A study on the association of various morphological traits through correlation analysisin gladiolus (Gladiolus x hybridus Hort.) showed that spike length had significant positivecorrelation with plant height, rachis length, duration of flowering and number of florets perspike, whereas it had negative correlation with number of shoots per plant, size of the floretand number of corms per plant at both phenotypic and genotypic levels. Number of florets perspike was positively and significantly correlated with number of leaves per plant, rachis length,leaf area, spike length and number and weight of cormels produced per plant at bothphenotypic and genotypic levels. The results of investigation revealed that spike length,number of florets per spike and floret size are important spike quality characters. Hence, thesecharacters may be considered as selection indices in gladiolus breeding programme

Choudhary, Mahesh

Kumari, Anop

Moond, S.K.

English

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Research in Plant Biology, 1(4): 68-72, 2011  ISSN : 2231-5101 www.resplantbiol.com    Correlation Studies in Gladiolus  Mahesh Choudhary*, S.K. Moond and Anop Kumari1  Department of Floriculture and Landscaping College of Horticulture and Forestry, Jhalarapatan, Jhalawar-326023 (Rajasthan) 1Department of Horticulture, CCS Haryana Agricultural University, Hisar, Haryana *Corresponding author email : balodamahesh@gmail.com  A study on the association of various morphological traits through correlation analysis in gladiolus (Gladiolus x hybridus Hort.) showed that spike length had significant positive correlation with plant height, rachis length, duration of flowering and number of florets per spike, whereas it had negative correlation with number of shoots per plant, size of the floret and number of corms per plant at both phenotypic and genotypic levels. Number of florets per spike was positively and significantly correlated with number of leaves per plant, rachis length, leaf  area,  spike  length  and  number  and  weight  of  cormels  produced  per  plant  at  both phenotypic  and  genotypic  levels.  The  results  of  investigation  revealed  that  spike  length, number of florets per spike and floret size are important spike quality characters. Hence, these characters may be considered as selection indices in gladiolus breeding programme.  Key words: Gladiolus (Gladiolus x hybridus Hort.), correlation, spike length, variability  Gladiolus (Gladiolus x hybridus Hort.) is a very important bulbous cut flower crop grown for its beauty, elegance and majestic spikes. It has colourful florets borne on spike. Development of varieties having higher yield and improved quality have been main objectives  of  most  of  the  breeding programmes. Heritable traits such as yield and quality  are  complex characters known  to  be collectively  influenced  by  various polygenically inherited traits which are highly vulnerable to environmental changes. Hence, for an effective and efficient selection of genotypes in  gladiolus for  yield and  quality parameters, the knowledge of direction and magnitude of  association between  yield  and quality and their components and within components   themselves   become   necessary. Such   relationship   can   be   known   through precise  estimation  of  genotypic  and phenotypic correlation between yield and its components. Correlations between different characters helps in finding out the degree of inter  relationship  among  various  characters and in evolving selection criteria for improvement of the available germplasm. Studies on genetic association are useful to ascertain the important component characters on which selection can be made. Therefore, the present investigation was undertaken to find out the correlations among various component characters.  MATERIALS AND METHODS The  present investigation was  carried out during 2008- 09, at the Research Farm of Department of Floriculture and Landscaping, College of Horticulture and Forestry, Jhalarapatan, Jhalawar (Rajasthan). Twelve genotypes of gladiolus (Gladiolus x hybridus Hort.) collected from diverse source were used for  the  present  study.  