Path coefficient studies of yield and yield associated traits in bread wheat
(Triticum aestivum L.)
CHITRALEKHA SHYAM, P. K. CHANDRAKAR and N. K. RASTOGI
Department of Genetics and Plant Breeding, Indira Gandhi Krishivishwavidyalaya, Raipur
(C.G.), India
* (Email: [email protected])
ABSTRACT
Wheat (Triticum aestivum L.) is an important cereal crop of cool climates, and plays an
important role in the food and nutritional security of India. The objective of this study was to
establish the inter-relationship and direct and indirect effect of various wheat components on
seed yield per plant. Twenty two wheat genotypes and seven check varieties were studied for
determining relationship, direct and indirect effects of yield components. The experiment was
conducted at Research Farm, IGKV, Raipur during Rabi 2013-14. Path coefficient analysis
revealed that number of seeds per spike, 1000-seed weight, biological yield per plot, spike length
and days to 50 % flowering exhibited a high positive direct effect and significant correlation
coefficient with seed yield per plant. Therefore direct selection through these traits will be
effective for yield improvement in seed yield. Plant height, days to maturity and number of
spikelets per spike had negative direct effect as well as significant negative correlation with seed
yield per plant. Therefore, it is logical to select plants having short plant height, early maturity
and low number of spikelets per spike for the improvement of seed yield per plant.
Key Words: Correlation coefficient, path coefficient, yield components, variability, wheat
INTRODUCTION
Wheat (Triticum aestivum L.) is an important cereal crop of cool climates, and plays an
important role in the food and nutritional security of India. In India, 86 % of the cultivated area
under wheat represents hexapliodies spring type belonging to Triticum aestivum L. em. Thell.,
(Singh et al., 2008) more commonly called bread wheat. Wheat is widely grown the world-over
and stands first among the cereals both in area and production. It is used in the form of chapatti,
bread, naan, tandoori, rumali, roti, puri, pudding, bhatore, bran and fodder etc. (Singh et al.,
2013).
Most of the agronomic characters in crop plants are quantitative in nature. Yield is one
such characters that results due to the actions and interactions of various component characters
(Graficus, 1960). The objective of this study was to establish the inter-relationship and direct and
indirect effects of various wheat components among themselves and with yield.
MATERIALS AND METHODS
Twenty two wheat genotypes and seven check varieties were used in this study. All the
twenty two genotypes were grown in Randomized Block Design with three replications during
Rabi 2013-14 at the Instructional cum Research Farm, Indira Gandhi Krishi Vishwavidyalaya,
Raipur. In each replication twenty two treatments were grown in 10 rows, 5 m long and 20 cm
apart.
Five randomly selected plants from each treatment were tagged for recording the
observations on the following characters, viz., Days to 50 % flowering, Days to maturity, Plant
height, Number of tillers per plant, Spike length, Number of spikelets per spike, Number of seeds
per spikelet, Number of seeds per spike, Number of seeds per plant, 1000-seed weight, Seed yield
per plant, Biological yield per plot, Seed yield per plot and Harvest Index.
Genotypic correlations were computed using variance and co-variances as suggested by
Johnson et al., (1955). Path coefficient analysis was performed as suggested by Dewey and Lu
(1959).
RESULTS AND DISCUSSION
Correlation coefficient analysis
Correlation coefficient analyses are presented in Table 1. Seed yield per plant exhibited
highly significant positive correlations with number of seeds per spike and number of seeds per
plant at both genotypic and phenotypic levels, whereas number of seeds per spikelet at the
genotypic level. The finding confirms to earlier reporters (Ali et al., 2008; Majumdar et al.,
2008). This indicates the relative utility of all these traits for selection with respect to seed yield.
Seed yield per plant was also significant negatively associated at genotypic level with days to 50
% flowering, days to maturity, plant height and number of spikelets per spike. Present results
conforms the finding of previous worker (Ali et al., 2008). Harvest index showed positive and
significant association with number of seeds per plant, 1000-seed weight, seed yield per plant
and biological yield per plot at genotypic level whereas plant height, numbers of tillers per plant
and spike length were significantly and negatively associated with harvest index at the genotypic
level. This was in conformity with the findings of Kumar et al., 2013; Keddam et al., 2014.
