Interrelationship and Cause-effect Analysis among Morpho-physiological Traits in Biroin Rice of Bangladesh
The aim of this study was to find out genetic variability, interrelationship and cause effect analysis for morpho-physiological traits in Biroin rice varieties. Ten traditional fine Biroin rice cultivars were tested at research plot of Bangladesh Rice Research Institute, Gazipur, Bangladesh in Randomized Complete Block Design (RCBD) with three replications during Transplanting Aman season 2004. Statistically, significant variation was observed among tested materials for all the characters studied. The higher genotypic coefficient of variations was found in case of grains per panicle followed by grain yield/plant, 1000-grain weight and panicles per plant. High heritability was observed for all the tested characters except harvest index. High heritability with high genetic advance in percentage of mean was recorded for the characters grains per panicle, grain yield per plant and 1000-grain weight indicating role of additive gene action in the expression of these traits. Genotypic correlations were higher than the phenotypic correlations in most of the cases. Grains per panicle, panicle length, leaf area index, harvest index and chlorophyll content were the major characters contributing to grain yield as these traits were significantly and positively associated with grain yield per plant. Maximum contribution of more chlorophyll content to grain yield was observed in path analysis, which was followed by higher harvest index and grains per panicle through higher direct effect. Leaf area index, panicle length, days to maturity, grains per panicle, harvest index, 1000-grain weight and plant height had positive but indirect effect on grain yield through chlorophyll content. Similar trends were also observed in harvest index through leaf area index, panicles per plant, days to flowering, grains per panicle, chlorophyll content and panicle length. So for increasing grain yield per plant a Biroin rice cultivar should have more number of grains per panicle, large panicle length, high harvest index, high leaf area index value and more chlorophyll content.
March 01, 2011; Accepted: April 20, 2011;
Published: May 21, 2011
Rice (Oryza sativa L.) is the staple food crop of more than half of
the worlds population (Anonymous, 2009). Ninety
percent of this crop is grown and consumed in South and South East Asia, the
major centers of the worlds population (Nanda, 2002).
Most of the consumers, who depend on rice as their primary food, live in less
developed countries. Bangladesh is the fourth largest producer and consumer
of rice in the world (Bhuiyan et al., 2002).
In sub continent thousands of locally adapted genotypes of rice have evolved
by nature and human (Singh et al., 2000), many
of which are either fine grain or aromatic types. Biroin is one of the fine
grain rice. The information on the quantitative and qualitative traits of Biroin
rice varieties is still lacking in Bangladesh and may have some special characteristics
to be essential for future breeding program. As these genotypes are traditional
and low yielder so the yield performances of these genotypes need to be improved.
For successful utilization of Biroin rice genotypes in yield improvement-breeding
programs, selection criteria of these genotypes need to be found out. The progress
in breeding for yield and its contributing characters of any crop is polygenic
controlled, environmentally influenced and determined by the magnitude and nature
of their genetic variability in which they grown (Falconer
and Mackay, 1996; Singh et al., 2000). Genetic
variability, interrelationship and cause effect analysis are pre-requisites
for improvement of any crop including rice for selection of superior genotypes
and improvement of any trait (Krishnaveni et al.,
2006). It is very difficult to judge whether observed variability is highly
heritable or not. Moreover, knowledge of heritability is essential for selection
based improvement as it indicates the extent of transmissibility of a character
into future generations. The knowledge of association i.e., genotypic and phenotypic
correlation between yield and its component characters is essential for yield
improvement through selection programmes (Ismail et al.,
2001; Kumar and Sukla, 2002). Cause-effect analysis
provides an effective means of partitioning the correlation coefficients into
direct and indirect effects of the component characters on yield on the basis
of which crop improvement programmes can be logically devised (Kozak
et al., 2007). Any successful hybridization program for varietals
improvement depends mainly on the selection of parents having high genetic variability
so that desired character (s) combinations may be selected to improve grain
quality and higher grain yield. Keeping in view the above facts, the present
study was undertaken to find out genetic variability, interrelationship and
selection criteria for yield and yield components in traditional Biroin rice
MATERIALS AND METHODS
The experiment was conducted at Bangladesh Rice Research Institute, Gazipur,
Bangladesh during T. Aman season, 2004. The trail consisted of 10 local Biroin
rice varieties collected from Sylhet and greater Mymensingh region of Bangladesh.
