. For number of fruits per plant the highest significant positive value (8.823) for SCA effect was recorded in H-24 x Sel-7 followed by Punjab Chhuhara x Sel-7 (7.137), Pant T-3 x Azad T-5 (6.346) and Pant T-3 x Sel-7 (6.262). ...
Research
Full-text available
Combining ability for yield and nutritional quality traits in tomato were studied by involving 28 cross combinations obtained from crossing 8 diverse lines in diallel mating fashion. Based on GCA effects of parents, the varieties Pant T-3, Arka Alok and Sel-7 were good general combiners for most of the traits under study. The crosses viz., Pant T-3 x H-24 (1.052%), Arka Meghali x Punjab Chhuhara (0.768%) and H-88-78-1 x Azad T-5 (0.768%) were found to be high positive specific combining ability effect for yield per plant. For quality traits, the crosses Arka Me-ghali x Punjab Chhuhara and H-24 x Sel-7 were also superior specific combiner for number of seeds per fruit and ascorbic acid, while cross Punjab Chhuhara x H-88-78-1 was superior specific combiner for number of seeds per fruit (24.165%), yield per plant (0.677%) and titrable acidity (0.183%). These elite hybrids may be tested for yield and other quality traits under different agro-climatic conditions for commercial exploitation of hybrid vigour.
... Information pertaining to different types of gene action, relative magnitude of genetic variance, and combining ability estimates are important and vital parameters to mould the genetic makeup of tomato crop. This important information could prove an essential strategy to tomato breeders in the screening of better parental combinations for further enhancement (Pedapati et al., 2013). Exploitation of heterosis is primarily dependent on the screening and selection of available germplasm that could be produced by better combinations of important agronomic characters (Hannan et al., 2007). ...
Research
Full-text available
A study was conducted on 8×8 diallel set of tomato excluding reciprocals to find out the combining ability for yield and its contributing traits. The magnitudes of variance due to general as well as specific combining ability were highly significant. Among parents, Arka Alok and Arka Meghali were found positive significant good general combiner for yield and some of the yield related traits studied. The hybrids viz. Pant T-3 x H-24 (1.052), Arka Meghali x Punjab Chhuhara (0.768), H-88-78-1 x Azad T-5 (0.768), Punjab Chhuhara x H-88-78-1 (0.677), Punjab Chhuhara x Azad T-5 (0.671) had significant SCA effects for yield and were suggested for the exploitation of heterosis.
... Selection of genetically diverse parental lines is necessary in any hybridization programme to develop the potential germplasm with all the desirable traits. (Pedapati et al., 2013 andSingh et al., 2013). At present in tomato, exploitation of heterosis by use of F 1 hybrids is getting more and more importance (Baishya et al., 2001). ...
... Selection of genetically diverse parental lines is necessary in any hybridization programme to develop the potential germplasm with all the desirable traits. (Pedapati et al., 2013 andSingh et al., 2013). At present in tomato, exploitation of heterosis by use of F 1 hybrids is getting more and more importance (Baishya et al., 2001). ...
... Selection of genetically diverse parental lines is necessary in any hybridization programme to develop the potential germplasm with all the desirable traits. (Pedapati et al., 2013 andSingh et al., 2013). At present in tomato, exploitation of heterosis by use of F 1 hybrids is getting more and more importance (Baishya et al., 2001). ...
... Information pertaining to different types of gene action, relative magnitude of genetic variance, and combining ability estimates are important and vital parameters to mould the genetic makeup of tomato crop. This important information could prove an essential strategy to tomato breeders in the screening of better parental combinations for further enhancement (Pedapati et al., 2013). Exploitation of heterosis is primarily dependent on the screening and selection of available germplasm that could be produced by better combinations of important agronomic characters (Hannan et al., 2007). ...
Article
Full-text available
A study was conducted on 8×8 diallel set of tomato excluding reciprocals to find out the combining ability for yield and its contributing traits. The magnitudes of variance due to general as well as specific combining ability were highly significant. Among parents, Arka Alok and Arka Meghali were found positive significant good general combiner for yield and some of the yield related traits studied. The hybrids viz. Pant T-3 x H-24 (1.052), Arka Meghali x Punjab Chhuhara (0.768), H-88-78-1 x Azad T-5 (0.768), Punjab Chhuhara x H-88-78-1 (0.677), Punjab Chhuhara x Azad T-5 (0.671) had significant SCA effects for yield and were suggested for the exploitation of heterosis.
Article
The present study was carried out in a private farm, Kaha city, Kalyobiya Governorate, Egypt during summer seasons of 2015 and 2016 to study the mean performance and heterosis for yield and fruit traits for six tomato cultivars, i.e. Tan Shit Star (p1), Real Stone (p2), Pearsone Imp (p3), Super marmande (p4), grown under normal irrigation and drought stress. This investigation was a half diallel F1 cross experiment to induce genetic variability by hybridization and evaluation and selection for best genotypes of tomato compared with the parents under drought conditions and normal irrigation. Two adjacent experiments were conducted. Where, the first experiment was irrigated every month (environment 1) and the second one was normally irrigated, i.e., every 2 week (environment 2). The data of the two experiments were subjected to proper statistical analysis of variance and estimate the mean performance of parents and their crosses. Data indicated that the P6 gave the highest values for total yield per plant under drought stress and combined analysis, respectively while the cross P1xP4 and P1xP6 expressed the highest values for total yield per plant under drought stress, normal irrigation and combined analysis. Moreover the highest number of fruits was detected for the parent P5 and the cross P5xP6 in drought condition, normal irrigation and combined analysis. Three, three and two crosses expressed significant or highly significant and positive heterosis relative to mid parent for fruits number in drought condition, normal irrigation and combined analysis, respectively. Moreover, highly significant and positive better parent heterosis were detected in 3, 2 and 2 crosses in drought stress, normal irrigation and combined analysis, respectively. It was clear that the cross P1 x P4 expressed the highest desirable heterosis relative to mid parent and better parent in the two environments treatments and combined analysis of them.
