Genetic diversity in early cauliflower (Brassica oleracea var. botrytis L.) germplasm H.M. Santhosha1, B. Varalakshmi2 and N.C. Narase Gowda1 Department of Horticulture, University of Agricultural Sciences GKVK Campus, Bangalore-560 065, India E-mail: san3070@gmail.com ABSTRACT An experiment was conducted to study genetic divergence in 51 genotypes of cauliflower. Data was recorded for 16 quantitative characters. The genotypes were grouped into 14 clusters. A majority of the genotypes grouped together in Cluster 14 (with 14 genotypes), followed by Cluster 12 (with 8 genotypes). Intra-cluster value was maximum in Cluster 8 and minimum in Cluster 2. Maximum inter-cluster distance was observed between Clusters 8 and 10, followed by that between Clusters 10 and 13 and between Clusters 8 and 12. Hence, genotypes IIHR-323-13, IIHR-214- 5 and IIHR-277-14 of Cluster 8, and genotypes IIHR-263 and IIHR-272 of cluster 10 present the best choice for hybridization. Highest mean value for plant weight, leaf number, curd diameter, curd size, net curd-weight , net plot yield, yield per hectare and marketable curd-weight was also observed in Cluster 10, which indicates that genotypes included in this cluster are potential parents for hybridization programmes aimed at increasing cauliflower yields. Key words: Cauliflower, genetic diversity, hybridization INTRODUCTION Cauliflower (Brassica oleracea var. botrytis L.) is one of the important cole crops grown for its curd in India. Information on genetic divergence of plant material is vital to a plant breeder for efficient choice of parents for hybridization. It is an established fact that genetically diverse parents are likely to contribute desirable segregants. More diverse the parents greater the chances of obtaining high heterotic F 1 s and broad-spectrum variability in segregating generations (Murthy, 1965; Murthy and Arunachalam, 1966; Moll et al, 1974). Improvement in yield and quality can be normally achieved by selecting genotypes with desired character-combinations existing in nature or inducing through hybridization. Parents identified on the basis of divergence analysis are expected be more promising in hybridization for both cross-and self-pollinated crops. Mahalanobis’s D2 statistic has been proved to be a powerful tool in quantifying genetic divergence in germplasm and has successfully used in various crops (Mahalanobis, 1936). Very little information is available on genetic divergence. In cauliflower, the present study was carried out to ascertain nature and magnitude of genetic diversity among 51 germplasm lines of early cauliflower, using D2 statistic. This shall be eventually helpful in planning 1 Unniversity of Horticultural Sciences, Bagalkot 2 Division of Vegetable Crops, IIHR, Hessaraghatta, Bangalore-89 appropriate breeding programmes for developing of superior varieties/hybrids. MATERIAL AND METHODS The experiment was conducted at Indian Institute of Horticultural Research (IIHR), Hessaraghatta, Bengaluru. Twenty three days old seedlings of 51 genotypes of early cauliflower (Brassica oleracea var. botrytis L.) were transplanted from the nursery to the field and were grown during kharif 2008-09. Sixty plants represented each genotype per replication. Standard package of practices was followed to raise a good crop, in Randomized Complete Block Design (RCBD) at spacing of 50cm between rows and 40cm between plants, with two replications. Observations were recorded on 10 randomly selected plants in each replication, for 16 quantitative