Abstract. String bean, heritability, genetic advance, correlation, path analysis.

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1 Jahangirnagar University J. Biol. Sci. 1(1): 1-10, 2012 (June) Genetic variability, correlation and path analysis for yield and its component characters in string bean (Vigna unguiculata ssp. sesquipedalis [L Verdc.) A. K. M Mahmudul Huque, M. K. Hossain, N. Alam*, M. Hasanuzzaman 1, B. K. Biswas 1 and M. Arifuzzaman 1. Department of Botany, Jahangirnagar University, Savar, Dhaka-1342, Bangladesh. Abstract Biometrical analysis of yield and its contributing characters was made for string bean with the use of thirteen genotypes. Phenotypic variation was greater than that of genotypic and environment variations for all the characters concerned. Minute differences between genotypic and phenotypic coefficient of variation indicated less environmental influences on considered characters. High heritability in broad sense and genetic advance estimated for the characters viz., pod yield per plant ( % and %), number of pods per plant ( % and %) and number of cluster per plant ( % and %). Significant and positive correlation both at genotypic as well phenotypic level was noticed between number of nodes per plant and number of primary branches per plant, days to first flowering and days to 50% flowering, days to 95% pod maturity, number of pods per plant and number of cluster, and number of pods per plant and number of pod per cluster. Plant height (cm), days to first flowering, days to 50% flowering and days to 95% pod maturity were negatively correlated with pod yield per plant (g) both at genotypic and phenotypic level. Path analysis revealed that number of pods per plant, Pod length (cm), number of cluster per plant and primary branches per plant were the major direct contributors to pod yield per plant. Key words: String bean, heritability, genetic advance, correlation, path analysis. INTRODUCTION: String bean (Vigna unguiculata ssp. sesquipedalis [L.] Verdc.) is an important summer vegetable of Bangladesh. It is commonly known as vegetable cowpea and in bengali barboti. At present string bean is cultivated in ha. of land in Bangladesh and the annual production is 21,348 tons with a national average of 3.64 t/ha. (Anon., 2009) which is much low in comparison to other Asian countries (Anon., 1993). Despite its importance as a common summer vegetable, no comprehensive systematic research has been done yet on this crop in Bangladesh to develop a high yielding string bean variety having broad genetic base and minimum vulnerability to various biotic and abiotic stresses for their long term sustainability in the country. An effective breeding programme, more specifically of selection, depends upon the variability of breeding materials. To get the idea of the genetic variability existing among the varieties with regard to quantitative characters of economic importance it becomes 1 Department of Genetics and Plant Breeding, Hajee Mohammad Danesh Science and Technology University, Dinajpur-5200, Bangladesh. * Author to whom all correspondences should be made.

2 2 Huque et al. necessary to study them under an array of distinguishable environments through statistical analysis (Hossain et al., 2000). Considering the above facts the present investigation was undertaken to facilitate the development of genotypes for high yield constraints by producing an index of parental lines. MATERIALS AND METHODS: The materials for the study comprised of thirteen commercial genotypes of string bean, collected from Lal Teer Seed Ltd., Ripa Seed Co., Masud Seed Co., Namdhari Seed Co. Ltd., Kashem Seed Co., Banashree Agro Seed Co., Bangladesh Agricultural Development Corporation And Bangladesh Agricultural Research Institute. The experiment was conducted at botanical garden, Jahangirnagar University, Savar, Dhaka, Bangladesh during kharif season, 2011, following randomized complete block design (RCBD). Plot size was 4.0 m x 4 m with 1.0 m spacing between rows and 0.3 m between plants in a row. Plants were trailed on coir ropes tied between wooden stakes erected 1.0 m apart along rows of plants. Recommended doses of fertilizer, irrigation, weeding, mulching and other cultural practices were done as and when required. Data were collected from five randomly selected plants from each plot and analyzed statistically. Genotypic and phenotypic variance was estimated according to Johnson et al. (1955) and genotypic and phenotypic coefficients of variations were estimated by Burton (1952). Heritability in broad sense was calculated by Singh and Chaudhury, The expected genetic advances for different characters were estimated according to Johnson et al. (1955) and Allard (1960) and genetic advance expressed as percentage of mean were estimated by Comstock and Robinson (1952). Genotypic and phenotypic correlation coefficients were calculated according to Miller et al., (1958) and path coefficient analysis according to Singh and Chaudhury (1985) and Dabholkar (1992) that were originally suggested by Dewey and Lu (1959). RESULTS AND DISCUSSION: The estimates of range, mean, genotypic variance (σ 2 g), phenotypic variance (σ 2 p), genotypic coefficient of variation (GCV), Phenotypic coefficient of variation (PCV), heritability (h 2 %), genetic advance (GA) and genetic advance as % of mean (GA %) for the different characters are shown in Table 1. The wide range especially for plant height (cm), number of pods per plant and pod yield per plant (g) indicated the rich diversity among the available string bean genotypes. The phenotypic variance (σ 2 p) and phenotypic coefficient of variation (PCV) were slightly higher than corresponding genotypic variance (σ 2 g) and genotypic coefficient of variation (GCV) for most of the characters indicated the presence of less environmental effect upon the concerned characters.

