GE NETIC VARI ABIL ITY AND TRAIT AS SO CI A TION IN CO RI AN DER (Coriandrum sativum L.) UN DER DIF FER ENT DATES OF SOW ING

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1 Progressive Research 8 (Special) : (2013) Society for Sci. Dev. in Agric. and Tech. GE NETIC VARI ABIL ITY AND TRAIT AS SO CI A TION IN CO RI AN DER (Coriandrum sativum L.) UN DER DIF FER ENT DATES OF SOW ING M.S. Darvhankar, G.U. Kulkarni, L.K. Sharma and C.K. Mandavia De part ment of Ge net ics and Plant Breed ing, Junagadh Ag ri cul tural Uni ver sity, Junagadh Key words : ABSTRACT Thirty diverse genotypes of coriander were grown in three (D 1 to D 3 ) environments during the Rabi seasons for three consecutive dates in the year 2011 at the Vegetable Research Station JAU, Junagadh. Analysis of variance for each sowing date revealed highly significant differences among the genotypes for all the characters. Broad-sense heritability was high for characters days to 50% flowering and number of basal leaves under early sown condition, seed yield per plant and harvest index in timely and late sown condition. A high estimate of genetic gain was noted for number of basal leaves, number of fruit bearing branches, umbels per plant, seed yield per plant, 100-seed weight and harvest index in all the three sowing condition. Phenotypic and genotypic correlation studies revealed that the seed yield per plant was positively and significantly correlated with harvest index, 100-seed weight, number of fruit bearing branches and umbellets per plant under all the three dates of sowing. Path coefficient analysis revealed that the days to 50% flowering, 100-seed weight, plant height, number of basal leaves, longest basal leaf length, umbels per plant and umbellets per plant (D 1 ) harvest index under all the three sowing dates. Coriander, Coriandrum sativum L., genetic variability, correlation, path analysis. Coriander (Coriandrum sativum L.) is an important seed spice crop belonging to the family Apiaceae (previously classified under the family Umbelliferae) with a diploid chromosome number 2n=22. The unripe fruits smell of bed bugs and thus character is responsible for determination of the name coriander from the Greek world Koris meaning bed bug. The ripe fruits are pleasantly aromatic. Two types of coriander namely small seeded and large seeded are cultivated. The large seeded types (3-5 mm diameter) belong to the group var. Vulgare while the small seeded (1.5-3 mm diameter) belong to var. microcarpum. In India large seeded varieties were mostly cultivated but they are being with small seeded ones, in recent years. In India coriander occupied an area of million hectares giving a total production of metric tonnes during The major coriander growing states are Andhra Pradesh, Tamil Nadu, Karnataka, Rajasthan, Gujarat, Madhya Pradesh, Utter Pradesh, Haryana and Bihar. Rajasthan is the leading state in area and production of coriander followed by Andhra Pradesh. The success of any breeding programme in general and improvement of specific trait through selection in particular, totally depends upon the genetic variability present in the available germplasm of a particular crop. For the success of crop improvement, the character for which variability is present, it should be highly heritable as progress due to selection depends on heritability, selection intensity and genetic advance of the character. Heritability and genetic advance estimates for different targeted traits helps the breeder to apply appropriate breeding methodology in the crop improvement programme. Main thrust in any crop improvement programme is to enhance yield. As an established fact, yield is complex trait and is dependent on much other ancillary character which is mostly inherited quantitatively. The different morphological traits vary in their relationship with yield in terms of their nature as well as magnitude, though they show a continuous variation and are influenced by environment. The components which have high heritability and positive correlation with yield can be used in the indirect selection for yield and act as an alternate mode of selection for yield improvement. When indirect association between complex, path coefficient analysis is most effective mean to find out direct and indirect causes of association among the different variables. Path coefficient analysis can discriminate between the realistic (general effect) and inflated (environmental effect) correlations. Hence, the knowledge of direct and indirect effect of different components on yield is of prime importance in selection of high yielding genotypes. Keeping the above facts in view, the present investigation was