parameters, namely, days to 50% curd initiation, days to 50% curd maturity, plant weight, leaf number, leaf length, leaf breadth, leaf weight, stalk length, stalk weight, curd depth, curd diameter, curd size, net curd- weight, net plot-yield, yield per hectare and marketable curd weight. To assess genetic diversity among the 51 genotypes of early cauliflower, Mahalanobis D2 statistic (Mahalanobis, 1936) was used, following the procedure given by Rao J. Hortl. Sci. Vol. 6(1):21-24, 2011 22 (1952). Grouping of genotypes into clusters was done using Tocher’s method, as described by Rao (1952). Statistical analysis of data was carried out using the statistical program GENRES at IIHR, Bangalore. RESULTS AND DISCUSSION Analysis of variance revealed significant variation among genotypes in early-cauliflower for all 16 quantitative characters studied (Table 1). D2 values ranged from 6.83 to Table 1. Classification of 51 early-cauliflower genotypes into 14 different clusters Cluster No. No. of accessions Genotype 1 4 IIHR-73 IIHR-78-7 IIHR-385 IIHR-391 2 2 IIHR-375 IIHR-384 3 2 IIHR-381 IIHR-386 4 2 IIHR-249 IIHR-264-3 5 2 IIHR-380 IIHR-389 6 2 IIHR-223-10 NS-60 7 2 IIHR-266 IIHR-324-1-5 8 3 IIHR-214-5 IIHR-277-14 IIHR-323-13 9 3 IIHR-217-1-4 IIHR-371 IIHR-392 10 2 IIHR-263 IIHR-272 11 3 IIHR-231-4 IIHR-318-2 IIHR-345 12 8 IIHR-249-5 IIHR-250 IIHR-265-2 IIHR-305 IIHR-311-3 IIHR-316 IIHR-343-1 IIHR-387 13 2 IIHR-376 IIHR-377 14 14 IIHR-352 IIHR-368 IIHR-369 IIHR-370 IIHR-372 IIHR-373 IIHR-374 IIHR-378 IIHR-379 IIHR-382 IIHR383 IIHR-388 IIHR-390 Early Kunwari Fig 1. Dendrogram of early-cauliflower genotypes for quantitative traits, using average degree of linkage (between groups) Foot note: 1. IIHR-73 2. IIHR-78-7 3. IIHR-214-5 4. IIHR-217-1-4 5. IIHR- 223-10 6. IIHR-231-4 7. IIHR-249 8. IIHR-249-5 9. IIHR-250 10. IIHR-263 11. IIHR-264-3 12. IIHR-265-2 13. IIHR-266 14. IIHR- 272 15. IIHR277-14. 16. IIHR-305 17. IIHR-311-3 18. IIHR-316 19. IIHR-318-2 20. IIHR-323-13 21. IIHR-324-1-5 22. IIHR-343-1 23. IIHR-345 24. IIHR-352 25. IIHR-368 26. IIHR-369 27. IIHR-370 28. IIHR-371 29. IIHR-372 30. IIHR-373 31. IIHR-374 32. IIHR-375 33. IIHR-376 34. IIHR-377 35. IIHR-378 36. IIHR-379 37. IIHR-380 38. IIHR-381 39. IIHR-382 40. IIHR-383 41. IIHR-384 42. IIHR-385 43. IIHR-386 44. IIHR-387 45. IIHR-388 46. IIHR-389 47. IIHR-390 48. IIHR-391 49. IIHR-392 50. Early Kunwari 51. NS-60 Santhosha et al J. Hortl. Sci. Vol. 6(1):21-24, 2011 23 Table 2. Inter-cluster and intra-cluster (in bold type-face) distances among 14 clusters in early-cauliflower, based on D2 analysis Cluster 1 2 3 4 5 6 7 8 9 10 11 12 13 14 1 8.09 7.29 6.13 8.56 6.03 8.75 8.11 9.72 9.16 9.82 7.85 9.04 8.16 8.21 2 2.84 5.55 6.11 4.57 7.91 8.31 11.88 9.31 6.31 9.27 6.01 9.58 7.73 3 2.98 7.22 3.64 9.44 8.85 9.89 6.85 9.35 8.32 8.14 5.61 6.95 4 3.09 5.97 7.62 7.76 12.55 10.01 6.05 10.83 7.24 10.61 8.72 5 3.21 8.29 7.53 9.84 7.47 8.14 8.03 7.32 6.91 6.71 6 3.31 5.48 11.27 12.20 6.46 8.28 8.37 12.67 9.71 7 3.42 9.80 12.28 7.93 7.50 9.24 12.09 9.46 8 10.13 11.63 14.10 8.26 13.21 10.40 10.90 9 9.30 12.61 10.77 10.94 6.73 9.37 10 3.74 11.57 6.92 13.40 10.25 11 6.73 10.55 10.03 9.39 12 7.33 11.33 9.60 13 4.02 8.88 14 9.08 Table 3. Cluster means for 16 quantitative characters and relative contribution of individual characters to total divergence in early- cauliflower, based on D2 analysis Cluster No. Characters DCI DCM PW LN LL LB LW SL SW CD C Dia. CS NCW NPY Y/ha MCW 1 40.00 56.30 507.50 14.80 30.00 14.50 189.50 3.30 26.60 4.20 7.70 34.20 157.50 9.00 