The  genotypes  Viz., ‘Jyotsna’,  ‘Sancerre’,  ‘Urmil’,  ‘TS-14’,  ‘GS-2’, ‘Punjab  Dawn’,  ‘Spic-n-Span’,  ‘Dhanvantari’, ‘Priscilla’,     ‘Peter     Pears’,     ‘Sabnam’     and ‘Chandani’ were  included  in  the  study.  The experiment was laid out in randomized block design (RBD) with three replications. Healthy Choudhary et al. / Research in Plant Biology, 1(4): 68-72, 2011 69    and  uniform  size  corms  of  3-5  cm  diameter were planted at a depth of 6-8 cm in plots of 1.55 m × 1.10 m size at spacing of 40 cm between rows and 25 cm between plants. The experimental data were recorded on five randomly selected plants in each plot and subjected to variance and covariance analysis described by Panse and Sukhatme (1967). The correlation at phenotypic and genotypic levels between all possible pairs of characters were calculated from variance and covariance components as proposed by Al- Jibouri et al. (1958).  RESULTS AND DISCUSSION Although, variability estimates provide information  on  the  extent  of  improvement possible in different characters, they do not throw light on the extent and nature of relationship  prevalent  between  the contributory characters and economically important characters. This could be obtained from simple association analysis that determines the direction and action of different characters. The estimate of genotypic correlations along with phenotypic correlations not only display clear picture of the extent of inherent   association,  but   also   indicate   the extent to which these phenotypically expressed correlations  are  influenced  by  the environment. These results are supported by findings of Misra and Saini (1990) and Balaram and Janakiram (2009). Based on this analysis, the traits that can be selected in improving the desired variables can be ascertained. The phenotypic and genotypic correlation coefficients were computed in all possible combinations  for  17  quantitative  characters and are presented in Tables 1 and 2. In the present study, the genotypic correlation coefficients were observed to be higher than the phenotypic correlation coefficient for most of the traits. The study showed that at both phenotypic and genotypic levels, spike length was found positively and significantly associated  with  plant  height,  rachis  length, duration of  flowering and number of  florets per spike (Tables 1 and 2) and non significant positive correlation was found with number of leaves per plant, days to  sleeping, leaf area, duration   of   flowering,   size   of   the   floret, number  of  florets  open  at  a  time,  cormels produced per plant, corm weight and diameter of  corm  at  both  phenotypic  and  genotypic levels. It shows that spike length, which is an important attribute of cut flower quality, can be increased with increase in any one of these characters,  specially  the  height  of  the  plant, number of  florets per spike and weight and diameter of corm. Similarly, the market value and marketability of gladiolus spikes depends upon the  number of  florets per  spike, floret size and number of florets open at a time and as  these  characters  had  positive  correlation with spike length, so a direct selection from germplasm  lines  may  be  effective  for  the improvement of this crop. The results obtained are in full agreement with the findings of Gil et al. (1978) and De and Misra (1994) suggesting selection of varieties on the basis of average to long  spike  length  for  improved  number  of florets  per  spike.  However,  Misra  and  Saini (1990) recorded negative or poor correlation of spike length with number of florets per spike. Floret   size   was   positively   correlated   with number of leaves per plant, rachis length, leaf area,  number of  florets  open  at  a  time,  and corm  weight  and  diameter. It  indicated that increase in  floret size  was  possible with the increase in any of these traits. The results find support from findings of Katwate et al. (2002). Plant height was positively and significantly correlated  with  rachis  length,  spike  length, duration of  flowering and number of  florets per  spike  both  at  phenotypic and  genotypic levels  (Tables  1  and  2).  