Twenty-two upland rice varieties were evaluated in randomized complete block design with three replications during 2014 cropping season at Pawe Northwestern Ethiopia to estimate association among grain yield and yield related traits and partition the correlation coefficients into direct and indirect effects. The analysis of variance showed significant (p < 0.01) differences for all traits except harvest index indicating the existence of variability. Correlation analysis of grain yield showed positive and significant associations with fertile tiller per plant (rg=0.792), biomass yield (rg=0.789), and plant height (rg=0.684) at genotypic level indicating that simultaneous improvement for these traits is possible. The path coefficient revealed that biomass yield, fertile tiller per plant and plant height exerted favorable direct effects on grain yield at both genotypic and phenotypic levels. Plant height, days to 85% maturity, fertile tillers per plant and thousand-grain weight supported the direct contribution of biomass yield to grain yield. The present investigations indicated that grain yield per plot was influenced by biomass yield, fertile tiller per plant, and plant height.

1. Correlation Coefficient and Path Analysis among Yield and Yield Related Traits in Upland Rice (Oryza sativa L. and Oryza glaberrima Steud)
Genotypes in Northwestern Ethiopia
IJPBCS
Correlation Coefficient and Path Analysis among Yield and
Yield Related Traits in Upland Rice (Oryza sativa L. and Oryza
glaberrima Steud) Genotypes in Northwestern Ethiopia
*Jember Mulugeta Bitew1, Firew Mekbib2, Alemayehu Assefa3
1Pawe Agricultural Research Centre, P.O. Box 25, Ethiopia
2Haramaya University School of Plant Sciences, P.O. Box 138, Dire Dawa, Ethiopia
3Ethiopian Institute of Agricultural Research, P.O. Box 2003, Fax .251-646-1294 Ethiopia
Twenty-two upland rice varieties were evaluated in randomized complete block design with three
replications during 2014 cropping season at Pawe Northwestern Ethiopia to estimate association
among grain yield and yield related traits and partition the correlation coefficients into direct and
indirect effects. The analysis of variance showed significant (p < 0.01) differences for all traits
except harvest index indicating the existence of variability. Correlation analysis of grain yield
showed positive and significant associations with fertile tiller per plant (rg=0.792), biomass yield
(rg=0.789), and plant height (rg=0.684) at genotypic level indicating that simultaneous improvement
for these traits is possible. The path coefficient revealed that biomass yield, fertile tiller per plant
and plant height exerted favorable direct effects on grain yield at both genotypic and phenotypic
levels. Plant height, days to 85% maturity, fertile tillers per plant and thousand-grain weight
supported the direct contribution of biomass yield to grain yield. The present investigations
indicated that grain yield per plot was influenced by biomass yield, fertile tiller per plant, and plant
height.
Keywords: Correlation, Path analysis, Rice, Variability, Yield.
INTRODUCTION
Rice (Oryza sativa L. and Oryza glaberrima Steud.) Is
central to the lives of billions of people around the world.
About 3.5billion people depend on rice as a daily food
staple for 20 % of their calories (OLAM
International,2015). It is the agricultural commodity with
the third-highest worldwide production, after sugarcane
and maize (FAOSTAT, 2012). Rice; is the most important
food crop and a major food grain for more than a third of
the world’s population (Zhao et al, 2011).
It is among the important cereal crops grown in different
parts of Ethiopia as food crop. Wide production of rice in
the country is believed to make a great contribution to food
security. Considering the importance and potential of the
crop, it has been recognized by the Government as “the
new millennium crop of Ethiopia” to attain food security
(MoA, 2010). However, the production, productivity, and
expansion of rice have been limited (Tesfaye et al., 2005).
In order to meet the fastest growing demand for rice grain,
developing high yielding genotypes with desirable
agronomic traits for diverse ecosystem is, therefore, a
requisite.
