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*Corresponding author’ e-mail: lalitha_email@yahoo.com.

Agric. Sci. Digest, 35 (1) 2015: 25-30Print ISSN:0253-150X / Online ISSN:0976-0547

Studies on genetic variability and character association for yield and itsattributes in chrysanthemum (Dendranthema grandiflora Tzvelev)P. Lalitha Kameswari*, M. Pratap, Hameedunnisabegum and G. Anuradha

Floricultural Research Station,Dr. Y.S.R. Horticultural University, Rajendranagar, Hyderabad-500 001, India.Received: 21-02-2014 Accepted: 13-11-2014 DOI: 10.5958/0976-0547.2015.00005.1

ABSTRACTOne hundred and four divergent genotypes of chrysanthemum were evaluated to study their genetic variability, correlationsand path coefficients during 2011-12. Higher estimates for GCV and PCV were observed for all the characters studiedexcept for plant height, days to flowering, spray length and duration of flowering showing ample scope for selection of thosecharacters. High heritability coupled with high genetic advance as percentage of mean was recorded for all the quantitativecharacters studied except for duration of flowering. A significant positive correlation both at genotypic and phenotypiclevels was recorded between flower yield and plant attributes viz., plant spread at both the directions, number of primarybranches per plant, spray length and number of flowers per spray. Path coefficient analysis revealed that plant spread in N-S direction recorded the highest direct effect on flower yield per plant followed by number of flowers per spray, days to 50%flowering, number of primary branches per plant, average flower weight and duration of flowering. Hence the direct selectionfrom germplasm lines for these characters may be effective for further improvement of the crop.

Key words: Chrysanthemum, Correlation and path coefficient, Variability analysis.

INTRODUCTIONChrysanthemum (Dendranthema grandiflora

Tzvelev) the “queen of the east” is a popular flower cropbeing cultivated for its pleasant and long lasting blossoms. Itis the national flower of Japan and is regarded as a symbol ofroyalty. It is one of the most widely cultivated garden flowersand there is hardly any other garden flower which has suchdiverse and beautiful range of colours, shades, wide flowershapes and height ranges. In India it occupies a place of prideboth as commercial flower crop and as a popular exhibitionflower. Because of its multifarious traditional uses, the crophas its own commercial value and of late good number ofvarieties has been released.

Crop improvement depends upon the magnitude ofgenetic variability and the extent to which the desirablecharacters are heritable. The total variability can be partitionedinto heritable and non heritable components with the help ofgenetic parameters like phenotypic and genotypic coefficientof variation, heritability and genetic advance. Genotypic andphenotypic coefficients of variation are useful in detecting theamount of variability present in the genotypes (Kumar et al,2012). Selection is effective only when the observed variabilityin the population is heritable in nature (Jhon et al, 2006). Burton(1952) suggested that genetic variation along with heritability

estimates would give a better idea about the efficiency ofselection. The yield is the end product of interactions of manyfactors known as contributing components, hence, it is a complextrait. As the breeders are always interested in the improvementof several economic characters including yield, the knowledgeof correlation among the traits is important to have the idea ofconcurrent changes which would be brought about in other traitswhile making selection for one trait (Bhatia, 2004). The natureand the extent of association among the traits is of greatimportance for planning an efficient breeding programme(Panwar et al, 2012). Path coefficient analysis measures the directeffect of variable upon another and permits the separation of thecorrelation coefficients into components of direct and indirecteffects. It will not only help to understand the desirable andundesirable relationship of economic traits but also help inassessing the scope of simultaneous improvement of two or moreattributes. Therefore, present investigation was undertaken toestimate associations among desired traits and their direct andindirect contribution towards yield.

MATERIALS AND METHODSOne hundred and four genotypes of chrysanthemum

were planted during Kharif season of 2012 at FloriculturalResearch Station, (Dr. YSR Horticultural University,

26 AGRICULTURAL SCIENCE DIGEST

Hyderabad, which is situated at an altitude of 542.3m above sealevel on 17.900 North latitude and 78.230 East Longitude. Therooted cuttings were transplanted in the main field in augumentedblock design. Each genotype was grown in a single row plot of9 m consisting of 30 plants spaced at 30 x 30 cm. Therecommended agronomical practices and plant protectionmeasures were followed to raise a normal crop. Observationswere recorded on five randomly selected plants from each linefor thirty characters viz., plant height (cm), plant spread E –Wdirection (cm), plant spread in N –S direction (cm), number ofprimary branches per plant, length of the petiole(cm), terminallobe length(cm), leaf length (cm), leaf width (cm), depth of thesinus(cm), internodal length(cm), days to first flower budappearance, days to 50% flowering, inflorescence width(cm),spray length(cm), bud width(mm), average flower weight(g),flower diameter(cm), peduncle length(cm), pedunclediameter(mm), number of ray florets/head, ray floret length(cm),

ray floret width(cm), ratio of ray floret length : width, discdiameter(cm), number of disc florets/head, disc floret length(cm),number of flowers per spray, number of flowers/plant, durationof flowering and number of suckers/plant.

