| Research Article (Open access) |
|---|
ABSTRACT- Twenty two selection indices involving seed yield and six yield components were constructed using the
discriminatnt function technique. The efficiency of selection increased with the inclusion of more number of the characters
in the index. Selection indices were constructed adapting discriminant function which indicated that the maximum
genetic advance and relative efficiency can be obtained when seed yield was included as one of the characters in combination
with all other characters viz., plant height, days to 50% flowering, number of primary branches per plant, number of
secondary branches per plant, number of pods per plant and test weight. However higher relative efficiency was obtained
when a function yield was included as one of the component character in combination with number of pods per plant,
number of secondary branches per plant and test weight than to a function with all the character in combination with yield.
Key words- Pigeonpea, Genetic advance, Relative efficiency, Genotype
INTRODUCTION
Pigeonpea is the second important pulse crop of India
grown in around 4.5 m. ha with an average productivity of
700 kg per ha which is below world productivity of one
tonne per ha. Yield is a complex character and governed by
poly genes. Yield is subjected to environmental fluctuations
and the performance of individual plant is consequently is
not a reliable index of the genotype [1]. Study of
discriminant function for yield alone does not result in
expected yield. Success of selection would be enhanced by
use of selection techniques as it facilitates simultaneous
improvement of number of characters [2]. Selection index
is most widely used selection method which can be used for
more than one character. The superiority of index increases
with increasing number of traits under selection but
decreases with increasing differences in relative
importance. The superiority of selection index is maximum
when the traits considered are equally important.
MATERIAL AND METHODS
Twenty two genotypes received from all over India were
utilized for the study to formulate selection indices. The
material was raised in randomized block design during July
2014 at Regional Agricultural Research Station, Lam,
Guntur. A total 693.9 mm rainfall was received during
entire period of crop season. Crop was sown in the month
of July and harvesting was completed in the month of
February, 2015. The observations were recorded on five
competitive plants from each replication for plant height,
days to 50% flowering, number of primary branches,
number of secondary branches, number of pods per plant,
test weight and yield. The mean data was subjected to
analysis of variance and selection indices were formulated.
The expected genetic advance from different selection
indices at 5% selection intensity and relative efficiency of
each selection function over straight selection was also
calculated. The reciprocals of means of each character were
used as relative weights of corresponding character by [3].
The expected genetic advance, by constructing different discriminant functions was calculated and relative efficiency of
each discriminant function was estimated [4]. The relative efficiency of discriminant function which includes yield per
plant alone was taken as 100% and the relative efficiency of other fuve>nctions
were estimated.
RESULTS AND DISCUSSION
The data on weighing coefficients and genetic advance for each character was estimated to assess extent contribution of
each character towards yield. Among the characters days to 50% flowering recorded the highest weightage of (9.720)
followed by number of pods per plant (0.604) and the least weightage was recorded by test weight (-84.452). The
weightage coefficients (ß1) for seven characters were given in the table 1. Discriminant function with index of genetic
advance as well as relative efficiency over grain yield was computed for seven characters viz., plant height (cm), days to
50% flowering, number of primary branches per plant , number of secondary branches for plant, number pods per plant,
test weight (g) and yield (Kg/ha) (Table 2).
Table 1: Weighing coefficients (b1), economic weight and genetic advance for different characters in Pigeonpea
| S. No | Character | Economic weight | Weighing coefficient (ß1) | Variance phenotypical | Genetic advance |
| 1 | Plant height (cm) | 1.000 | -2.935 | -362.468 | -1.031 |
| 2 | Days to 50% flower | 1.000 | 9.720 | 142.080 | 0.404 |
| 3 | Primary branches/plant | 1.000 | -6.557 | 6.983 | 0.019 |
| 4 | Secondary branches/plant | 1.000 | -20.804 | 45.000 | 0.128 |
| 5 | Pods/plant | 1.000 | 0.604 | 5406.4618 | 15.387 |
| 6 | Test weight (g) | 1.000 | -84.452 | -162.0741 | -0.4613 |
| 7 | Yield (kg/ha) | 1.000 | 0.566 | 118381.743 | 336.919 |
| code | yield | Plan
t height (cm) |
Day
s to 50% flower |
Primary branches /plant |
Secondary branches /plant |
Pods/ plant | Test weight (g) | Genetic
advance ment |
Seletion intensity 5% |
%
gain over 1st variable |
| 1 | 0.624 | -- | -- | -- | -- | -- | -- | 328.49 | 676.70 | 100.0 % |
| 2 | 0.346 | 5.76 | 11.86 | 1.75% | ||||||
| 3 | 0.979 | 6.08 | 12.52 | 1.85 | ||||||
| 4 | 0.532 | 0.19 | 0.40 | 0.06% | ||||||
| 5 | 0.598 | 0.95 | 1.97 | 0.29% | ||||||
| 6 | 0.349 | 31.86 | 65.63 | 9.7% | ||||||
| 7 | 0.799 | 0.93 | 1.92 | 0.28% | ||||||
| 12 | 0.623 | -2.314 | -- | -- | -- | -- | -- | 329.43 | 678.63 | 100.2% |
| 16 | 0.632 | -- | -- | -- | -- | 0.457 | -- | 340.64 | 701.72 | 103.7% |
| 126 | 0.628 | -2.356 | -- | -- | -- | 0.546 | -- | 341.72 | 703.94 | 104.0% |
| 167 | 0.592 | -- | -- | -- | -- | 0.444 | - 48.113 | 344.20 | 709.04 | 104.7 % |
| 1267 | 0.58 5 | - 2.558 | -- | -- | -- | 0.538 | -58.652 | 345.85 | 712.45 | 105.2% |
| 1367 | 0.576 | -- | 7.631 | -- | -- | 0.449 | -65.983 | 346.44 | 713.68 | 105.4% |
| 1567 | 0.596 | -- | -- | -- | -25.8362 | 0.500 | -58.187 | 346.58 | 713.96 | 105.5% |
| 12367 | 0.561 | -3.200 | 10.255 | -- | -- | 0.565 | -77.157 | 349.77 | 720.52 | 106.4% |
| 123467 | 0.561 | -3.160 | 10.276 | -7.1564 | -- | 0.567 | -78.009 | 349.80 | 720.58 | 106.4% |
| 123567 | 0.567 | -2.971 | 9.699 | -- | -20.818 | 0.602 | -83.671 | 351.34 | 723.76 | 106.9% |
| 1234567 | 0.566 | -2.935 | 9.720 | -6.557 | -20.804 | 0.604 | -84.452 | 351.37 | 723.81 | 106.9% |
| Economic weights | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| International Journal of Life-Sciences Scientific Research (IJLSSR)
Open Access Policy
Authors/Contributors are responsible for originality, contents, correct
references, and ethical issues.
IJLSSR publishes all articles under Creative Commons
Attribution- Non-Commercial 4.0 International License (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/legalcode |