A successful breeding program depends on the genetic
diversity of a crop for achieving the goal so improving the
crop and producing high yielding varieties (Padulosi,
1993). Grain yield is a complex polygenic quantitative trait,
greatly affected by environment and determined by the
magnitude and nature of their genetic variability (Singh et
al., 2000)
*Corresponding Author: Jember Mulugeta Bitew, Pawe
Agricultural Research Centre, P.O. Box 25, Ethiopia. Tel:
+251585500327 Email: mulugetab39@gmail.com
Co-Author Email: 2
firew.mekbib@gmail.com;
3a_assefa@yahoo.com
International Journal of Plant Breeding and Crop Science
Vol. 5(3), pp. 429-436, December, 2018. © www.premierpublishers.org. ISSN: 2167-0449
Research Article

2. Correlation Coefficient and Path Analysis among Yield and Yield Related Traits in Upland Rice (Oryza sativa L. and Oryza glaberrima Steud)
Genotypes in Northwestern Ethiopia
Bitew et al. 430
Correlation coefficient measures the relationship between
two variables (Dabholkar, 1992). It simply measures mutual
association without regard to causation (Dewey and Lu,
1959). Phenotypic and genetic correlations are commonly
used in plant breeding. Phenotypic correlations involve
both genetic and environmental effects (Halluer and
Miranda, 1988).
Correlation analysis is a handy technique, which provides
information that selection for one-character results in
progress for other positively correlated characters
(Manggoel et al., 2012). The importance of correlation
studies in selection programs is appreciable when highly
heritable characters are associated with the important
characters like yield. Correlation coefficients, although very
useful in quantifying the size and direction of trait
associations, can be misleading if the high correlation
between two traits is a consequence of the indirect effect of
other traits (Bizeti et al., 2004).
The estimates of correlation coefficients reveal only the
relationship between yield and yield associated traits, but
could not explain the direct and indirect effects of different
traits on yield. This is because the attributes that are in
association do not exist by themselves, but are linked to
other components traits.
The path coefficient analysis by Dewey and Lu (1959)
suggests effective measure of direct and indirect causes of
association and depicts the relative importance of each
factor involved in contributing to the final product that is
yield. The variable grain yield is a result of interaction
between component traits, which are either positively or
negatively associated with each other. Path coefficient
analysis separates the direct effects from the indirect
effects through other related traits by partitioning the
correlation coefficient (Sravan, 2012). It requires a cause
and effect situation among variables.
However; information on relationship of grain yield and
yield contributing traits for upland rice of Ethiopian agro-
ecology is not sufficiently available. In view of the above
gaps, the present study was undertaken to investigate the
genetic variability, heritability, genetic advance and
association between grain yield and yield related traits as a
basis for selection of high yielding rice genotypes in
Ethiopian upland ecology. Hence, the present study was
undertaken with the objectives of (i) estimating association
among grain yield and yield related traits and; (ii) partition
the correlation coefficients in to direct and indirect effects,
MATERIALS AND METHODS
A field experiment was conducted using 22 upland rice
genotypes in the Northwestern part of Ethiopia at Pawe
agricultural research center during 2014 main cropping
season. Randomized complete block design with three
replications was used. Each experimental plot had a total
area of 6 m2 (1.2 m x 5 m) and six rows at 0.2 m interval.
There was a 0.5 m distance between two consecutive
plots within a replication. Seeds were sown in rows with
manual drilling at a rate of 60 kg % ha. Fertilizer was
applied at a rate of 100 kg DAP and 100 kg Urea per ha.
Recommended amount of DAP was applied during
planting while urea was applied in three splits at planting
tillering and at panicle initiation stages.
Data Collection and Analysis
Data was collected on number of fertile tillers per plant,
plant height, panicle length, number of filled grains per
panicle and number of unfilled grains per panicle were
collected on plant base and days to heading, days to
maturity, harvest index, thousand-grain weight, biological
yield and grain yield were collected on plot base. Analysis
of variance (ANOVA) was carried out on the data to
assess the genotypic effects and their interaction using
general linear model (GLM) procedure for randomized
complete blocks design (RCBD) using SAS (2004) version
9.1.3. Mean comparisons among treatment means were
conducted by the least significant difference (LSD) test at
5% levels of significance. The RCBD design analysis of
variance was used to derive variance components as
structured in Table 1 (Cochran and Cox, 1957).
Estimation of Phenotypic and genotypic correlation
coefficient (r)
The phenotypic and genotypic correlation coefficients
between two variables including genotype were estimated
as described by Singh and Chaudhary (1985).
Correlation coefficients at genotypic level (rgxy) were
calculated as;
rgxy=
gygx
GCOVxy
22
*
Where:
rgxy = genotypic correlation coefficient between traits x and
y
Covg xy= genotypic covariance between traits x and y.
