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Greener
Journal of Agricultural Sciences ISSN:
2276-7770 Vol.
13(1), pp. 46-53, 2023 Copyright
©2023, Creative Commons Attribution 4.0 International. |
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Genetic Variability for Some Morphological Traits in Lowland
Rice (Oryza sativa L.)
Agbodike, Onyekachi Cynthia1 and Efisue,
Andrew Abiodun1
1Department of Crop & Soil Science, University of Port
Harcourt, Port Harcourt, Nigeria.
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ARTICLE INFO |
ABSTRACT |
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Article No.: 050122043 Type: Research |
The study
on genetic variability for some morphological trait in rice enables breeders
to be able to select the lines of rice that can be suitable for breeding
programs. Different data was
collected on growth parameter and yield components. The objective of this
study was to determine the genetic variability for some morphological traits
and their correlation with yield contributing factors. There are 10 entries
that comprised 8 anther cultured derived lines from South Korea and 2 from
University of Port Harcourt AGRA germplasm.
Experimental design used was Randomized Complete Block Design (RCBD), in
three replications. The rice seeds were directly seeded in a poly pot of
three seeds per pot and thinned to two after 15 days of emergency,
each variety has two poly pots per replication. Significant differences
exist among the genotypes for all the morphological traits measured.
Genotypes four are earlier than the mean value for days to 50% flowering and
days to maturity. The earliest genotype was UPN 234 followed by UPN 268 and
the late maturing genotype was UPN 276. Most of the traits measured were
significant and positively correlated with other traits and correlation
magnitudes ranging from 0.45 to 1.00. Dendrogram
showed that WBK114 is different from other rice varieties evaluated, because
it is interspecific hybrid (O. sativa and O. glaberrima). This information will assist the breeder in
the selection of parent for crop improvement. The early maturing genotypes
can be recommended to farmers to grow them because it is possible for the
farmers to grow them in three cropping seasons in a year which is of
economic importance and livelihood to farmers. |
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Accepted: 14/04/2023 Published: 26/04/2023 |
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*Corresponding
Author Efisue Andrew Abiodun E-mail: andyefisue@ yahoo.com |
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Keywords: |
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INTRODUCTION
Rice
is considered as one of the most important cereal crop after corn and it is
grown on over 161.1 million hectares of land, yielding 487.5 metric tons of
milled rice worldwide (Statista, 2018). Exploring genetic
diversity in available landrace and wild relatives is one of the most important
ways to improve the germplasms (Thomson et al., 2007)
used in breeding programs. For sustainable breeding programme,
clear-cut knowledge on genetic diversity related to yield and yield
contributing traits is a vital one. Through systematic test and evaluation of germplasms, plant breeders are trying to exploit superior
genetic stock for selection and production of cultivars with high yield
potentiality (Salim et al., 2021) as rice cultivation
does not solely depends on cultural practices but also relies on inherent
genetic variability among the germplasm (Augustina et al., 2013). For enhancement of rice
production, determining the best breeding procedures is a must and in this
aspect, it is crucial to have morpho-genetic
diversity for different yield contributing traits in rice. Presence of wide
genetic diversity for yield and its attributes in rice have been reported
(Ahmed et al., 2016, Akter et al., 2016 and Akter et al., 2018a,b,c). To
ascertain the polygenic relationships within and between species,
agro-morphological traits have been widely used to study genetic variability
and character association in rice (Akter et al., 2018
a,b,c). The genetics of morpho-physiological traits in segregating populations rice was reported (Efisue
et al., 2009) to assist the breeders in crop improvement.
Therefore, it is necessary to determine the association
between yield and some of the morphological components that have a great effect
on yield. This information on the association is of great importance to
breeders in selecting desirable genotypes (Özer et
al., 1999; Fukai et al., 1991 and Weng
et al., 1982). The objective of this study was to determine the genetic
variability for some morphological traits and their correlation with yield
contributing factors
MATERIALS
AND METHODS
The research was
carried out at the University of Port Harcourt Faculty of Agriculture’s
teaching and research farm in Choba, Rivers State.