The data recorded on various characters wassubjected to statistical analysis and both genotypic andphenotypic coefficients of variability were computed as perthe method suggested by Burton and Devane (1953).Heritability in broad sense has been estimated as per theformula given by Lush (1940). Genetic advance as per centof mean was worked out for each character adopting theformula given by Johnson et al, (1955). Both genotypic andphenotypic coefficients of correlation between two characterswere determined by using the variance and covariancecomponents as suggested by Al-Jibouri et al, (1958). Pathcoefficient analysis was carried out using phenotypiccorrelation values of yield components on yield as suggestedby Wright (1921) and illustrated by Dewey and Lu (1959).

Character Mean Range PCV GCV Heritability (%) Genetic Advance as per cent Mean (%)

Plant Height (cm) 40.61 23.22-60.75 17.50 17.41 99.00 35.68 Plant Spread in E-W direction (cm) 24.21 11.81-57.03 28.61 28.51 99.30 58.54 Plant Spread in N-S direction (cm) 24.23 13.34 - 69.99 28.62 28.59 99.80 58.84 No.of primary Branches/ Plant 8.50 3.73 - 30.92 38.10 38.08 99.90 78.41 Petiole Length (cm) 1.86 0.53 - 4.10 33.23 31.65 90.70 62.08 Terminal lobe length (cm) 1.93 0.53 - 4.72 31.78 30.97 95.00 62.17 Leaf lamina Length(cm) 5.07 1.80 - 8.70 22.37 22.26 99.90 45.63 Leaf lamina width (cm) 3.94 1.52 - 6.66 22.13 22.04 99.20 45.21 Depth of the sinus (cm) 1.26 0.23 - 2.78 34.85 34.37 97.30 69.83 Internodal length (cm) 1.84 0.42 - 4.01 34.47 34.14 98.10 69.66 Days to first flower bud appearance 78.71 48.99 - 133.59 15.89 15.72 97.90 32.06 Days to 50% flowering 92.51 53.97 - 138.73 12.24 12.15 98.50 24.83 Inflorescence width (cm) 37.29 18.94 - 71.79 25.55 25.50 99.60 52.41 Spray length (cm) 16.80 7.29 - 31.84 19.84 19.79 99.50 40.68 Bud width (mm) 9.92 4.27 - 18.59 28.25 27.98 98.00 57.06 Avg. flower weight (g) 2.49 0.61 - 9.00 66.69 66.55 99.60 136.81 Flower diameter (cm) 5.00 2.10 - 8.89 28.44 28.39 99.70 58.38 Peduncle length (cm) 5.56 2.56 - 10.14 25.34 25.29 99.60 51.99 Peduncle diameter (mm) 2.32 0.88 - 4.73 29.09 28.82 98.20 58.82 Ray florets/head 170.70 10.98 - 406.71 55.74 55.70 99.80 114.65 Length of ray floret (cm) 2.66 0.68 - 5.39 33.28 32.89 97.70 66.97 Width of ray floret (cm) 0.67 0.15 - 1.54 31.73 31.65 99.50 65.03 Ray floret length : width 4.23 1.37 - 24.00 45.78 45.54 99.00 93.32 Disc diameter (cm) 1.28 0.00 - 3.34 51.38 51.37 100.00 105.800 No. of disc florets/head 109.32 0.00 -300.64 60.51 60.50 100.00 124.61 Length of disc florets (cm) 0.70 0.00 - 1.76 48.96 48.94 99.90 100.78 No. of flowers/spray 7.60 2.95 - 23.30 41.23 40.34 95.70 81.32 No. of flowers/plant 101.77 5.81 -298.54 55.21 54.87 98.80 112.35 Duration of flowering 45.35 36.22 -70.35 9.58 9.23 92.90 18.33 No. of suckers/plant 15.00 0.00 - 54.46 69.85 69.7 99.6 143.28

TABLE 1: Estimates of variability and genetic parameters for yield and yield attributes in chrysanthemum

Volume 35 Issue 1 (2015)