Ϭ
2g x= genotypic variance of trait x
Ϭ2g y = genotypic variance of trait y
Correlation coefficients at phenotypic level (rpxy) were
calculated as;
rpxy
PyPx
PCOVxy
22
*
Where:
rpxy= phenotypic correlation coefficient between traits x and
y
Covp xy= phenotypic covariance between traits x and y.
Ϭ
2p x= phenotypic variance of trait x
Ϭ2p y = phenotypic variance of trait y

3. Correlation Coefficient and Path Analysis among Yield and Yield Related Traits in Upland Rice (Oryza sativa L. and Oryza glaberrima Steud)
Genotypes in Northwestern Ethiopia
Int. J. Plant Breed. Crop Sci. 431
The calculated phenotypic correlation value was tested for
its significance using t-test:
t = rph/SE (rph)
Where, rph = Phenotypic correlation; SE (rph) = Standard
error of phenotypic correlation was obtained using the
following formula (Sharma, 1998).
SE (rph) = √ (1-r2
ph)/(n-2)
Path coefficient analysis
Path coefficient was estimated as suggested by Dewey and
Lu (1959) to determine direct and indirect effect of different
variables on grain yield as:
rij = Pij + ∑rikPkj
RESULT AND DISCUSSIONS
The analysis of variance showed the presence of
significant differences among the tested genotypes for all
characters considered, indicating the existence of
variability among the tested genotypes. The analysis of
variance showed that the genotypes differed significantly
(p< 0.05) for fertile tiller per plant, filled grains per panicle,
unfilled grains per panicle, biomass yield and grain yield per
plot. and highly significant (p<0.001) for days to flowering,
days to maturity, hundred seed weight, plant height and
panicle length. But harvest index showed non-significant
variation on the tested genotypes (Table 1).
Table 1: The means quares for different sources of
variation for 11 Traits of 22 genotypes evaluated under
rainfed upland condition and the corresponding CV in
percentage.
Traits Mean Squares CV%
Replication (2) Genotype (21) Error (42)
DH 10.92 61.74** 25.15 6.75
DM 1.7 20.58** 3.01 1.6
PL 6.28 6.31** 2.35 7.1
PH 115.44 140.06** 40.87 6.39
FTPP 4.8 2.25* 0.96 14.64
GF 43.45 215.98* 121.96 10.61
UFGPP 1.46 2.69* 1.27 19.43
HI 0.0003 0.005NS 0.006 20.46
BY 271867 1446863.28* 575738 19.21
TGW 3.61 11.40*** 1.62 4.27
GY 2326975 717166.85* 317754 15.5
***Indicate significance at 0.05 and 0.01 probability levels.
NS =Non Significant
Where: GY=grain yield, DH= number of days to heading,
DM=number of days to85% maturity, PL= panicle length,
PH= plant height, GF = filled grains per panicle, BY=
biomass yield, HI= harvest index, TGW= thousand grain
weight, UFGPP = unfilled grains per panicle and FTPP =
fertile tiller per plant.
Estimates of correlation coefficients at phenotypic and
genotypic levels
Estimates of phenotypic, and genotypic, correlation
coefficients between each pair of traits are presented in
(Tables-4) respectively. The magnitudes of genotypic
correlation coefficients for most of the traits were higher
than their corresponding phenotypic correlation
coefficients, except in a few cases, which indicate the
presence of inherent or genetic association among various
traits.
In present study the correlation analyses revealed that, the
genotypic correlation coefficients were higher than the
phenotypic correlation coefficients demonstrating that, the
observed relationships among the various traits were due
to genetic causes indicating the phenotypic expression of
correlations is reduced under the influence of the
environment. This is also in agreement with the findings of
Jayasudha and Sharma (2010) and Patel et al. (2014).
Correlations of grain yield and yield related traits
Grain yield, being a quantitative trait, is a complex
character of any crop. Various morphological and
physiological plant traits contribute to yield. These yield-
contributing components are interrelated with each other
showing a complex chain of relationship and highly
influenced by the environmental conditions (Prasad et al.,
2001). Breeding strategy in rice mainly depends upon the
degree of associated traits as well. Grain yield had
significant and positive genotypic associations with fertile
tiller per plant (rg= 0.792), biomass yield (rg= 0.786), plant
height (rg= 0.684), days to maturity (rg=0.561) and days
to heading (rg=0.455). Thousand grain weight also showed
positive correlation with grain yield. Sharifi et al. (2013) also
reported a similar result.