2 348 Genetic variability and trait association in coriander coriander. in sowing of dates different three in parameters genetic of Estimates Table-1: C haracters M ea n R ang e P CV % G CV % H 2 GA % D1 D2 D3 D1 D2 D3 D1 D2 D3 D1 D2 D3 D1 D2 D3 D1 D2 D3 D ays to 50% flowering P lant height (cm) N umber of basal leaves L ongest basal leaf length (cm) N o. of fruit bearing branches U mbels per plant U mbellets per plant S eeds per umbel S eed yield per plant (g) seed weight (g) D ays to maturity H arvest index (%) D1 - First date of sowing, D 2 - Second date of sowing and D 3 -Third date of sowing. under taken by involving some popularly cultivated and newly developed varieties of coriander. MATERIALS AND METHODS The experimental material comprised of 30 different genotypes of coriander. There were 26 genotypes from NRC on Seed Spices Ajmer (Rajasthan) and remaining four from Vegetable Research Station, Junagadh. Three environments were created by giving interval of 25 days between each sowing date. Three sowing dates are, (early sown), (timely sown) and (late sown) at the Vegetable Research Station, Junagadh Agricultural University, Junagadh during Rabi season of the year During all these three sowing, trials were laid out in randomized block design with three replications. Row to row and plant to plant distance was kept at 30 and 10 cm, respectively. The soil of experimental site was medium black, alluvial in origin and poor in organic matter. The climate of the area represents tropical condition with semiarid nature. The data were recorded on twelve characters viz. days to 50% flowering, plant height, number of basal leaves, longest basal leaf length, number of fruit bearing branches, umbels per plant, umbellets per plant, seeds per umbel, seed yield per plant, 100-seed weight, days to maturity and harvest index. Except days to 50% flowering and days to maturity, were recorded on plot basis, data on rest of the characters was recorded on five randomly selected plants in all the three replications. The recommended package of practices was followed to raise a good crop. Analysis of variance was performed following the standard procedures given by (1). The phenotypic and genotypic coefficient of variation (PCV, GCV) was computed as per method described by (2) and correlation coefficient at genotypic and phenotypic level was computed according to (3). Path coefficient analysis was done by formula suggested by (4). In present investigation, path coefficient analysis was carried out by taking seed yield per plant as dependent variable and other observed traits as independent variables in each of the environments and also for the pooled basis. RESULTS AND DISCUSSION The analysis of variance revealed highly significant differences among the genotypes for all the characters. The presence of highly significant differences established the existence of large variability among

3 Darvhankar et al., 349 genotypes included in the experimental material. Analysis of variance on pooled basis for all the characters due to sowing dates was observed for all the characters. This indicates the significance of sowing date in the expression of character and hence many genotypes behaved differently in different sowing conditions. Wide range of variation was observed for all the characters viz. umbellets per plant, harvest index, umbels per plant, days to 50% flowering, plant height and number of fruit bearing branches in early sown condition (Table-1). Similar results were reported by (5, 6). The variance indicated that the values of phenotypic coefficient of variation were always higher than genotypic coefficient of variation, indicating the influence of environmental factors. The highest genotypic coefficient of variation observed for harvest index, number of fruit bearing branches, number of basal leaves, 100-seed weight and seed yield per plant for all sowing condition. The high genotypic coefficient of variation indicated the presence of wide genotypic variation for the character under study to allow selection for individual traits. Results revealed presence of high amount of genetic variability in the evaluated genotypes for the major yield contributing characters along with seed yield which indicated that further improvement for these traits is possible. Broad-sense heritability was high for characters days to 50% flowering and number of basal leaves under early sown condition, Seed yield per plant and harvest index in timely sown condition and days to 50% flowering, number of fruit bearing branches, umbels per plant, umbellets per plant, seeds per umbel, seed yield per plant, 100-seed weight and harvest index under late sown conditions. Similar results were reported by (5, 6). A high estimate of genetic gain was noted for number of basal leaves, number of fruit bearing branches, umbels per plant, seed yield per plant, 100-seed weight and harvest index in early sowing condition; while number of basal leaves, longest basal leaf length, number of fruit bearing branches, seeds per umbel, seed yield per plant, 100-seed weight and harvest index for timely sown conditions; plant height, number of basal leaves, number of fruit bearing branches, seeds per umbel, seed yield per plant, 100-seed weight and harvest index for late sown condition. Similar results were reported by (5, 6). Table-2: Genotypic (G) and phenotypic (P) correlation co-efficient of eleven component characters with seed yield in three environments. Characters D1 D2 D3 Days to 50% flowering G * P Plant height (cm) G P No. of basal leaves G ** P Longest basal leaf length (cm) G ** 0.5** 0.453** P No. of fruit bearing branches G ** P ** Umbels per plant G * P Umbellets per plant G ** 0.30** P 0.286* 0.294* Seeds per umbel G ** P seed weight (g) G 0.965** 1.000** 0.810** P 0.908** 0.516** 0.600** Days to maturity G P ** Harvest index (%) G 1.000** 0.890** 0.895** P 0.394** 0.621** 0.810** *, ** Significant at P = 0.05 and P = 0.01, respectively D 1 -First date of sowing (Early) D 2 -Second date of sowing (Timely) D 3 -Third date of sowing (Late)