The trail was set in a Randomized Complete Block Design (RCBD) with three replications.
Thirty-five days old seedlings grown in wet seedbed were transplanted in 3.4x2.4
m-2 plots with a spacing of 20x25 cm, using single seedling per hill.
Fertilizers were applied @ 60:40:40 kg NPK ha-1. All other recommended
nutrients were applied except nitrogen at final land preparation. Nitrogen was
applied in three equal splits, at 15 Days After Transplanting (DAT), 45 DAT
and just before panicle initiation. Intercultural operations and pest control
measures were employed as when necessary during whole growing period. Leaf chlorophyll
content and leaf area for calculating leaf area index were measured by using
Japanese SPAD and leaf area meter, respectively. At maturity, grain yield was
taken excluding border area and yield was adjusted at 14% moisture level. Data
were recorded on ten characters, viz., plant height in cm (Ph), Days to Maturity
(DM), Panicles per plant (PN), Harvest Index (HI), leaf area index in cm-2
(LAI), Chlorophyll content (CHL) and Grain Yield in g (GY) from ten randomly
selected plants from each plot. Again panicle characters viz., Panicle Length
in cm (PL), Grains per panicle (GN), 1000-grain weight in g (GW) were recorded
from 10 randomly selected panicles at maturity stage from each plot.
The analysis of variance was done according to the MSTAT C software. The components
of variance including error variance (σ2e) genotypic
variance (σ2g) and phenotypic variance (σ2p)
were estimated, according to the following formula:
Heritability (h2) was studied based on formula (σ2g/σ2p)
stated by Singh and Ceccarelli (1996). The coefficient
of genotypic and phenotypic variation was evaluated according to Burtons
formula (Burton, 1952) as the square root of σ2g
and σ2p divided by the mean and converted into
percentage, and the genetic advanced was estimated based on formula of GA =
(k) (h2) (
). Here 2.06 values for k, was used to obtain the GA. The phenotypic and genotypic
correlation between variable x and y (r(xy)p and r(xy)g),
were also estimated by following formula:
Where, Cov(x,y)p and Cov(x,y)g are phenotypic and genotypic
covariance between variable x and y respectively. Finally the cause effect analysis
i.e., path analysis was done to partition the correlation coefficients of independent
variable with the dependent variable into direct and indirect effects using
following formula described in Fig. 1 and Table
In Fig. 1 and Table 1 nine independent (cause) variables were: 1) Plant height, 2) days to flowering, 3) panicles per plant, 4) panicle length, 5) grains per panicle, 6) 1000-grain weight, 7) harvest index, 8) leaf area index and 9) chlorophyll content and dependent (effect) variable was 8) grain yield per plant.
The analysis of variance revealed highly significant variations among the varieties for all the characters studied (Table 2), indicated presence of variation for all the characters among the population. The phenotypic variance was partitioned into genotypic and environmental variances for a clear understanding of the pattern of variations.
The highest genotypic, phenotypic and environmental variance was found in grains per panicle. The lowest magnitude of genotypic, environmental and phenotypic variance was recorded in harvest index.
||Diagrammatic sketch of ten characters of bironi rice varieties
are showing dependent (left) and independent (right) variables
|| Symbolic formula of total effect i.e. total correlation direct
and indirect effect
The highest GCV and PCV were obtained from grains per panicle (20.45 and 21.89)
followed by grain yield per plant (15.27 and 16.70), 1000-grain weight (14.42
and 15.68) and panicles per plants (10.10 and 10.85), indicated presence of
high variation and role of environment on the expression of these traits.