At phenotypic level, biomass yield, fertile tiller per plant,
plant h e ig h t a n d days to 85% maturity were observed
to have positive and highly significant (p ≤ 0.01)
correlations with grain yield. Grain yield was significantly
and positively associated with numbers of fertile tiller per
plant (rp= 0.651), biomass yield (rp= 0.629), plant
height (rp= 0.558) number of days to maturity (rp=0.368)
and thousand grain weight (rp= 0.32). Similar findings
were reported by Prasad et al. (2001).
The strong positive correlation of number of fertile tillers
per plant biomass yield, plant height, and days to 85%
maturity with grain yield indicated that these characters
might be utilized as selection criteria for improving grain
yield in upland rice. Ekka et al. (2011) and Sravan et al.
(2012) also reported positive correlation of grain yield
with plant height, and that with plant height and effective
tillers per plant (Patel et al., 2014).

4. Correlation Coefficient and Path Analysis among Yield and Yield Related Traits in Upland Rice (Oryza sativa L. and Oryza glaberrima Steud)
Genotypes in Northwestern Ethiopia
Bitew et al. 432
Correlation among yield related traits
Remarkable associations were observed among yield
related traits (Table-2). Biomass yield per plot was
positively correlated with plant height (rg =0.713 and rp
=0.485), da ys to maturity (rg=0.683 and rp= 0.435),
numbers of fertile tiller per plant (rg =0.653 and rp =0.49),
thousand grain weight (rg =0.603 and rp =0.45). Although,
biomass yield per plot was also negatively correlated with
filled grains per panicle and significant at genotypic level
(rg=-0.42* and rp = -0.24) and none significant at
phenotypic level. This indicates that breeding for reduced
biomass yield might result in production of high filled
grains per panicle,
Fertile tillers per plant was strongly and positively
correlated with days to 85% maturity (rg =0.527and rp
=0.346) and plant height (rg =0.527andrp =0.440). Its
phenotypic correlation with thousand grain weight
(rp=0.334) was also positive and significant. However,
none of the traits showed significant negative association
with fertile tiller per plant at phenotypic level.
The genotypic and phenotypic associations between days
to 50% heading and days to 85% maturity were strong and
positive (rg = 0.770 and rp = 0.534). Venkata et al. (2014)
also reported similar findings. Days to 50% heading and
days to 85% maturity had also strong and positive
correlation with biomass yield at genotypic level. Plant
height, fertile tiller per plant, biomass yield and thousand
grain weights had significant positive correlation with days
to 85% maturity at phenotypic and genotypic levels. Days
to 50% heading had significant and positive association
with plant height (rg=0.498) and biomass yield
(rg=0.543). Filled grains per panicle had positive
association with panicle length but negative association
with plant height, unfilled grains per panicle, biomass
yield, and thousand grain weights at genotypic level.
Such negative correlations arise primarily from competition
for a common possibility, such as nutrient supply. If one
component gets advantage over the other, a negative
correlation may arise (Adams and Grafius, 1971).
At phenotypic level, filled grains per panicle had positive
and significant association with panicle length. Improving
these trait increases the development of filled grains per
panicle that support to increases grain yield. Plant height
showed significant and positive correlation with panicle
length at phenotypic level and days to maturity, fertile tillers
per plant, biomass yield thousand-grain weight and unfilled
grains per panicle at genotypic and phenotypic levels.
Eradasappa et al. (2007) reported a similar result for plant
height association with panicle length. Jayasudha and
Sharma (2010) and Selvaraj et al. (2011) also reported
similar findings with present study for fertile tiller per plant
and panicle length. Panicle length showed positive and
significant association with plant height (rp=0.441), filled
grains per panicle (rp=0.380) and unfilled grains per
panicle (rp=0.273). Panicle length also showed negative
correlation with days to 50 % heading, days to 85%
maturity and thousand grain weights at phenotypic and
genotypic level.