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7***RESULTS AND DISCUSSION

Critical estimates of the genetic parameters, viz.,phenotypic coefficient of variation (PCV), genotypiccoefficient of variation (GCV), heritability in broad senseand genetic advance as per cent mean were presented inTable 1. Analysis of variance revealed highly significantdifference among the genotypes for all the characters. A widerange of variability was recorded for number of disc florets(0.0 – 300.64) and ray florets (10.98-406.71) per head andnumber of flowers/plant (5.81-298.54). This wassupplemented by higher values of both genotypic coefficientof variation (GCV) and phenotypic coefficient of variation(PCV)for these characters. Relatively low level of geneticvariability was recorded for number of suckers/plant and daysto 50% flowering. Similar kind of high GCV and PCV fornumber of flowers per plant was reported earlier by Singhand Sen (2000), Nandkishore and Raghava (2001) in marigoldand Ravi Kumar and Patil (2003) in Chinaster. It is interestingto note that the differences between GCV and PCV valueswere minimum implying least influence of environment andadditive gene effects indicating that the genotypes can beimproved and selected for these characters. High heritabilitycoupled with high genetic advance as percentage of mean wasrecorded for all the characters studied except for duration offlowering indicating contribution of additive gene effectsin the expression of these traits. Therefore improvement inthese characters can be done through direct selection to selectbetter genotypes of chrysanthemum. Burton and de Vane (1953)suggested that high GCV along with high heritability andgenetic advance gave a better indication for selection ofgenotypes. Similar kind of high estimates of heritability coupledwith high genetic advance as percentage of mean were reportedby Balamurugan et al, (2002) in gladiolus, Sheela et al,(2007)for number of flowering shoots/year in heliconias and Bhatiaet al, (2013) in tulips. High estimates of heritability coupledwith moderate genetic advance as per cent of mean wasrecorded for duration of flowering suggesting that the characteris governed by dominant and epistatic gene action and needsfurther improvement of genotypes for this character for furtherselection and subsequent use in breeding programme.

Correlation studies were carried out to reveal thenature and extent of association between different traits(Table 2). In the present study the genotypic correlation washigher than phenotypic correlation indicating less influenceof environmental factors and relative stability of theaccessions. Similar results were reported by Bhaskaran et al,(2004) in Chrysanthemum.

A significant positive correlation both at genotypicand phenotypic levels was recorded between flower yieldand plant attributes viz., plant spread at both the directions,number of primary branches per plant, spray length and

28 AGRICULTURAL SCIENCE DIGEST

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281

Volume 35 Issue 1 (2015)

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number of flowers per spray. The magnitude of correlationwith flower yield was highest in case of number of flowers perspray followed by characters viz., plant spread in both thedirections, number of primary branches per plant and lengthof the spray, indicating that the association between yield andthese characters was positive and high. These results are inaccordance with those reported by Reena et al, (2005), DeeptiSingh and Santosh Kumar (2008), Singh and Singh (2005) inmarigold. This indicates that flower yield in chrysanthemumcan be improved by direct selection of these characters.

Other characters like days to first flower budappearance, days to 50% flowering and duration of floweringrecorded positive but non-significant correlation with floweryield both at genotypic and phenotypic levels. On the otherhand, characters like bud width, average flower weight andflower diameter showed negative correlation with floweryield both at phenotypic and genotypic levels indicating thatthe association between these two traits was negative andhigh. These results are in consonance with those reported bySirohi and Behera (1999), Pal and George (2002), Deka andPaswan (2002) and Bhaskaran et al, (2004).

The correlation coefficient between flower yield perplant and its component characters were positioned into theircorresponding direct and indirect effects through pathcoefficient analysis. The estimates of path coefficient fordifferent attributes on flower yield were presented inTable 3. Plant spread in N-S direction recorded the highestdirect effect on flower yield per plant followed by number offlowers per spray, leaf length, days to 50% flowering, numberof primary branches per plant, average flower weight andduration of flowering. The high direct effect of these traitsappeared to be the main factor for their strong associationwith flower yield per plant. Hence, direct selection for thesetraits would be highly effective in improving the per plantflower yield.

Plant spread in N-S direction showed a high indirectpositive effect on flower yield per plant via plant spread in E-W direction followed by number of flowers per spray, numberof primary branches per plant and spray length. As plant spreadin N-S direction influences flower yield per plant through thesecharacters, indirect selection for plant spread in N-S directionvia the aforesaid characters may be useful in improving theyield. Since this trait is showing high positive correlation andhigh direct effect on flower yield per plant, one can improvethe flower yield in chrysanthemum by making selection forthis character during the yield improvement programme.

Along with the high direct positive effect, numberof flowers per spray exhibited a positive indirect effect toflower yield via plant spread in both the directions and spraylength. This suggests that emphasis must be given on such

30 AGRICULTURAL SCIENCE DIGEST

traits while exercising selection to improve the flower yieldin chrysanthemum. Therefore, it would be rewarding to stresson plant spread in N-S direction and number of flowers perspray while making selections. These traits also had highcorrelation and high direct effect on flower yield per plant.