11.10 294.00 2 38.80 54.00 617.90 15.30 32.70 16.10 227.70 3.20 24.10 5.00 9.70 49.30 199.80 11.00 13.50 365.00 3 37.50 54.50 500.40 14.40 28.40 14.30 170.60 3.20 23.10 4.20 8.40 35.70 145.00 9.10 11.30 303.80 4 37.00 52.50 681.40 17.40 31.30 14.60 299.50 3.30 19.30 4.80 8.90 41.40 198.90 10.70 13.30 366.40 5 38.50 53.00 539.60 15.40 31.40 15.30 190.40 3.10 23.10 4.30 9.00 38.90 182.30 9.60 11.80 324.30 6 43.00 57.00 741.10 18.10 34.60 17.60 327.40 2.90 27.00 4.60 8.90 42.50 195.80 10.30 12.70 386.80 7 41.30 54.50 738.80 17.90 37.40 17.40 306.50 3.10 27.50 4.40 8.50 39.10 205.30 12.00 14.90 408.50 8 40.80 58.00 453.80 15.20 35.30 16.30 184.40 3.20 22.70 4.10 6.30 27.80 126.10 7.90 9.10 271.80 9 37.30 54.00 370.20 13.50 24.20 12.20 130.20 3.10 20.50 4.10 7.00 30.50 121.20 5.80 7.20 221.20 10 38.30 56.00 802.30 18.70 33.80 17.30 314.50 3.30 28.30 4.80 10.00 50.70 235.60 12.50 15.40 462.10 11 43.70 56.30 515.80 15.60 33.20 14.90 196.20 3.20 28.40 4.50 7.40 35.10 143.80 8.50 10.50 291.40 12 39.00 54.10 640.70 16.00 31.50 14.10 242.20 3.70 30.70 4.80 9.40 46.80 197.30 10.00 12.40 370.60 13 37.50 55.00 294.10 11.50 23.50 12.10 95.30 3.70 24.60 3.40 6.50 22.40 104.30 5.30 6.60 177.70 14 39.00 54.60 523.00 14.90 30.70 15.70 198.00 3.10 23.10 4.60 8.20 37.40 168.40 9.00 11.10 309.20 Percentage 4.16 0.08 16.94 0.16 0.24 0.47 1.73 2.75 3.22 1.10 7.29 9.02 6.51 13.49 5.88 26.98 contribution DCI = Days to 50% curd initiation LL = Leaf length (cm) SW = Stalk weight (g) NCW = Net curd-weight (g) DCM = Days to 50% curd maturity LB = Leaf breadth (cm) CD = Curd depth (cm) NPY = Net plot-yield (kg/6m2) PW = Plant weight (g) LW = Leaf weight (g) C Dia. = Curd diameter (cm) Y/ha = Yield/hectare (tons) LN = Leaf number SL = Stalk length (cm) CS = Curd size (cm2) MCW=Marketable curd-weight (g) 469.19, showing a high divergence among germplasm lines. Similar observations were also reported by Varalakshmi et al (2010) in cauliflower. On the basis of relative magnitude of D2 values, the 51 germplasm lines of early-cauliflower were grouped into 14 clusters (Fig. 1) with an assumption that those within a cluster had smaller differences in D2 values among themselves than those of other clusters. Depending on their genetic divergence, Cluster 14 had the highest number of genotypes (14), indicating that less variation existed among the genotypes for these quantitative traits, followed by Cluster 12 and 1 (each with 8 and 4 genotypes), respectively. Clusters 8, 9, 11 had 3 genotypes each, while, Cluster 2 to 7, 10 and 13 had two genotypes each. Distribution of genotypes in different clusters is shown in Table 1. Inter-cluster distances were higher than intra-cluster distances, indicating presence of a wider genetic diversity among genotypes included in these clusters (Table 2). These results are in conformity with finding of Quamruzzaman et al (2007) in cauliflower. Occurrence of such diversity contributes to heterosis and is, therefore, useful in identifying transgressive segregation. Intra-cluster distance varied from 2.84 to 10.13, with Cluster 8 showing the maximum distance. Maximum inter- cluster distance (Table 2) was observed between Cluster 8 and 10 (14.1). Genotypes of clusters with maximum inter- cluster distance are expected to be genetically more Genetic diversity in early cauliflower J. Hortl. Sci. Vol. 6(1):21-24, 2011 24 divergent. Selection of parents for hybridization should be done from two clusters having higher inter-cluster distance, to aim for higher variability. Therefore, genotypes IIHR- 