Table 2: Estimation of genotypic (above diagonal) and phenotypic (below diagonal) correlation coefficients between
yield and yield components traits in 22 Upland rice genotypes
Traits DH DM PNL PH FTPP GF UFGPP BY TGW GY
DH 1 0.770** -0.034 0.498* 0.42 0.341 0.213 0.543** 0.305 0.455*
DM 0.534** 1 -0.119 0.630** 0.527* 0.409 0.27 0.683** 0.539* 0.561**
PNL -0.01 -0.172 1 0.281 0.221 -0.207 0.349 0.064 -0.432* 0.283
PH 0.224 0.397** 0.411** 1 0.527* 0.130 0.616** 0.713** 0.497* 0.684**
FTPP 0.234 0.346** 0.234 0.440** 1 0.269 0.415 0.653** 0.376 0.792**
GF 0.068 0.091 -0.156** 0.014 -0.0193 1 0.162 0.495*
0.323 0.322
UFGPP 0.122 0.207 0.273* 0.461** 0.376** -0.067 1 0.558** 0.211 0.455*
BY 0.223 0.435** 0.072 0.485** 0.499** -0.144 0.186 1 0.603** 0.786**
TGW 0.099 0.451** -0.19 0.451** 0.334** 0.008 0.174 0.452** 1 0.348
GY 0.187 0.368** 0.195 0.558** 0.651** -0.053 0.299 0.629** 0.328* 1
***Indicate significance at 0.05 and 0.01 probability levels, respectively.
NS =Non Significant
Where: GY= grain yield, DH = number of days to head, DM = number of days to 85% maturity, PL= panicle length, PH =
plant height, GF = filled grains per panicle, BY= biomass yield, TGW= thousand grain weight, UFGPP = unfilled grains
per panicle,
Path Coefficient Analysis
Path-coefficient analysis using grain yield as dependent
variable and other traits as independent variables is
presented in Table 3 & 4. The genotypic path coefficient
analysis revealed that biomass yield (0.611) had the
maximum direct effect on grain yield, followed by fertile tiller
per plant (0.417) and plant height (0.368). Positive direct
effects of these traits on grain yield indicated their
importance in determining these complex traits and,
therefore, should be kept in mind while practicing selection
aimed at the improvement of grain yield. Rangare et al.

5. Correlation Coefficient and Path Analysis among Yield and Yield Related Traits in Upland Rice (Oryza sativa L. and Oryza glaberrima Steud)
Genotypes in Northwestern Ethiopia
Int. J. Plant Breed. Crop Sci. 433
(2012) also observed similar results for biomass yield.
Selvaraj et al. (2011), Ishwar et al. (2012), Neha and Lal
(2012) and Reddy et al. (2013) also reported similar results
for fertile tiller per plant.
Indirect effects of plant height, days to 85% maturity, and
fertile tillers per plant, thousand-grain weight, days to 50%
heading and unfilled grains per panicle supported the
direct contribution of biomass yield to grain yield.
Similarly, fertile tiller per plant also contributed to higher
grain yield via biomass yield (0.206), plant height (0.182),
unfilled grains per panicle (0.155), and days to 85%
maturity (0.143). Based on the result the trait biomass
yield per plot, fertile tiller per plant, and plant height
influenced grain yield either directly or indirectly.
Therefore, these traits should be included in the breeding
program of upland rice.In other words, favorable direct
effects of biomass yield per plot, fertile tiller per plant,
plant height and filled grains per panicle on grain yield
indicated that, other variables kept constant, improvement
of these traits will increase grain yield. Biomass yield per
plot, fertile tiller per plant and plant height had positive
indirect effects through most of the characters. The
genotypic indirect effects of these traits were important
components of genotypic correlations among these traits
and grain yield per plot. However, days to 50% heading,
panicle length, days to maturity, and thousand-grain weight
had negative indirect effects via several traits considered
in the study.
Days to 85% maturity, unfilled grains per panicle and days
to 50% heading were positively and significantly correlated
with grain yield per plot but their direct effects were
negative, indicating that indirect effects would be the cause
of correlation. In this situation, the indirect causal factors
were to be considered simultaneously for selection.
Therefore, it would be better to consider the other traits that
showed high indirect effect on grain yield per plant.
The phenotypic path coefficient revealed that fertile tiller
per plant (0.412), biomass yield (0.330) and plant height
(0.299) exerted high and favorable direct effects on grain
yield. Whereas thousand-grain weight (-0.114), days to
50% heading (-0.057), panicle length (-0.055), unfilled
grains per panicle (-0.021) and filled grains per panicle (-
0.002) had minor negative direct effect on grain yield.