CONCLUSIONThe results of the study indicated that the characters

with positive correlation have shown high direct effects.

Hence, it can be concluded that plant spread in N-S directionand number of flowers per spray are the highly importantyield attributing components in the order of having directbearing on the improvement of flower yield per plant. Theresidual effect in the present study was found to be high inpath analysis indicating that there is a need to include othercharacters in order to derive a much clear picture of the causalrelationship.

REFERENCESAl-Jibouri, H A, Miller, P A and Robinson, H V (1958) Genotypic and environmental variances and co-variances in an

upland cotton cross of inter specific origin. Agronomy Journal, 50:533-536.Burton, G N (1952) Quantitative Inheritance in Grasses. Proceedings of sixth international Grassland congress 1: 277-283.Burton, G W and Devane, E H (1953) Estimating heritability in tall fescue (Festuca arundinaceae) from replicated clonal

material. Agronomy Journal, 45: 478-481.Balamurugan, Rengasamy, P and Arumugam (2002) Variability studies in gladiolus. Journal of Ornamental Horticulture,5(1): 38–9.Bhaskaran, V, Janakiram, T and Jayanthi, R (2004) Correlation and Path coefficient analysis studies in chrysanthemum.

Journal of Ornamental Horticulture, 7(3-4): 37-44.Bhatia, R (2004) Genetic variability and correlation studies in gladiolus. M Sc thesis, Punjab Agricultural University, Ludhiana.Bhatia, R, Dhiman, M R, Chander Prakash and Dey, S S (2013) Genetic variability and character association in tulip (Tulipa

gesneriana) for various quantitative traits. Indian Journal of Agricultural Sciences, 83(7): 773-780.Deepti Singh and Santosh Kumar (2008) Studies on genetic variability, heritability, genetic advance and correlation in

marigold. Journal of Ornamental Horticulture, 11(1): 27-31.Deka, K K and Paswan, L (2002) Correlation and path analysis studies in chrysanthemum. Annals of Biology, 8(1): 31-34.Dewey, D R and Lu, K N (1959) A correlation and path coefficient analysis of components of crested wheat grass seed

production. Agronomy Journal, 51:515-518.Jhon, A Q, Khan, F U and Rather, Z A (2006) Genetic variability studies in tulip. Applied Biological Research, 8 (1-2): 37–9.Johnson, H W, Robinson, H F and Constock, R E (1955) Estimates of genetic and environmental variability in soybean.

Agronomy Journal, 47:314-318.Kumar, R, Deka, B C and Venugopalan, R (2012) Genetic variability and trait association studies in gerbera (Gerbera

jamesonii) for quantitive traits. Indian Journal of Agricultural Sciences, 82(7): 615–9.Lush, J L (1940) Intra-sire Correlation on Regression Off-spring on Dams as a Method of Estimating Heritability of Characters.

Proceedings of American Society of Animal Production, 33: 292-301.Nandkishore and Raghava, S P S (2001) Variability studies in African marigold. Journal of Ornamental Horticulture, 4(2):

124-125.Pal, P and George, S V (2002) Genetic variability and correlation studies in chrysanthemum. Horticultural Journal, 15(2): 75-81.Panwar, S, Singh, K P, Prasad, K V, Satyavathi, C T and Namita (2012) Character association and path coefficient analysis

in rose (Rosa x hybrida). Indian Journal of Horticulture, 69 (2): 231–8.Ravi Kumar, H and Patil, V S (2003) genetic variability and characters association studies in Chinaster (Callistephus chinensis

Nees )genotyeps Journal of Ornamental Horticulture, 6(3): 222-228.Reena M, Beniwal B S, Bhatia S K and Deswal D P 2005 Variability and correlation studies in African marigold (Tagetes

erecta L.) Research on crops. 6(2): 322-327.Sheela, V.L., Sabina George, T., Rakhi, R and Geetha Lakshmi, P.R. 2007. Variability studies in cut flower varieties of

Heliconias. Indian Journal of Horticulture. 64(1): 109-111.Singh, D and Sen, N L (2000) Genetic variability, heritability and genetic advance in marigold. Journal of Ornamental

Horticulture 3(2): 75-78.Singh, D and Singh, A K (2005) Correlation and path coefficient analysis in marigold (Tagetes spp.). Progressive Horiculture

37(2): 385-388.Sirohi, P S and Behera. P K (1999) Correlation and path analysis studies in chrysanthemum. Journal of Ornamental

Horticulture, 2(2): 80-83.Wright, S (1921) Correlation and causation. Journal of Agricultural Research, 20:557-587.