Days to 50 % flowering showed significant and positive correlations with days to
maturity at phenotypic and genotypic levels, suggesting that plants with early maturity produce
early flowering. The finding confirms to earlier reporters (Kumar et al., 2013; Mohammad et
al., 2005; Shahid et al., 2002; Keddam et al., 2014). Significant and negative correlation of days
to 50 % flowering with number of seeds per spike exhibited at the genotypic and phenotypic
levels. However, plant height with number of tillers per plant observed a significant and positive
correlation at genotypic level, suggesting that plants with more tillers produce shortest plant
height. Similarly, plant height presented positive significant association at both genotypic and
phenotypic levels with spike length, suggesting that taller plants with heavier spikes were
produce. Present results conforms the finding of previous worker (Kumar et al., 2013; Nukasani
et al., 2013).
Number of tillers per plant with spike length observed significant and positive correlation
at phenotypic and genotypic levels, suggesting that plants with more tillers bear heavier spike,
which is in agreement with the earlier reports of (Keddam et al., 2014; Kumar et al., 2013;
Mohammad et al., 2005; Shahid et al., 2002). Significant and positive correlations were
observed at genotypic level for days to maturity with number of spikelets per spike. Significant
and negative correlation existed at the genotypic and phenotypic levels for days to 50 %
flowering with number of seeds per spikelet.
Path coefficient analysis
In the present study path coefficient analysis has been conducted taking seed yield per
plant as dependent variable. Path coefficient analysis was carried out using coefficient of all the
traits with seed yield per plant (Table 2.) Number of seeds per spike and biological yield per plot
had positive direct effect (3.327, 0.677) and exhibited significant positive correlation (0.726**,
0.764**) with seed yield per plant, indicating a true relationship among these traits. This may
indicate that the direct selection for number of seeds per spike and biological yield per plot
would likely be effective in increasing seed yield per plant. Similar results were reported by Ali
et al., (2008); Khan and Dar (2009); Majumder et al., (2008).
On the other hand, the maximum negative direct effect and significant positive
correlation was exhibited by number of seeds per plant (-3.166), harvest index (-1.349), number
of seeds per spikelet (-0.542) and seed yield per plot (-0.187). Direct effect of number of seeds
per plant with seed yield per plant was negative (-3.166) however; the correlation coefficient was
significant positive (0.877**) due to the positive indirect effect via. number of seeds per spike,
plant height, biological yield per plot, days to maturity, 1000-seed weight, number of spikelets
per spike and number of tillers per plant. Since the direct effect was negative, so the direct
selection for these traits to improve yield will be undesirable. However, improvement in number
of seeds per spike, plant height, biological yield per plot, days to maturity, 1000-seed weight,
number of spikelets per spike and number of tillers per may help compensate the negative effect
of number of seeds per plant.
Direct positive effect and significant negative correlation (-0.448*) on seed yield per
plant was showed by days to 50 % flowering (0.28), indicating the negligible. So that the
selection for this traits will not be effective.
Plant height, days to maturity and number of spikelets per spike had negative direct effect
as well as significant negative correlation with seed yield per plant. Therefore, it is logical to
select plants having short plant height, early maturity and low number of spikelets per spike for
the improvement of seed yield per plant.
Harvest index (3.358), Seed yield per plot (2.908), number of seeds per plant (2.664),
Biological yield per plot (2.521), plant height (2.029), 1000-seed weight (1.868), days to 50 %
flowering (1.752), number of seeds per spikelet (1.621), number of tillers per plant (1.371) and
days to maturity (1.292) exhibited positive indirect effect on seed yield per plant. Majumdar et
al., (2008) also reported indirect effect of harvest index on seed yield per plant. The ndirect
effect of harvest index and biological yield per plant on seed yield per plant is supported by the
finding of Singh et al., (2013).
The ideotype to increase seed yield per plant through direct selection in wheat should
have maximum number of seeds per spike, high biological yield per plot, more number of seeds
per plant, high harvest index and greater number of seeds per spikelet.
All the above characters exhibited indirect effect mostly through harvest index, Seed
yield per plot, number of seeds per plant, Biological yield per plot, plant height, 1000-seed
weight, days to 50 % flowering, number of seeds per spikelet, number of tillers per plant. Hence,
it may be concluded that harvest index is the main traits which is responsible for the
manipulation of seed yield per plant in wheat. Selection for any other yield contributing
character will reflect on seed yield per plant only through harvest index.