Biomass yield (0.206), plant height (0.182), unfilled grains
per panicle (0.155), days to 85% maturity (0.143) and
thousand-grain weight (0.138) exhibited considerably
positive indirect effects on grain yield through fertile tiller
per plant. Therefore, these situations further confirm the
crucial role of fertile tiller in improving grain yield. It is also
logical to select plant height, thousand grain weight and
number of fertile tiller per plant to improve grain yield.
Similarly, fertile tiller per plant (0.164), plant height
(0.160), thousand grain weight (0.149) and days to 85%
maturity (0.143) exerts positive indirect effect on grain
yield through biomass yield.
The residual effect (0.1818) indicates that characters,
which are included in the genotypic path analysis,
explained 81.9% of the total variation in grain yield in
which the number of characters, chosen for the study were
appropriate for yield improvement in rice (the rest 18.1 %
was the contribution of other factors, such as traits not
studied). Yadav et al. (2010) and Mulugeta et al.
(2012) reported similar findings. Path analysis indicated
that fertile tiller per plant; biomass yield and plant height
could be used as selection criteria for better grain yield.
The results of this study revealed that the highest positive
indirect effects of plant height, days to 85% maturity,
fertile tillers per plant and, thousand-grain weight through
biomass yield and biomass yield and plant height through
fertile tiller per plant and plant height was recorded
Therefore, selection for higher yield in rice genotypes
should place maximum emphasis on these three traits
namely biomass yield, fertile tiller per plant and plant height
Table 3: Genotypic direct and indirect effects of nine component traits on grain yield in upland rice.
Variable DH DM PL PH FTPP GF UFGPP BY TGW rg
DH -0.06534 -0.06583 0.00087 0.166843 0.195992 0.003494 -0.03753 0.331951 -0.07566 0.455*
DM -0.05029 -0.08552 0.003059 0.21101 0.245986 0.000161 -0.04772 0.417846 -0.13357 0.561**
PL 0.002209 0.010166 -0.02574 0.094099 0.103142 0.014657 -0.06157 0.038843 0.107161 0.283
PH -0.03253 -0.05386 -0.00723 0.335074 0.245823 -0.00728 -0.10865 0.436392 -0.12335 0.684**
FTPP -0.02745 -0.04509 -0.00569 0.176537 0.466581 -0.00526 -0.0733 0.399464 -0.0933 0.792**
GF -0.0037 -0.00022 -0.00612 -0.03958 -0.0398 0.061647 0.032434 -0.25838 0.092195 -0.162
UFGPP -0.01389 -0.02313 -0.00898 0.206282 0.19379 -0.01133 -0.17649 0.341261 -0.05227 0.455*
BY -0.03546 -0.05842 -0.00163 0.239045 0.304696 -0.02604 -0.09846 0.611699 -0.14959 0.786**
TGW -0.01993 -0.04606 0.01112 0.166649 0.175523 -0.02292 -0.0372 0.368922 -0.24802 0.348
Residual effect=0.1818
***Indicate significance at 0.05 and 0.01 probability levels, respectively.
Where: GY= grain yield, DH= number of days to 50% heading, DM = number of days to 85% maturity, PL= panicle
length, PH= plant height, GF = filled grains per panicle, UFGPP= unfilled grains per panicle FTPP= fertile tillers
per plant, BY=biomass yield, and TGW= thousand grain weight

6. Correlation Coefficient and Path Analysis among Yield and Yield Related Traits in Upland Rice (Oryza sativa L. and Oryza glaberrima Steud)
Genotypes in Northwestern Ethiopia
Bitew et al. 434
Table 4: Phenotypic direct and indirect effects of nine component characters on grain yield in upland rice.