323-13, IIHR-214-5 and IIHR-277-14 from Cluster 8, and genotypes IIHR-263 and IIHR-272 from Cluster 10 are the best choice to be parents for hybridization. Differences in cluster-means (Table 3) existed for almost all characters. Highest mean value for plant weight (802.3g), leaf number (18.7), curd diameter (10.0cm), curd size (50.7cm2), net curd-weight (235.6g), net plot yield (12.5kg/ 6m2), yield per hectare (15.4t), and marketable curd- weight (462.1g) was observed in Cluster 10. Cluster 12 recorded maximum stalk-length (3.7cm) and stalk-weight (30.2g) while Cluster 6 recorded maximum leaf-breadth (17.6cm) and leaf-weight (327.3g). Clusters 7 and 2 showed highest mean value for leaf length (37.4cm) and curd depth (5.0cm), respectively. Cluster 13 ranked lowest in plant weight (294.1g), leaf number (11.5), leaf breadth (12.1cm), leaf length (23.5cm), leaf weight (95.3g), curd depth (3.4cm), curd size (22.4cm2), net curd-weight (104.2g), net plot-yield (5.3kg/ 6m2), yield per hectare (6.6t) and marketable curd-weight (177.7g). Cluster 4 ranked lowest for days to 50% curd- initiation (37.0days), days to 50% curd-maturity (52.5days) and stalk-weight (19.3g). Cluster 6 showed the lowest mean for stalk-length (2.9cm) while Cluster 8 had the lowest curd- diameter (6.3cm), respectively. Lower yield in Cluster 13 may be due to smaller size of curd. Based on cluster-mean, cross between genotypes of Cluster 10, 12, 6, 7, 2, 8 & 11, with genotypes of Cluster 13 and 4 should result in production of highly transgressive segregants for yield-contributing characters. Also, this stands to increase variability and scope for selection of superior lines. Important characters identified to be responsible for maximum divergence were marketable curd-weight (26.98%), followed by plant weight (16.94%), net plot-yield (13.49%) and curd size (9.02%) (Table 3). This confirms the existence of ample divergence among genotypes with respect to these traits, and hence, selection of best genotypes for these traits will help increase curd-yield in cauliflower. From these studies, it is concluded that highest inter- cluster distance between Clusters, namely, 8 (IIHR-323- 13, IIHR-214-5, IIHR-277-14 IIHR-263) and IIHR-272, IIHR 263 of Clusters 10 indicated the presence of large diversity among genotypes cluster segregants. Hence genotypes of Cluster 8 and 10 may be used as parents in hybridization for obtaining useful segregants. REFERENCES Mahalanobis, P.C. 1936. On the generalized distance in statistics. Proc. Nat’l. Instt. Sci. (India), 2:49-55 Moll, R.W., Salhauaonam, W.S. and Robinson, H.F. 1974. Quantitative genetics - empirical results relevant to plant breeding. Adv. Agron., 26:277-313 Murthy, B.R. 1965. Heterosis and combining ability in relation to genetic divergence in flue-cured tobacco. Ind. J. Genet., 25:46-56 Murthy, B.R. and Arunachalam, V. 1966. The nature of genetic divergence in relation to breeding system in crop plants. Ind. J. Genet., 26:188-198 Quamruzzaman, A.K.M., Rahman, M.M., Nazim Uddin, M.N., Siddiky, M.A. and Prodhan, M.D.H. 2007. Genetic diversity in cauliflower (Brassica oleracea L. var. botrytis). Ind. J. Hort., 64:50-52 Rao, C.R. 1952. Advanced Statistical Methods in Biometrical Research. John Wiley and Sons Inc., New York Varalakshmi, B., Pushpalatha, A. and Girigowda, J.R. 2010. Genetic diversity in early cauliflower (Brassica oleracea L. var. botrytis). Ind. J. Hort., 67:281- 283 (MS Received 21 October 2010, Revised 15 April 2011) Santhosha et al J. Hortl. Sci. Vol. 6(1):21-24, 2011