REFERENCES
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association and diversity studies in wheat (Triticum aestivum L.) Germplasm. Pak. J.
Bot., 40(5): 2087-2097.
Dewey, D.R. and Lu, K.H. 1959. A Correlation and path coefficient analysis of component of
crested wheat grass seed production. Agronomy Journal 51: 515-518.
Grafius, J. E. 1960. Does overdominance exist for yield in corn? Agronomy Journal 52: 361
Johnson, H.W., Robinson, H.F. and Comstock, R.E. 1955. Genotypic and phenotypic
correlations and their implication in selection. Agronomy Journal 47: 477-483.
Keddem, W.K., Markar, S. and Lavanya G.R. 2014. Investigation of genetic variability and
correlation analysis of wheat (Triticum aestivum L.) genotypes for grain yield and its
component traits. European Academic Research 2(5): 2286-4822.
Khan, M.H. and Dar, A.N. 2009. Correlation and path coefficient analysis of some quantitative
traits in wheat. African Crop Science Journal 18 (1): 9-14.
Kumar, B., Singh, C.M. and Jaiswal, K. K. 2013. Genetic variability association and diversity
studies in bread wheat ( Triticum aestivum L. ). An International journal of life Science
(1): 143-147.
Majumder, D.A.N., Shamsuddin, A.K.M., Kabir, M.A. and Hassan, L. 2008. Genetic variability,
correlated response and path analysis of yield and yield contributing traits of spring
wheat. J. Bangladesh Agril. Univ., 6(2): 227-234.
Mohammad, T., Haider, S., Amin, M., Khan, I.M. and Zamir, R. 2005. Path coefficient and
correlation studies of yield and yield association traits in candidate bread wheat (Triticum
aestivum L.) lines. Suranaree Journal of Science Technology 13 (2) : 175 – 180.
Nukasani, V., Potdukhe, N.R., Bharad, S., Deshmukh, S. and Shinde, S.M. 2013. Genetic
variability, correlation and path analysis in wheat. Journal of Wheat Research 5(2): 4851.
Shahid, F., Mohammad, F. and Tahir, M. (2002). Path coefficient analysis in wheat. Sarhad
J. Agric., 18(4): 383-388.
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New Botanist 35 (1-4): 65-69.
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Science9(2):480-485.
Table 1.Phenotypic and genotypic correlation coefficients of yield and its components in wheat
Days to
maturit
y
0.755**
0.778**
P
Days to 50 %
flowering
G
P
Days to
maturity
G
P
Plant height
(cm)
G
No. of tillers per P
plant
G
P
Spike length
(cm)
G
P
No. of spikelets
per spike
G
P
No. of seeds per
spikelet
G
P
No. of seeds per
spike
G
P
No. of seeds per
plant
G
P
1000-seed
weight (g)
G
P
Seed yield per
plant (g)
G
P
Biological yield
per plot (g)
G
P
Seed yield per
plot (g)
G
**, * Significant at 1 % and 5 % level
Plant
height
(cm)
0.147
0.152
0.356
0.406
No. of
tillers per
plant
0.035
0.025
0.163
0.26
0.406
0.502*
Spike
length
(cm)
-0.082
-0.091
0.276
0.325
0.632**
0.842**
0.493*
0.790**
No. of
spikelets
per spike
0.128
0.181
0.306
0.500*
0.26
0.363
0.018
-0.267
0.238
0.14
No. of
seeds per
spikelet
-0.426*
-0.733**
-0.393
-0.735**
0.004
0.129
0.129
0.327
0.208
0.185
0.096
-0.203
No. of
seeds per
spike
-0.307
-0.424*
-0.056
-0.059
-0.075
-0.15
0.287
0.275
0.32
0.328
0.273
0.051