The estimates of heritability were varied from 40.90 to 95.89 % (Table
2). Days to flowering exhibited high heritability (95.89%) followed by plant
height (92.92%), grains per panicle (87.28%), panicles per plant (86.70%), 1000-grain
weight (84.61%) and grain yield per plant (83.56%).
|| Estimation of statistical and genetical parameters of morpho-physiological
characters for different genotypes of biroin rice
|** Significant at 1% level of probability, * Significant at
5% level of probability. MS: Mean square, σ2p: Phenotypic
variance, σ2g: Genotypic variance, σ2e:
Environmental variance, PCV: Phenotypic coefficient of variation, GCV: Genotypic
coefficient of variation, ECV: Environmental coefficient of variation, GA:
Genetic advance, PH: Plant height (cm), DF: Days to flowering, PN: Panicles
per plant, PL: Panicle length (cm), GN: Grains per panicle, GW: 1000-grain
weight (g), HI: Harvest index, LAI: Leaf area index (cm2), CHL:
Chlorophyll content, GY: Grain yield/plant (g)
|| Correlation coefficients among different pairs of morpho-physiological
characters for different genotypes of biroin rice
|**Significant at 1% level of probability, * Significant at
5% level of probability. G: Genotypic correlation, P: Phenotypic correlation
DF: Days to flowering, PL: Panicle length (cm), PN: Panicle per plant, GN:
Grains per panicle, GW: 1000-grain weight, HI: Harvest index, LAI: Leaf
area index (cm2), CHL: Chlorophyll content
Accordingly, high genetic advance in percent of mean exhibited by grains per panicle (39.35) which followed by grain yield per plant (28.75) and 1000-grain weight (27.32). High heritability associated with high genetic advance percent of mean obtained in grains per panicle, 1000-grain weight and grain yield per plant.
|| Path coefficient showing direct and indirect effects of morpho-physiological
characters on grain yield of boroin rice
|Residual effect, R = 0.2658 ** Significant at 1% level of
probability, * Significant at 5% level of probability. DF: Days to flowering,
PL: Panicle length (cm), PN: Panicle per panicle, GN: Grains per panicle,
GW: 1000-grain weight, HI: Harvest index, LAI: Leaf area index (cm2),
CHL: Chlorophyll content
Genotypic and phenotypic correlation coefficients studied (Table
3) among yield and yield contributing morpho-physiological traits of Biroin
rice revealed that panicle length, grains per panicle, harvest index, leaf area
index and chlorophyll content exhibited significant and positive association
with grain yield per plant. On the contrary, 1000-grain weight exhibited negative
association with grain yield per plant.
From the path analysis (Table 4) it was revealed that trait chlorophyll content (1.681) exhibited maximum positive direct effect on grain yield followed by harvest index (1.244) and filled grains per panicle (0.411).
The analysis of variance revealed highly significant variations among the varieties
for all the characters studied, indicated presence of variation for all the
characters among the population. High genetic variability for different quantitative
traits in rice was also reported earlier by Umadevi et
al. (2009), Akter et al. (2004), Hossain
and Haque (2003) and Pandey and Awasthi (2002).
Genotypic and phenotypic coefficient of variation indicated that the magnitude
of GCV and PCV was highest in case of grains per panicle followed by grain yield
per plant, 1000-grain weight and panicles per plant, indicated presence of high
variation and role of environment on the expression of these traits. The magnitudinal
differences were medium to low in GCV and PCV for Plant height, days to flowering,
panicle length and chlorophyll content suggesting the little role of environment
in the expression of these characters. These findings were in agreement with
the findings of Pushpa et al. (1999), Venkataramana
et al. (1999), Kumar et al. (1998)
and Kaw et al. (1999).