University of Port Harcourt is located in the southern part of the country
along the Niger-Delta coast and lies on latitude 4°31 to 5°00N
and longitude 6°45 to 7°00 E, has an estimated
annual rainfall of 2000 – 2680 mm and an average temperature of 28 – 30
with an elevation of 20 metres above sea level. There are 10 entries that comprised 8 anther cultured
derived lines from South Korea and 2 from University of Port Harcourt AGRA germplasm (Table 1). Experimental design used was Randomized Complete Block Design (RCBD), in
three replications. The rice seeds were directly seeded in a poly pot of three
seeds per pot and thinned to two after 15 days of emergency,
each variety has two poly pots per replication. Manual irrigation was applied
to maintain soil field capacity. Basal fertilizer was applied at 5g per poly
pot of NPK 20:10:10 (200kg/ha) and top-dressed with urea (46% N) 65 kg /ha at 5g per poly pot. Weeds were controlled manually by
hand picking throughout the duration of the experiment.
Table 1: Varieties used in this study
|
S/NO |
Origin/Source |
|
|
1 |
WBK 114 |
Uniport Agra germplasm |
|
2 |
IR 64 |
Uniport Agra germplasm |
|
3 |
UPN 276 |
Anther culture line (derived from South Korea) |
|
4 |
UPN 228 |
Anther culture line (derived from South Korea) |
|
5 |
UPN 254 |
Anther culture line (derived from South Korea) |
|
6 |
UPN 266 |
Anther culture line (derived from South Korea) |
|
7 |
UPN 347 |
Anther culture line (derived from South Korea) |
|
8 |
UPN 234 |
Anther culture line (derived from South Korea) |
|
9 |
UPN 236 |
Anther culture line (derived from South Korea) |
|
10 |
UPN 268 |
Anther culture line (derived from South Korea) |
Data
Collection
Data was collected at the appropriate time
of crop development. The following data were collected at the appropriate phenology.
All data measurements were based on the standard evaluation system (SES) for
rice reference manual (IRRI, 2013). Data was taken for four weeks after
planting and was taken from two plants stand of each variety per pot. Plant
height was measured in centimeter from the base to the tip of the highest leaf,
leaf length was measured from below the flag leaf to the tip of the highest
leaf, and leaf width was measured from the widest leaf. Effective tillers,
which is the number of tiller harvested, the number of panicles in each plant.
Panicle length of the central tiller of each plant was measured at maturity
using a meter rule. The number of grains (seeds) per panicle was taken from the
main tiller of each plant and was counted at maturity stage separately after
harvesting. Plant biomass was taken, weight of panicle, weight of seeds per
1000g were all taken at maturity.
Data
Analysis
The following analysis were carried out,
Analysis of variance (ANOVA) using PROC GLM (SAS 2003) for mean separation, correlation
analysis and cluster analysis using pair-wise distance matrixes between
genotypes, and were again derived using the numerical taxonomy and multivariate
analysis system (NTSYS-PC), Version 2.1 (Rohlf, 2000)
and the Jaccard coefficient of similarity (Jaccard, 1908). Genetic diversity dendogram
for the genotypes was created by unweighted pair
group method with arithmetic mean (UPGMA) cluster analysis (Sneath
and Sokal, 1973; Swofford
and Olsen, 1990).
RESULTS
Evaluation of Growth
and Yield Parameters of Selected Rice Genotypes
Table
2 below shows that significant differences exist in the growth parameters of
the rice genotypes with exception of number of tillers, but the genotype with
the highest number of tillers was UPN276 (14.17±2.05) followed by UPN228
(12.00±3.33), while WBK114 (2.07±0.07) had the least number of tillers. WBK114
produced the highest mean plant height of 93.83±2.17cm while plant height means
were UPN228 (87.40±6.97cm), UPN347 (85.50±4.51cm). WBK also dominated leaf area
(163.71±7.89cm2) and leaf area index (8.48±0.41) measurement which
was significantly different from other genotypes. UPN228
(109.24±10.47cm2; 5.66±0.54), UPN276 (87.21±3.95cm2;
4.52±0.20). Genotype UPN276 had the highest mean number of panicles per
plant of 10.33±0.33 and followed by UPN228 (9.67±1.01) and UPN347 (8.50±2.57)
(Table 2).