0.352
0.487*
No. of
seeds per
plant
-0.489*
-0.554**
-0.373
-0.409
-0.490*
-0.642**
-0.024
-0.049
-0.11
-0.147
-0.16
-0.373
0.232
0.408
0.591**
0.801**
1000seed
weight (g)
-0.072
-0.077
-0.409
-0.418
-0.517*
-0.573**
-0.470*
-0.698**
-0.693
-0.782**
-0.172
-0.263
-0.073
-0.077
0.343
-0.424*
0.079
0.105
Seed yield
per plant
(g)
-0.295
-0.448*
-0.351
-0.508*
-0.403
-0.746**
0.258
-0.083
-0.133
-0.374
-0.048
-0.492*
0.36
0.629**
0.538**
0.726**
0.589**
0.877**
0.077
0.182
Biological
yield per
plot (g)
-0.265
-0.341
-0.287
-0.364
-0.504**
-0.774**
-0.045
-0.346
-0.266
-0.399
-0.21
-0.711**
0.224
0.303
0.265
0.332
0.553**
0.730**
0.191
0.272
0.571**
0.764**
Seed yield
per plot
(g)
-0.287
-0.34
-0.33
-0.395
-0.713**
-0.892**
-0.257
-0.41
-0.349
-0.539**
-0.283
-0.569**
0.127
0.171
0.272
0.353
0.596**
0.824**
0.319
0.399
0.570**
0.813**
0.771
0.980**
Harvest
index
(%)
-0.084
-0.161
-0.165
-0.344
-0.537**
-1.030**
-0.364
-0.649**
-0.274
-0.826**
-0.194
-0.347
-0.099
-0.319
0.086
0.132
0.29
0.794**
0.327
0.700**
0.239
0.673**
0.085
0.816**
0.680**
0.919**
Table 2.Genotypic path coefficient analysis showing direct and indirect effect of different yield contributing traits on seed yield per plant (g)
Days to 50
flowering
Days to 50 % flowering
0.28
-0.676
-0.497
-0.001
-0.158
No. of
spikelets
per
spike
-0.049
Days to maturity
0.218
-0.868
-1.323
-0.013
0.564
-0.136
0.398
-0.195
1.292
-0.735
-0.247
0.074
0.464
-0.508*
Plant height (cm)
0.043
-0.352
-3.259
-0.026
1.461
-0.099
-0.070
-0.498
2.029
-1.008
-0.524
0.167
1.390
-0.746**
No. of tillers per plant
0.007
-0.225
-1.637
-0.052
1.371
0.072
-0.177
0.914
0.154
-1.227
-0.234
0.077
0.875
-0.083
Spike length (cm)
-0.026
-0.282
-2.746
-0.041
1.735
-0.038
-0.100
1.090
0.465
-1.375
-0.271
0.101
1.114
-0.374
No. of spikelets per spike
0.051
-0.434
-1.184
0.014
0.243
-0.271
0.110
0.171
1.177
-0.462
-0.481
0.106
0.469
-0.492*
No. of seeds per spikelet
-0.205
0.638
-0.419
-0.017
0.320
0.055
-0.542
1.621
-1.289
-0.136
0.205
-0.032
0.430
0.629**
No. of seeds per spike
-0.119
0.051
0.488
-0.014
0.568
-0.014
-0.264
3.327
-2.531
-0.746
0.225
-0.066
-0.178
0.726**
No. of seeds per plant
-0.155
0.355
2.092
0.003
-0.255
0.101
-0.221
2.664
-3.160
0.184
0.494
-0.154
-1.071
0.877**
1000-seed weight (g)
-0.021
0.363
1.868
0.036
-1.357
0.071
0.042
-1.412
-0.331
1.758
0.184
-0.075
-0.944
0.182
Biological yield per plot (g)
-0.095
0.316
2.521
0.018
-0.693
0.193
-0.164
1.104
-2.306
0.477
0.677
-0.183
-1.101
0.764**
Seed yield per plot (g)
-0.095
0.343
2.908
0.021
-0.935
0.154
-0.093
1.176
-2.604
0.701
0.664
-0.187
-1.239
0.813**
Harvest index (%)
-0.045
0.299
3.358
0.033
-1.432
0.094
0.173
0.439
-2.509
1.231
0.553
-0.172
-1.349
0.673*
Residual effect = 0.3174
**, * Significant at 1 % and 5 % level
Days to
maturity
Plant
height
(cm)
No. of
tiller per
plant
Spike
length
(cm)
No. of
seeds
per
spikelet
0.397
No. of
seeds per
spike
-1.41**
No. of
seeds
per
plant
1.752
1000seed
weight
(g)
-0.135
Biologic
al yield
per plot
(g)
-0.231
Seed
yield
per plot
(g)
0.064
Harvest
index
(%)
0.217
Genotypic
correlation
with Seed yield
per plant (g)
-0.448*