Plant height, days to flowering, panicles per plant, grains per panicle, 1000-grain
weight and harvest index exhibited high heritability supported these with the
findings of Iftekharudduaula et al. (2001) and
Karthikeyan et al. (2010). High heritability
have been found to be effective in the selection of superior genotypes on the
basis of phenotypic performance. High heritability associated with high genetic
advance percent of mean obtained in grains per panicle that was supported by
Bagheri et al. (2008) and grain yield per plant
that supported by Manickavelu et al. (2006).
1000-grain weight and grain yield per plant also showed high heritability and
high genetic advance percent of mean were in agreement with the results of Chaudhury
and Das (1998) and Shanthi and Singh (2001). High
heritability along with low genetic advance indicates non-additive type of gene
action and genotype-environment interaction plays a significant role in the
expression of the trait as observed in days to flowering. Grains per panicle,
1000-grain weight and grain yield per plant had high heritability with high
genetic advance in percentage of mean made these three characters most effective
in the selection of best Biroin rice varieties. High GCV, PCV, heritability
and GA% mean of grains per panicle and grain yield per plant suggested that
these two characters could be transmitted to the progeny when hybridization
would be conducted and phenotypic based selection on these would be effective.
The correlation coefficient showed grains per panicle serve as most important
selection indices of grain yield. Meenakshi et al.
(1999) and Mustafa and Elsheikh (2007), Janardhanam
et al. (2001), Rao and Saxena (1999), Ray
and Debi (1999) and Pushpa et al. (1999)
emphasized the importance of grains per panicle in determining grain yield in
rice. Chakraborty and Chakraborty (2010), Hossain
and Haque (2003), Singh et al. (2002) and
Biswas et al. (2000) reported positive significant
association of panicle length with grain yield per plant. Kole
et al. (2008), Jayasudha and Sharma (2010)
and Saif-ur-Rasheed et al. (2002) in rice and
Kotal el al. (2010) in wheat reported similar
finding that is harvest index exhibited significant and positive association
with grain yield per plant. Chlorophyll content revealed significant positive
correlation with yield which was supported the results of Poshtmasari
et al. (2007).
Chlorophyll content exerted highest direct effect on grain yield reported by
Akter et al. (2004) in rice. This indicates that
more chlorophyll content of leaf of plant is highly reliable component on grain
yield by supporting in photosynthesis.
Another important character with high direct effect on seed yield is harvest
index showed positive direct effect on seed yield, which were earlier reported
by Jayasudha and Sharma (2010), Iftekharudduaula
et al. (2001) and Surek et al. (1998).
Data analysis revealed that grains per panicle had the highest genotypic correlation
coefficient and accordingly chlorophyll content had the maximum direct effect
on grain. Hence, grains per panicle and chlorophyll content should be given
prior attention in Biroin rice improvement programme because of their major
influence on yield. The residual effect was 0.2658, indicated that the contribution
of component characters on grain yield was 73.5% by the ten characters studied
in path analysis, the rest 26.5% was the contribution of other factors such
as characters not studied and sampling error.
From this study it is clearly observed that grains per panicle, panicle length, leaf area index, harvest index and chlorophyll content appeared most yield contributing characters for local Biroin rice. Further study with different Biroin rice varieties of Bangladesh may help confirmation of this study as well as genetic improvement for yield potentiality of local Biroin rice.
Akter, K., K.M. Iftekharuddaula, M.K. Bashar, M.H. Kabir and M.Z.A. Sarker, 2004. Genetic variability, correlation and path analysis in irrigated hybrid rice. J. Subtrop. Agric. Res. Dev., 2: 17-23.
Anonymous, 2009. Annual report for 2008. IRRI, Los Banos, Philippines.
Bagheri, N., N.B. Jelodar and A. Ghanbari, 2008. Diallel analysis study of yield and yield-related traits in rice genotypes. Int. J. Agric. Res., 3: 386-396.