This  association  of plant height with the characters mentioned is a desirable feature in this crop. Non-significant positive   correlation  was   recorded   between plant height and number of leaves per plant, leaf area, shoots per plant, number of cormels produced per plant, weight of cormels produced per plant, corm weight and diameter Choudhary et al. / Research in Plant Biology, 1(4): 68-72, 2011 70    of corm. Negative correlation was observed between   plant   height   and   size   of   floret, number of florets open at a time and corms produced per plant. Number of leaves per plant had significant positive correlations with days to sleeping, leaf area, number of florets per spike and corm weight at both genotypic and phenotypic level indicating the importance of photosynthetic area for these characters. Non- significant positive correlation was recorded between number of leaves per plant and rachis length, spike length and size of the floret. Significant positive association of  number of shoots per plant with number of corms per plant   indicated   that   with   increase   in   the number of shoots per plant increased the corm production which is a desirable attribute with respect to corm production and multiplic- ability  of  the  genotype.  However,  for  cut flower production more number of shoots per planted corm is a negative attribute as this character was negatively correlated with number of florets per spike, size of floret and corm weight. Jhon et al. (2002) also reported a similar trend in gladiolus. For early flowering, importance of reduced number of shoots per planted corm was indicated by negative correlation of days to sleeping with number of shoots per plant. The lack of association between number of florets per spike with days to sprouting, number of shoots per plant and number of corms produced per plant at genotypic level leads to the conclusion that these characters could be improved indepen- dently through selection. Corm diameter was positively and significantly correlated with rachis length, leaf area, size of the floret and corm weight at phenotypic level, whereas significant negative correlation was recorded for number of shoots and corms produced per plant at both genotypic and phenotypic levels. Corm weight exhibited positive and significant correlation with number of leaves per plant, leaf area, size of the floret and cormels weight per plant. De and Misra (1994) also obtained similar trends in gladiolus. The yield in terms of cormels produced per  plant  can  be  increased  with  increase  in plant height, rachis length, leaf area, spike length, shoots per plant, florets per spike, size of floret, number of floret open at a time, corms per plant, corm weight and diameter because these   characters  were   positively  correlated with cormels produced per plant at both phenotypic and genotypic levels. Negative correlation  between  cormel  weight  with cormels per plant indicated that with the increase   in   one   parameter   there   will   be decrease in another. Similar results were reported by Jhon et al. (2002).  REFERENCES Al-Jibouri,  H.A.,  Miller,  P.A.  and  Robinson, H.F. (1958). Genotypic and environ-mental variances and covariances in an upland cotton cross of interspecific origin. Agron. J., 50: 633-636. Balaram, M.V. and Janakiram, T. (2009). Correlation and path coefficient analysis in gladiolus. J. Ornam. Hort,. 