4 350 Genetic variability and trait association in coriander 100-seed weight and harvest index. In late sowing condition (D 3 ) seed yield per plant showed significant and positive correlation with number of basal leaves, longest basal leaf length, number of fruit bearing branches, umbellets per plant, seeds per umbel, 100-seed weight and harvest index. Similar results were reported by (5, 6). Figure-1: Genotypic (G) correlation co-efficient of eleven component characters with seed yield in three environments. D 1 - First date of sowing, D 2 - Second date of sowing and D 3 -Third date of sowing. 1. Days to 50% flowering 2. Plant height (cm) 3. No. of basal leaves 4. Longest basal leaf length (cm) 5. No. of fruit bearing branches 6. Umbels per plant. Umbellets per plant 8. Seeds per umbel seed weight 10. Days to maturity 11. harvest index (%) Correlation coefficient (Table-2 and Figure-1) were estimated between seed yield and other traits under study indicated that seed yield per plant was positively and significantly correlated with harvest index, 100-seed weight, number of fruit bearing branches and umbellets per plant under all the three dates of sowing. In early sowing condition (D 1 ) seed yield per plant showed significant and positive correlation with plant height, number of basal leaves, days to maturity and harvest index. While in timely sowing condition (D 2 ) seed yield per plant showed significant and positive correlation with longest basal leaf length, umbels per plant, umbellets per plant, Table-3: Direct effects of eleven characters on seed yield in three environments Characters D1 D2 D3 Days to 50% flowering Plant height (cm) No. of basal leaves Longest basal leaf length (cm) No. of fruit bearing branches Umbels per plant Umbellets per plant Seeds per umbel seed weight (g) Days to maturity Harvest index (%) Residual effect D 1 -First date of sowing (Early) D 2 -Second date of sowing (Timely) D 3 -Third date of sowing (Late) The results of path coefficient analysis revealed (Table-3) that the days to 50% flowering, 100-seed weight, plant height, number of basal leaves, longest basal leaf length, umbels per plant and umbellets per plant (D 1 ) harvest index, days to 50% flowering, longest basal leaf length, umbels per plant, umbellets per plant, seeds per umbel and 100-seed weight (D 2 ) days to 50% flowering, plant height, number of basal leaves, number of fruit bearing branches and umbellets per plant weight (D 3 ) exhibited high and positive direct effects on seed yield per plant. Thus, these characters turned-out to be the major components of seed yield and direct selection for these traits would be rewarding for yield improvement. Similar results were reported by (5, 6). The residual effect was of low magnitude suggesting that the majority of the yield attributes have been included in the path analysis. Thus, the material studied is of diverse nature and information emanated would help in designing the selection methodology which can be further used in the breeding programme for improvement of seed yield. REFERENCES 1. Panse, V.G. and Sukhatme, P.V. (1985). Statistical methods for Agricultural Workers, ICAR Publications New Delhi. 2. Burton G. W. and DeVane, E. H. (1953). Estimation of heritability in tall festuca (Festuca arundinacea) from replicated clonal material. Agron. J. 45: Al-Jibouri H.A., Millar P.A. and Robinson H.F. (1958). Genotype and environmental variance and co-variance in an upland cotton cross of interspecific origin. Agron. J. 50: Dewey J.R. and Lu K.H. (1959). A correlation and path analysis of components of crest wheat grass and seed production. Agron J. 51: Singh D., Jain U.K., Rajput S.S., Khandelwal V., and Shiva K.N. (2006). Genetic variation for seed yield and its components and their association in coriander (Coriandrum sativum L.) germplasm. J. of Spices and Aromatic Crops 15 (1): Meena M.L. Kumar Vikas, Kumar Sanjay, Yadav Y.C. and Kumar Adesh (2010). Genetic variability, heritability, genetic advance, correlation coefficient and path analysis in coriander. Indian J. Hort. 6: Burton G. W. (1952). Quantitative inheritance in grasses. Proc. 6th Int. Grassland Cong. 1:

5 Darvhankar et al., 351