Table 2: Mean Comparison of Growth
Parameters Amongst Selected Rice Genotypes
|
Genotype |
No. of Tillers |
Plant Height (cm) |
Leaf Area (cm2) |
Leaf Area Index |
Number of Panicle Per Plant |
Panicle Length (cm) |
|
UPN254 |
9.67±1.09a |
61.17±8.41bc |
65.13±14.29cd |
3.37±0.74cd |
7.83±0.60ab |
21.15±3.38a |
|
UPN347 |
8.83±4.33a |
85.50±4.51a |
86.64±1.50bc |
4.49±0.08bc |
8.50±2.57ab |
25.58±1.66a |
|
WBK114 |
2.07±0.07a |
93.83±2.17a |
163.71±7.89a |
8.48±0.41a |
3.00±0.00c |
26.27±1.10a |
|
UPN234 |
7.33±2.33a |
47.33±2.67c |
29.96±4.28d |
1.55±0.22d |
6.67±1.67abc |
12.56±0.58c |
|
UPN228 |
12.00±3.33a |
87.40±6.97a |
109.24±10.47b |
5.66±0.54b |
9.67±1.01ab |
25.24±0.42a |
|
UPN276 |
14.17±2.05a |
78.50±2.47ab |
87.21±3.95bc |
4.52±0.20bc |
10.33±0.33a |
23.30±0.86a |
|
UPN268 |
10.50±0.58a |
47.83±1.09c |
30.15±3.86d |
1.56±0.20d |
7.17±1.17abc |
12.55±0.80c |
|
UPN236 |
8.33±3.11a |
62.67±12.67bc |
72.44±24.50c |
3.75±1.27c |
5.33±1.59bc |
19.74±4.20b |
|
Mean |
9.11 |
70.53 |
80.56 |
4.17 |
7.31 |
20.8 |
|
CV (%) |
24.77 |
27.84 |
37.41 |
35.4 |
30.04 |
29.38 |
Means with different alphabet are
significantly different at p ≤ 0.05
There were significant differences observed
among the rice genotypes except in the biomass and weight of seed per plant. (Table 3). The UPN234 (83.99±0.74g) had the highest mean
value for biomass followed by UPN347 (81.65±1.85g). The highest mean weight of
seed per plant were UPN228 (15.97±1.62g) and UPN268 (15.45±4.48g). The highest
value of weight of 1000 seeds was WBK114 (21.13±0.62g), followed by UPN 268
(19.70±0.30g). Four genotypes were earlier than the mean value for days to 50%
flowering and days to maturity (Table 3). The earliest genotype was UPN 234,
followed by UPN 268 and late maturing genotype was UPN 276 (Table 3).
Table 3: Mean Comparison of Yield
Components and Flower Parameters Amongst Selected Rice
Genotypes
|
Genotype |
Biomass (g) |
Weight of Seed Per Plant (g) |
Weight of 1000 seeds (g) |
Days to 50% flowering |
Days to Maturity |
|
76.38±2.57a |
12.53±1.75a |
18.50±0.80bc |
45.67±6.71bc |
75.67±6.71bc |
|
|
UPN347 |
81.65±1.85a |
14.26±3.26a |
17.87±0.37bc |
57.17±10.04abc |
87.17±10.04abc |
|
WBK114 |
69.38±1.66a |
7.88±1.66a |
21.13±0.62a |
51.00±1.00abc |
81.00±1.00abc |
|
UPN234 |
83.99±0.74a |
12.25±5.55a |
17.97±0.99bc |
32.07±9.05c |
62.07±9.05c |
|
UPN228 |
79.80±1.23a |
15.97±1.62a |
17.87±0.35bc |
66.00±3.79ab |
96.00±3.79ab |
|
UPN276 |
77.93±2.91a |
14.47±3.00a |
18.00±0.25bc |
71.67±8.80a |
101.67±8.80a |
|
UPN268 |
73.37±9.16a |
15.45±4.48a |
19.70±0.30ab |
35.17±1.67bc |
65.17±1.67bc |
|
UPN236 |
79.23±3.19a |
9.08±2.34a |
17.80±0.26c |
59.67±13.35ab |
89.67±13.35ab |
|
Mean |
77.72 |
12.74 |
18.6 |
52.3 |
82.3 |
|
CV (%) |
9.14 |
42.94 |
7.53 |
33.77 |
21.46 |
Means with different alphabet are
significantly different at p ≤ 0.05
Relationship
between Growth and Yield Parameters of Selected Rice Genotype
Most
of the traits measured were significant and positively correlated with other
traits and had correlation magnitudes ranging from 0.45 to 1.00. Number of
tiller was significantly correlated with Weight of Seed per Plant, days to 50% flowering, days to maturity and Number of Panicles
per Plant. Significant correlation was also observed between leaf area index
and days to 50% flowering, days to maturity and panicle length (Table 4).