CrossRef | Direct Link |
Bhuiyan, N.I., D.N.R. Paul and M.A. Jabber, 2002. Feeding the extra millions by 2025-challenges for rice research and extension in Bangladesh. Proceedings of the National Workshop on Rice Research and Extension, 2002, Jan. 29-31, Bangladesh Rice Research Institute, Joydebpur, pp: 9-9.
Biswas, P.S., B. Prasad and S.B.A. Dewan, 2000. Variability, character association and path analysis in rice (Oryza sativa L.). Bangladesh J. Plant Breed. Genet., 13: 19-25.
Burton, G.W., 1952. Quantitative inheritance in grasses. National Publishing Co., Washington D.C., New York, pp: 277-283.
Chakraborty, R. and S. Chakraborty, 2010. Genetic variability and correlation of some morphometric traits with grain yield in bold grained rice (Oryza sativa L.) gene pool of Barak valley. American-Eurasian J. Sustainable Agric., 4: 26-29.
Chaudhury, P.K.D. and P.K. Das, 1998. Genetic variability, correlation and path coefficient analysis in deep water rice. Ann. Agric. Res., 19: 120-124.
Falconer, D.S. and T.F.C. Mackay, 1996. Introduction to Quantitative Genetics. 4th Edn., Benjamin Cummings, England, ISBN-13: 9780582243026, Pages: 464.
Hossain, M.A. and M.H. Haque, 2003. Genetic variability and path analysis in rice genotypes. Bangladesh J. Pl. Breed. Genet., 16: 33-37.
Iftekharudduaula, K.M., M.A. Badshah, M.S. Hossain, M.K. Basher and Akter Khaleda, 2001. Genetic variability, character association and path analysis of yield components in irrigated rice (Oryza sativa L.). Bangladesh J. Pl. Breed. Genet., 14: 43-49.
Ismail, A.A., M.A. Khalifa and K.A. Hamam, 2001. Genetic studies on some yield traits of durum wheat. Asian J. Agric. Sci., 32: 103-120.
Janardhanam, V., N. Nadarajan and S. Jebaraj, 2001. Correlation and Path analysis in rice (Oryza sativa L.). Madras Agric. J., 88: 719-720.
Jayasudha, S. and D. Sharma, 2010. Genetic parameters of variability, correlation and path-coefficient for grain yield and physiological traits in rice (Oryza sativa L.) under shallow lowland situation. Electronic J. Plant Breed., 1: 1332-1338.
Karthikeyan, P., Y. Anbuselvam, R. Elangaimannan and M. Venkatesan, 2010. Variability and heritability studies in rice (Oryza sativa L.) under coastal salinity. Electronic J. Plant Breed., 1: 196-198.
Kaw, R.N., R.C. Aquino, H.P Moon, J.D. Yae and N. Haq, 1999. Variability and interrelations in rice under cold stress environment. Oryza, 36: 1-4.
Kole, P.C., N.R Chakraborty and J.S. Bhat, 2008. Analysis of variability, correlation and path coefficients in induced mutants of aromatic non-basmati rice. Tropic. Agric. research and extension, 11. http://www.sljol.info/index.php/TARE/article/view/1791.
Kotal, B.D., A. Das and B.K. Choudhury, 2010. Genetic variability and association of characters in wheat (Triticum aestivum L.). Asian J. Crop Sci., 2: 155-160.
CrossRef | Direct Link |
Kozak, M., K.P. Singh, M.R. Verma and D.K. Hore, 2007. Causal mechanism for determination of grain yield and milling quality of lowland rice. Field Crops Res., 102: 178-184.
Krishnaveni, B., N. Shobharani and A.S. Ramprasad, 2006. Genetic parameters for quality characteristics in aromatic rice. Oryza, 43: 234-237.
Kumar, G.S., M. Mahadevappa and M. Rudradhya, 1998. Studies on genetic variability, correlation and path analysis in rice during winter across the locations. Karnataka J. Agric. Sci., 11: 73-77.