Variable DH DM PL PH FTPP GF UFGPP BIO TGW rp
DH -0.05785 0.0209 0.000548 0.066964 0.096966 0.000214 -0.00263 0.073702 -0.01133 0.187
DM 0.030886 0.039149 0.009498 0.118857 0.143469 0.000392 -0.00446 0.143937 -0.05168 0.368**
PL 0.000574 -0.00674 -0.05519 0.123099 0.097049 -0.00312 -0.00588 0.023826 0.021742 0.195
PH -0.01293 0.015533 -0.02268 0.299577 0.182189 -0.00183 -0.00994 0.160163 -0.05172 0.558**
FTPP -0.01354 0.01356 -0.01293 0.131769 0.414208 -0.00054 -0.0081 0.164956 -0.03833 0.651**
GF 0.00151 -0.00187 -0.021 0.066899 0.027441 -0.0082 -0.00084 -0.07929 0.015149 -0.0002
UFGPP -0.00706 0.008101 -0.01505 0.138195 0.155585 -0.00032 -0.02156 0.061462 -0.02 0.299
BIO -0.0129 0.017048 -0.00398 0.145157 0.206706 0.001967 -0.00401 0.330547 -0.05179 0.628**
TGW -0.00572 0.017652 0.010471 0.135205 0.138519 0.001084 -0.00376 0.149368 -0.11461 0.328*
Residual effect 0.406508
***Indicate significance at 0.05 and 0.01 probability levels, respectively
Where: GY= grain yield, DH = number of days to head, DM= number of days to mature, PL= panicle length, PH = plant
height, GF =filled grains per panicle, UFGPP = unfilled grains per panicle FTPP=fertile tillers per plant, BY= biomass
yield and TGW= thousand grain weight
CONCLUSION
The genotypic correlation coefficients were higher than the
phenotypic correlation coefficients demonstrating that, the
observed relation-ships among the various traits were due
to genetic causes. Grain yield had significant and positive
association with fertile tiller per plant, biomass yield, plant
height and days to 85% maturity at both genotypic and
phenotypic levels. The strong positive correlation of these
characters might be utilized as selection criteria for
improving grain yield in upland rice. Remarkable
associations were observed among yield related traits.
Biomass yield per plot was positively correlated with
plant height, days to maturity, numbers of fertile tiller per
plant, thousand grain weight. Although, biomass yield per
plot was also negatively correlated with filled grains per
panicle and significant at genotypic level. This indicates
that breeding for reduced biomass yield might result in
production of high filled grains per panicle, filled grains per
panicle had positive association with panicle length but
negative association with plant height, unfilled grains
per panicle, biomass yield, and thousand grain weights
at genotypic level. Such negative correlations arise
primarily from competition for a common possibility, such
as nutrient supply. At phenotypic level, filled grains per
panicle had positive and significant association with
panicle length. Improving these trait increases the
development of filled grains per panicle that support to
increases grain yield.
Path coefficient analysis of grain yield per plot revealed that
biomass yield per plot, fertile tiller per plant and plant
height were the major contributors of grain yield.
Positive direct effects of these traits on grain yield indicated
their importance in determining these complex traits and
therefore, should be kept though practicing selection
aimed at the improvement of grain yield. Based on the
result the trait biomass yield per plot, fertile tiller per plant,
and plant height influenced grain yield either directly or
indirectly. Therefore, these traits should be included in the
breeding program of upland rice. In other words, favorable
direct effects of these traits on grain yield indicated that,
other variables kept constant, improvement of these traits
will increase grain yield. The phenotypic path coefficient
revealed that fertile tiller per plant, biomass yield and
plant height exerted high and favorable direct effects on
grain yield Biomass yield, plant height, unfilled grains per
panicle , days to 85% maturity and thousand-grain weight
exhibited considerably positive indirect effects on grain
yield through fertile tiller per plant. Therefore, these
situations further confirm the crucial role of fertile tiller in
improving grain.
Based on the result of present study on correlation and
path analysis, biomass yield per plot, fertile tiller per plant
and plant height influenced grain yield either directly or
indirectly. Therefore, these traits should be included in the
breeding program of upland rice. The phenotypic path
coefficient analysis revealed that fertile tiller per plant,
biomass yield and plant height exerted high and favorable
direct effects on grain yield. The favorable direct effects of
these traits on grain yield indicate that, other variables kept
constant, improvement of these traits will increase grain
yield.
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8. Correlation Coefficient and Path Analysis among Yield and Yield Related Traits in Upland Rice (Oryza sativa L. and Oryza glaberrima Steud)
Genotypes in Northwestern Ethiopia
Bitew et al. 436
Accepted 1 November 2018
Citation: Bitew MU, Mekbib F, Assefa A (2018).
Correlation Coefficient and Path Analysis among Yield
and Yield Related Traits in Upland Rice (Oryza sativa L.
and Oryza glaberrima Steud) Genotypes in Northwestern
Ethiopia. International Journal of Plant Breeding and Crop
Science 5(3): 429-436.
Copyright: © 2018 Bitew et al. This is an open-access
article distributed under the terms of the Creative
Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium,
provided the original author and source are cited.