Table 4: Correlation Matrix of Relationship between Growth
and Yield Parameters of Selected Rice Genotypes
|
|
NT |
HT |
LA |
LAI |
BM |
WS |
DF |
DM |
NP |
PL |
WSP |
|
1000 |
|||||||||||
|
NT |
|||||||||||
|
HT |
-0.07 |
||||||||||
|
LA |
-0.21 |
0.86** |
|||||||||
|
LAI |
-0.21 |
0.86** |
1.00** |
||||||||
|
BM |
0.14 |
-0.12 |
-0.32 |
-0.32 |
|||||||
|
WS |
0.52** |
0.1 |
-0.12 |
-0.13 |
0.22 |
||||||
|
DF |
0.52** |
0.50* |
0.50* |
0.50* |
-0.02 |
0.17 |
|||||
|
DM |
0.52** |
0.50* |
0.50* |
0.50* |
-0.02 |
0.17 |
1.00** |
||||
|
NP |
0.88** |
0.09 |
-0.15 |
-0.15 |
0.17 |
0.74** |
0.45* |
0.45* |
|||
|
PL |
0.07 |
0.83** |
0.85** |
0.85** |
-0.099 |
-0.06 |
0.71** |
0.71** |
0.1 |
||
|
WSP1000 |
-0.38 |
0.2 |
0.38 |
0.38 |
-0.396 |
0.05 |
-0.15 |
-0.149 |
-0.39 |
0.04 |
|
|
**Correlation significant at 0.01 level, *Correlation significant at
0.05 level; NT = Number of tillers; HT = Plant height; LA = Leaf Area; LAI =
Leaf Area Index; BM = Biomass, DF = Days to Flowering; DM = Days to Maturity; NP =
Number of Panicles per Plant; PL = Panicle Length; WSP100g = Weight of 1000
Seeds, WS = Weight of Seed per Plant; |
|||||||||||
Cluster
Analysis of Rice Genotypes
Cluster analysis showed three optimal clusters/groupings (A, B and C) of the selected rice genotypes based on the growth and yield parameters measured as shown (Figure 1). Cluster A had two genotypes while cluster B had only WBK 114, which is interspecific hybrid between (O. sativa and O. glaberrima). The cluster with the highest number of genotypes is cluster C with 7 genotypes, anther-culture derived lines (Figure 1).

Figure 1:
Dendrogram of
Selected Rice Genotypes
DISCUSSION
Some
of the characteristics that can help increase rice production potential are the
number of tillers and plant height. Due to its large impact on panicle number
and number of tiller, it is crucial in determining eventual grain production.
Grain yield is hampered by insufficient tillers, while too many tillers result
in excessive tiller abortion, small panicle size, poor
grain filling, and even lower grain yield (Yang et al., 2006). Though
not significant, result from this study showed a negative relationship between
number of tillers and plant height which corroborates with reports (Yang et
al. 2006).
Panicle number is a crucial factor in
determining grain yield, and it was observed that crop management and
environmental factors have a significant impact on this key yield component (Garris cia
et al., 2005). Increasing the number of panicles is often how crop
management improvements are realized, which increases yield (Wang et al.,
2017). This study shows that the number of panicles is strongly and positively
correlated with the number of tillers, weight of seeds produced, days to 50%
flowering and days to maturity; this corroborate with earlier reports (Efisue et al.,2022). Thus, these lines could be promising
based on panicle number per plant UPN276, UPN228, UPN347 and UPN254. Due to
current erratic rainfall experienced over the globe, early maturing rice
varieties such as UPN 234 and UPN 268 could be introduced to rice farmers,
which can be cropped for two cropping seasons.