12(1): 22-29. De, L.C. and Misra, R.L. (1994). Studies on correlation and path coefficient analysis in gladiolus. J. Ornam. Hort., 2: 14-19. Gil,  C.M.,  Minami,  K.  and  Demetrio,  C.G.B. (1978). The effect of corm size in gladioli on the quality of flower stalk. Solo, 70(2): 66-68. Jhon, A.Q., Bichoo, G.A. and Wani, S.A. (2002). Correlation studies in gladiolus. J. Ornam. Hort., 5(1): 25-29. Katwate,  S.M.,  Nimbalkar,  C.A.,  Desai,  U.T. and Warade, S. D. (2002). Variability, correlation and path analysis in gladiolus. Floriculture Research Trend in India, pp 105- 109.    Indian    Society    of    Ornamental Horticulture, IARI, New Delhi. Misra, R.L. and Saini, H.C. (1990). Correlation and path coefficient studies in gladiolus. Indian J. Hort., 47(1): 27-32. Panse, V.G. and Sukhatme, P.V. (1967). Statistical Methods for Agricultural Workers. ICAR, New Delhi. Choudhary et al. / Research in Plant Biology, 1(4): 68-72, 2011 71    Table: 1. Phenotypic correlation co-efficients between different characters in gladiolus cultivars  Traits X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17  X1 1.000 0.129 0.115 0.278 0.366 0.165 0.302 0.394 -0.309 0.022 0.112 -0.110 -0.237 0.219 0.299 -0.064 0.160  X2 1.000 0.064 -0.009   0.712** 0.122 0.653**   0.653** 0.078 0.387 -0.105 -0.018 -0.009 0.204 0.062 0.167 0.052  X3 1.000 0.428* 0.288 0.501** 0.169 0.323 -0.744** 0.471* 0.053 0.084 -0.710**   -0.051 0.400* -0.029 0.334  X4 1.000 0.057 0.078 0.040 0.079 -0.459* 0.027 -0.332 -0.098 -0.444*   -0.456* -0.078 -0.287 -0.108  X5 1.000 0.419* 0.827**   0.622** -0.153 0.761** 0.193 0.409* -0.134 0.406* 0.396 0.430* 0.810**  X6 1.000 0.162 0.139 -0.352 0.584** 0.386 0.509**   -0.389 0.604 0.619** 0.689**    0.498**  X7 1.000 0.672** -0.051 0.544**    -0.041 0.248 -0.007 0.101 0.078 0.132 0.128  X8 1.000 -0.260 0.421* -0.230 -0.048 -0.176 -0.123 0.100 0.053 -0.110  X9 1.000 -0.158 -0.280 0.078 0.909** 0.176 -0.556** 0.158 0.428  X10 1.000 0.210 0.060 -0.168 0.538** 0.350 0.621** 0.144  X11 1.000 0.215 -0.305 0.539**   0.779** 0.379 0.596**  X12 1.000 0.154 0.596** 0.171 0.707** 0.140  X13 1.000 0.140 -0.574** 0.150 -0.416*  X14 1.000 0.532**    -0.837** 0.365  X15 1.000 0.414* 0.774**  X16 1.000 0.298  X17 1.000  *= Significant at 5% level, ** = Significant at 1% level  X1= Days to corm sprout, X2= Plant height (cm), X3= No. of leaves/plant, X4= Days to slipping, X5=Rachis length (cm) , X6=leaf area (cm2), X7= Spike length (cm), X8= Duration of flowering, X9= No. of shoots/plant, X10= No. of florets/spike, X11= Size of floret (cm), X12= No. of florets open at a time, X13= No. of corms/plant, X14 = No. of cormels/plant, X15= Weight of corm (g), X16= Cormels weight/plant (g), X17= Diameter of corm (cm) Choudhary et al. / Research in Plant Biology, 1(4): 68-72, 2011 72       Table: 2. Genotypic correlation co-efficients between different characters in gladiolus cultivars  Traits X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17  X1 1.000 0.334 0.456* 0.383 0.436* 0.276 0.565**   0.718**   -0.597** -0.117 0.160 -0.162 -0.515** -0.373 0.482** -0.167 0.386  X2 1.000 0.103 0.136 0.821**   0.105 0.761**   0.745**   0.037 0.493** -0.153 -0.036 0.016 0.226 0.060 0.173 -0.163  X3 1.000 0.641**   0.304 0.631**   0.184 0.400* -0.899** 0.466** 0.001 -0.160 -0.921** -0.058 0.447* 0.007 0.436*  X4 1.000 0.035 0.123 0.049 0.195 -0.512** -0.003 -0.395 -0.128 -0.603** -0.560** 0.168 -0.377 -0.155  X5 1.000 0.462* 0.899**   0.738**   -0.150 0.803** 0.214 0.461* -0.165 0.429* 0.408* 0.402* 0.210  X6 1.000 0.139 0.155 -0.398* 0.703** 0.456* 0.543**   -0.424* 0.626** 0.686** 0.726** 0.692**  X7 1.000 0.919**   -0.051 0.628** -0.113 0.287 -0.005 0.117 0.089 0.167 0.235  X8 1.000 -0.248 0.462* -0.285 -0.075 -0.218 -0.145 0.123 0.009 -0.155  X9 1.000 -0.179 -0.311 0.081 0.993** 0.189 -0.590** 0.161 0.700**  X10 1.000 0.150 0.798**   -0.187 0.635** 0.380 0.737** 0.248  X11 1.000 0.282 -0.331 0.609** 0.899** 0.481** 0.015  X12 1.000 0.175 0.647** 0.174 0.784** 0.169  X13 1.000 0.148 -0.625** 0.147 -0.702**  X14 1.000 0.471* -0.863** 0.533**  X15 1.000 0.438* 0.040  X16 1.000 0.436*  X17 1.000  *= Significant at 5% level, ** = Significant at 1% level, Characters as in Table 1 

Correlation Studies in Gladiolus

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