Kumar, P. and R.S. Shukla, 2002. Genetic analysis for yield and its attributed traits in bread wheat under various situation. JNKVV Res. J., 36: 95-97.
Manickavelu, A., R.P. Gnanamalar, N. Nadarajan and S.K. Ganesh, 2006. Genetic variability studies on different genetic populations of rice under drought condition. J. Plant Sci., 1: 332-339.
CrossRef | Direct Link |
Meenakshi, T., A.A.D. Ratinam and S. Backiyarani, 1999. Correlation and path analysis of yield and some physiological characters in rain fed rice. Oryza, 6: 154-156.
Mustafa, M.A. and M.A.Y. Elsheikh, 2007. Variability, correlation and path co-efficient analysis for yield and its components in rice. Afr. Crop Sci. J., 15: 183-189.
Direct Link |
Nanda, J.S., 2002. Rice Breeding and Genetics: Research Priorities and Challenges. Oxford and IBH Publishing Co. Pvt. Ltd., New Delhi, pp: 1-15.
Pandey, V.K. and L.P. Awasthi, 2002. Studies on genetic variability for yield contributing traits in aromatic rice. Crop Res., 23: 214-218.
Poshtmasari, H.K., H. Pirdashti, M. Nasiri and M.A. Bahmanyar, 2007. Chlorophyll content and biological yield of modern and old rice cultivars in different urea fertilizer rates and applications. Asian J. Plant Sci., 6: 177-180.
CrossRef | Direct Link |
Pushpa, K., D.N. Singh, M.P. Singh, M.F. Haque and P. Kumari, 1999. Genetic variability in gora rice (Oryza sativa L.). J. Res., 11: 23-26.
Rao, S.S. and R.R. Saxena, 1999. Correlation and regression analysis in upland rice. Oryza, 36: 82-84.
Ray, P.K.S. and B.P. Debi, 1999. Correlation response and path analysis in irrigated rice and their implication in selection. J. Bio-Sci., 7: 99-101.
Saif-ur-Rasheed, M., H.A. Sadaqat and M. Babar, 2002. Correlation and path co-efficient analysis for yield and its components in rice (Oryza sativa L.). Asian J. Plant Sci., 1: 241-244.
CrossRef | Direct Link |
Shanthi, P. and J. Singh, 2001. Variability studies in induced mutants of Mahsuri rice (Oryza sativa L.). Madras Agric. J., 88: 707-709.
Singh, L., J.D. Singh, and N.S. Sachan, 2002. Intercharacter association and path analysis in paddy (Oryza sativa L.). Annals Biol., 18: 125-128.
Direct Link |
Singh, M. and S. Ceccarelli, 1996. Estimation of heritability of crop traits from variety trial data. Technical Manual International Center for Agricultural Research in the Dry Areas, Aleppo, Syria, pp: 21.
Singh, R.K., P.L. Gautam, S. Saxena and S. Singh, 2000. Scented Rice Germplasm: Consevation, Evaluation and Utilization. In: Aromatic Rices, Singh, R.K., U.S. Singh and G.S. Khush (Eds.). Oxford and IBH Publishing Co. Pvt. Ltd., New Delhi, pp: 107-133.
Surek, H., Z.K. Korkut and O. Bilgin, 1998. Correlation and path analysis for yield and yield components in rice in a 8-parent half diallel set of crosses. Oryza, 35: 15-18.
Umadevi, M., P. Veerabadhiran and S. Manonmani, 2009. Genetic variability, heritability, genetic advance and correlation for morphological traits in rice genotypes. Madras Agric. J., 96: 316-318.
Venkataramana, P., Shailaja Hittalmani and S. Hittalamani, 1999. Genetic variability on some important trits in two F2 segregants of rice (Oryza sativa L.) under non-submergence condition. Crop Res. Hisar., 18: 53-56.