The leaf area and leaf area index could also
determine the efficiency of photosynthetic rate in plant (Quan
et al., 2017). It is an indication of the carbon dioxide absorption and
light intercepting capacity as well as the release of oxygen. Leaf area and
leaf area index in this study were significantly and positively correlated with
plant height, days to 50% flowering, maturity and panicle length. Leaf area has
been reported to increase from vegetative, reproductive to maturity phase of
rice development, which accounts for the positive relationship in the growth
variables measured in this study. Fagade and Datta (1971) reports the effect of
leaf area index on yield components such as increasing spikelet number which is
an important component of physical capacity for grain yield. WBK114 had the
largest leaf area and leaf area index and could be a promising rice variety.
Dendrogram showed that WBK114
is different from other rice varieties evaluated because it is an interspecific hybrid (O. sativa and O. glaberrima); this information will
assist the breeder in the selection of parent for crop improvement.
CONCLUSION
Rice
is a major staple food for the world population and serves as a good source of
energy for humans when consumed. The study showed significant difference in
morphological traits among the varieties studied, while significant
correlations were also observed among the measured traits. Using the traits
data from the rice varieties studied, significant differences and correlations
were observed between the agronomic traits and yield of the rice varieties. For
yield improvement, number of tillers, and number of panicles which had more
direct relationship with days to flowering, days to maturity and had indirect
correlations with yield component, should be focused on by rice breeders.
UPN234 and UPN268 are early maturing varieties and it can be recommended to
farmers to grow them because it is possible for the farmers to grow them in
three cropping season in a year which is of economic importance and value to
the farmers.
ACKNOWLEDGMENT
The
authors wish to express their gratitude to Korea-Africa Food and Agriculture
Cooperation Initiative (KAFACI), Rural Development Administration (RDA) of
Korea for providing the genetic materials (anther culture
derived rice) used for this study under the project KAR20190112.
REFERENCES
Ahmed, M. S. U., Khalequzzaman,
M., Bashar, M. K. and Shamsuddin, A. K. M. (2016). Agro-morphological,
physico- chemical and molecular characterization of
rice germplasm with similar names of Bangladesh.
Rice Science, 23: 211-218.
Akter, N., Begum, H., Islam, M.Z., Siddique, M.A. and Khalequzzaman,
M. 2018b. Genetic diversity in Aus rice (Oryza sativa L.) genotypes of Bangladesh.
Bangladesh Journal of Agricultural Research, 43: 253-266.
https://doi.org/10.3329/bjar.v43i2.37329
Akter, N., Islam, M.Z., Chakrabarty,T. and Khalequzzaman, M.
2018a. Variability, Heritability and diversity analysis for some morphological
traits in Basmati rice (Oryza sativa L.) genotypes. The
Agriculturists, 16: 01-14. http://dx.doi.org/10.3329/agric.v16i02.40338
Akter, N., Islam, M.Z., Siddique,
M.A., Chakrabarty,T., Khalequzzaman, M. and Chowdhury,
M.A. Z. 2016. Genetic diversity of Boro rice (Oryza sativa L.) landraces
in Bangladesh. Bangladesh Journal of Plant Breeding and Genetics, 29: 33-40.
https://doi.org/10.3329/bjpbg.v29i2.33948
Akter,
N., Khalequzzaman, M., Islam, M.Z., Mamun, M.A.A. and Chowdhury,
M.A.Z. 2018c.
Genetic variability and character association of quantitative traits in Jhum rice genotypes. SAARC Journal of Agriculture, 16:
193-203. https://doi.org/10.3329/sja.v16i1.37434
Augustina,
U.A., Iwunor, O.P. and Ijeoma,
O.R. (2013).
Heritability and character correlation among some rice genotypes for yield and
yield components. Journal of Plant Breeding and Genetics, 1: 73-84.
Efisue, A.A, Kang, K., Lee
, H. S.(2022). Performance of Korean Anther Culture
Derived Rice (O. sativa L.) Across Agroecological
System of Nigeria. American Journal of Agriculture and
Forestry. Vol. 10, No. 6, 2022, pp. 230-237. doi: 10.11648/j.ajaf.20221006.13
Efisue A. A, Tongoona, P, Derera, J, Ubi
B.E,and Oselebe, H.O.