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Tomato (Solanum lycopersicum L.) has the potential for improvement through heterosis breeding which can further be utilized for development of desirable recombinants. A 3 × 3, line × tester mating design was used to determine heterosis over better parent, combining ability and gene action for eleven characters in tomato. Preponderance of non-additive gene action was evident for control of all characters studied except TSS content of fruit for which both additive and non-additive gene actions were evident. Amongst the parental lines, 'CLN2498-D', 'CLN2762-A' and 'BCT-110' were the best general combiners for fruit yield and component characters along with good processing traits and thus could be used in tomato hybridization programs. Crosses showing high specific combining ability (SCA) for fruit yield involved parents showing high general combining ability (GCA) for numbers of fruit per flower cluster or numbers of fruit per plant or fruit weight or fruit diameter. The promising hybrids of the CLN2498-D x DVRT-2 and CLN2777-C x BCT-53 were selected on the basis of their performance per se; heterosis manifested in them and the SCA effects. These two hybrids could be used commercially for high yield. However, the cross CLN2498D x BCT-110 could be exploited for better processing qualities.
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This study investigates the effects of water stress on moisture content distribution at different soil layers (pot) and on morphological characters of tomato plants. Three treatments of moisture level were imposed, viz, 100%, 70% and 40% of the field capacity. Moisture content distribution was higher at the surface and decreased with increasing stress at all growth stages. Yield and related morphological characters responded better at 70% of the field capacity compared with other treatments. Keywords: Tomato; Water stress; Moisture content; Tomato yield; Yield component. © 2011 JSR Publications. ISSN: 2070-0237 (Print); 2070-0245 (Online). All rights reserved. doi:10.3329/jsr.v3i3.7000 J. Sci. Res. 3 (3), 677-682 (2011)
Article
Full-text available
Line x tester experiment was conducted to evaluate the performance of 30 hybrids along with 13 parents in tomato. Variance due to treatments, crosses and lines x testers was significant for days to fruiting, fruit weight, fruit length, fruit width, number of fruit per plant and yield per plant. The estimate of variance of gca, sca, their ratio and degree of dominance indicated preponderance of non-additive gene action for all the traits suggesting that selection might not be made in the early generations and recurrent selection with periodic intercrossing appeared to be the best method. Narrow sense heritability was low in all traits but moderate for fruit weight, while genetic advance was low to high in aforementioned traits. Contribution of lines towards the total variance was more than that of testers. Line x tester interactions contributed more in days to fruiting, number of fruit per plant and yield per plant than that of lines and testers. Based on mean performance and gca effects, line 88572 and UC-134 and tester Nagina were better for yield and its various components. Considering mean performance, sca effects and heterobeltiosis, three hybrids 88572 × Riogrande, Picdeneto × Riogrande and H-24 × Riogrande were superior for yield and recommended for further evaluation.
Article
Full-text available
Line x tester experiment was conducted to evaluate the performance of 30 hybrids along with 13 parents in tomato. Variance due to treatments, crosses and lines x testers was significant for days to fruiting, fruit weight, fruit length, fruit width, number of fruit per plant and yield per plant. The estimate of variance of gca, sca, their ratio and degree of dominance indicated preponderance of non-additive gene action for all the traits suggesting that selection might not be made in the early generations and recurrent selection with periodic intercrossing appeared to be the best method. Narrow sense heritability was low in all traits but moderate for fruit weight, while genetic advance was low to high in aforementioned traits. Contribution of lines towards the total variance was more than that of testers. Line x tester interactions contributed more in days to fruiting, number of fruit per plant and yield per plant than that of lines and testers. Based on mean performance and gca effects, line 88572 and UC-134 and tester Nagina were better for yield and its various components. Considering mean performance, sca effects and heterobeltiosis, three hybrids 88572 × Riogrande, Picdeneto × Riogrande and H-24 × Riogrande were superior for yield and recommended for further evaluation.
Data
Thirteen parental lines were crossed in line X tester fashion comprising 10 lines and 3 testers at vegetable farm Banaras Hindu University Varanasi to estimate combining ability in tomato for fruit yield, yield components and fruit quality traits. F 1 and parents were grown in towards four and half meters in randomized block design with three replications during winter-2010 involvement of both additive and non additive gene action was operated for the control of fruits per plant, fruit weight and average fruit weight. All the fruit quality characters like, total soluble solids (TSS), titratable acidity, ascorbic acid and lycopene of the fruit were governed by non additive gene action. In most of the traits, over-dominance was predominant. The analysis of components of genetic variance for yield components showed that the main part of genetic variance was due to additive effect. Estimation of general combining ability (GCA) for yield and earliness showed that Pant T-3 had the highest GCA for increasing yield and Punjab Upma had the highest GCA for both earliness and average fruit weight. Cross combination CO-3 X Azad T-5 exhibit significant specific combining ability (SCA) for the most of desirable traits among all cross combinations.
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A detailed examination of the concept of combining ability in relation to diallel crossing systems is made. Eight different analyses aro presented. 'l'hese result from a consideration of four different diallel crossing systems together wit.h two alternative assumptions with regard to the sampling nature of tho experimental material. A numerical example is given.
  • Roberto Gaxiola
Roberto Gaxiola 2006. Tomatoes Against Drought. www. Checkbiotech. org