(2009). Genetics of Morpho-Physiological Traits in
Segregating Populations of Interspecific Hybrid Rice Under
Stress and Non-Stress Conditions. Journal of Crop Improvement, 23:383–401, 2009
Fagade,
S. O., & De Datta, S. K. (1971). Leaf area index, tillering capacity, and grain yield of tropical rice as
affected by plant density and nitrogen level 1. Agronomy
Journal, 63(3), 503-506.
Fukai, S., L. Li, P.T. Vizmonte, and K.S.
Fischer. 1991. Control of grain yield by sink capacity and assimilate
supply in various rice (Oryza sativa) cultivars.
Experimental Agriculture 27:127-135.
Garris,
A.J., T.H. Tai, J. Coburn, S. Kresovich, and S. McCouch. 2005. Genetic structure and diversity in Oryza sativa L. Genetics 169:1631-1638.
IRRI
(International Rice Research Institute). (2013). Standard Evaluation System
(SES) for Rice (5th ed.). Los Banos,
Philippines. .
Jaccard, P. 1908. Nouvelles recherches
sur la distribution florale.
But. Soc. Vaudoise
Sci. Natur. 44: 223-270
Özer, H., E. Oral, and Ü. Dogru. 1999.
Relationships between yield and yield components on currently improved spring
rapeseed cultivars. Tropical Journal of Agriculture and Forestry 23:603-607.
Quan,
X., He, B., Yebra, M., Yin, C., Liao, Z., Zhang, X.,
& Li, X. (2017). A radiative
transfer model-based method for the estimation of grassland aboveground
biomass. International Journal of Applied Earth Observation and Geoinformation, 54, 159-168.
Rohlf, F. J. (2000). NTSys pc, Version 2.02j. Exeter software, Setauket, New York.
SAS
Institute Inc. (2003). SAS/STAT user’s guide, version 9.1.
Cary, NC: SAS Institute Inc.
Salim H.K., Efisue
A. A., Olasanmi, B.and Kang K.
(2021). Genetic variation and diversity analysis of rice (Oriza
sativa L.) based on quantitative traits for crop improvement. Greener Journal
of Agricultural Sciences Vol. 11(1), pp. 57-66, 2021
Sneath,
P.H.A. and R.R. Sokal, (1973). The
Principle and Practice of numerical classification. In: Numerical
Taxonomy, Kennedy, D. and R.B.Park (Eds.) Freeman,
San Francisco.
Statista, (2018) Cited on the 19th January, 2023.
Swofford,
D. L. and.Olsen, G.J. (1990). Phylogenetic
Reconstruction In. Molecular Systematics. Hills, D.M. and C. Moritz
(Eds.), Sinauer Associates, Sunderland, Pp 411-501.
Thomson,
M.J., Septiningsih. E.M., Suwardjo, F., Santoso, T.J., Silitonga, T.S. and McCouch, S.R.
(2007). Genetic diversity analysis of traditional and
improved Indonesian rice (Oryza sativa L.) germplasm using microsatellite markers. Theoritical and Applied Genetics, 114: 559–568.
http://dx.doi.org/10.1007/s00122-006-0457-1
Wang,
D., Huang, J., Nie, L., Wang, F., Ling, X., Cui, K.,
and Peng, S. (2017). Integrated crop management
practices for maximizing grain yield of double-season rice
crop. Scientific Reports, 7(1), 1-11.
Weng, J.H., T. Takeda, W. Agata, and
S. Hakoyama.
(1982). Studies on dry matter and grain production of rice
plants. 1. Influence of the reserved carbohydrate until heading stage
and the assimilation production during the ripening period on grain production.
Japanese Journal of Crop Science. 51:500-509.
Yang, G., Xing, Y., Li, S., Ding, J., Yue,
B., Deng, K., and Zhu, Y. (2006). Molecular dissection of developmental
behavior of tiller number and plant height and their relationship in rice (Oryza sativa L.). Hereditas, 143(2006),
236-245.
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Cite this Article: Agbodike,
OC; Efisue, AA (2023). Genetic Variability for Some
Morphological Traits in Lowland Rice (Oryza sativa L.). Greener
Journal of Agricultural Sciences, 13(1): 46-53. https://doi.org/10.5281/zenodo.7856904.
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