3 Genetic variability, correlation, path analysis, yield, string bean 3 Table 1. Estimates of genetic parameters for various yield contributing characters in different genotypes of string bean. Characters Range Mean Genotypic Phenotypic Heritability Genetic Genotypic Phenotypi Genetic coefficient of coefficient of in broad advance as variance c variance advance variation variation sense % of mean (σ 2 g) (σ 2 p) (GA) (GCV) (PCV) (h 2 %) (GA %) Plant height (cm) Number of nodes per plant Number of primary branches per plant Terminal leaflet length (cm) Terminal leaflet breadth (cm) Days to first flowering Days to 50% flowering Days to 95% pod maturity Length of harvesting time Number of cluster per plant Length of cluster stalk (cm) Number of pods per cluster Number of pods per plant Pod length (cm) Pod girth (mm) Seed number per pod seed weight Pod yield per plant (g)

4 4 Huque et al. The Genotypic coefficient of variation (GCV) was maximum for number of cluster per plant followed by pod yield per plant (g) and number of pods per plant (Table 1). This suggested the scope for improvement of these characters through selection. High GCV and PCV for pod yield and number of pods per plant were earlier reported by several workers (Rajaravindran and Das, 1997; Resmi, 1998; Vardhan & Savithramma, 1998 and Vidya et al., 2002b). Heritability estimates were relatively higher for most of the characters studied. High values of heritability coupled with high genetic advance (GA) as percentage of mean were obtained for pod yield per plant (g), number of pods per plant and number of cluster per plant (Table 1) is indicative of additive gene action and selection based on these parameters would be more reliable which was same as by Sobha (1994), Sreekumar et al. (1996), Resmi (1998), Vardhan & Savithramma (1998) and Vidya et al. (2002b). Character association: The association of pod yield with other characters was estimated by genotypic and phenotypic correlation coefficient (Table 2). The values of the genotypic correlation coefficients in general were higher than those of the phenotypic correlation coefficients indicated the association in largely due to genetic reason. Genotypic correlation of pod yield per plant was found highly significant and positive for number of pods per cluster, pod length, number of cluster per plant, seed number per pod and number of pods per plant (Table 2) and nominal position for number of primary branches per plant and length of harvesting time which was in close conformity with the results of Sobha (1994), Sreekumar et al. (1996), Resmi (1998) and Vardhan & Savithramma (1998) and Vidya and Ooman (2002a). Pod yield per plant was found to be significantly correlated with pod length, seed number per pod, number of pods per plant and number of cluster per plant and number of pods per cluster was found to be moderately correlated with pod yield per plant at phenotypic level which was highly significant at genotypic level (Table 2). Number of pods per plant showed highly significant positive correlation with number of cluster per plant both at genotypic and phenotypic level and number of pods per cluster showed high significant positive correlation with number of pods per plant at genotypic level, but moderate significant positive correlation at phenotypic level (Table 2). Similar results were obtained by Resmi (1998). Number of primary branches per plant was significantly and positively associated with number of nodes per plant both genotypically and phenotypically. Days to 50% flowering was significantly correlated with days to first flowering both at genotypic and phenotypic level and Days to 95% pod maturity was significant and positively correlated with days to first flowering and days to 50% flowering both genotypically and phenotypically. Length of harvesting time showed moderately significant positive genotypic correlation with pod yield per plant but no significant correlation at phenotypic level. Seed number per pod was positively correlated with pod length both at genotypic and phenotypic level.

5 Genetic variability, correlation, path analysis, yield, string bean 5 3 Table 2. Genotypic (r g ) and phenotypic (r p ) correlation among different yield contributing traits in different genotypes of string bean. NN NPb DFF D50%F D95%M HT PL PG NC PC NPd SP SW YP PH r g r p NN r g 0.937** r p 0.827** NPb r g * r p DFF r g 0.975** 0.923** r p 0.969** 0.870** D50%F r g 0.970** r p 0.918** D95%M r g r p HT r g * r p PL r g ** ** r p ** ** PG r g ** r p NC r g ** ** r p 0.618* 0.798** ** NPC r g 0.931** ** r p 0.622* * NPd r g ** r p ** SP r g ** r p ** SW r g r p *and ** indicate the significant at 5% and 1% level of probability, respectively. PH = Plant height, NN = No. of nodes / plant, NPb = No. of primary branches / plant, DFF = Days to first flowering, D50%F = Days to 50% flowering, D95%M = Days to 95% pod maturity, HT = Harvesting time, PL = Pod length (cm), PG = Pod girth (mm), NC = No. of clusters / plant, NPC = No. of pods / cluster, NPd = No. of pods / plant, SP = Seed no. / pod, SW = Seed weight, YP = Pod yield / plant.

6 6 Huque et al. Table 3: Direct (Diagonal) and indirect effect of various yield contributing characters on pod yield per plant (g) in string bean. PH NN NPb DFF D50%F D95%M HT PL PG NC PC NPd SP SW r withyp PH r g r p NN r g r p NPb r g r p DFF r g r p D50%F r g r p D95%M r g r p HT r g r p PL r g r p PG r g r p NC r g r p NPC r g r p NPd r g r p SP r g r p SW r g r p Residual Effect, At genotypic level = ; At phenotypic level = PH = Plant height, NN = No. of nodes / plant, NPb = No. of primary branches / plant, DFF = Days to first flowering, D50%F = Days to 50% flowering, D95%M = Days to 95% pod maturity, HT = Harvesting time, PL = Pod length (cm), PG = Pod girth (mm), NC = No. of clusters / plant, NPC = No. of pods / cluster, NPd = No. of pods / plant, SP = Seed no. / pod, SW = Seed weight, YP = Pod yield / plant.

7 Genetic variability, correlation, path analysis, yield, string bean 7 No significant negative correlation was recorded for any pair of traits both at genotypic and phenotypic level (Table 2). Corroborative reports of significant negative correlation between days to first flowering and number of pods per plant by Sreekumar et al. (1996) and between days to first flowering and number of pods per cluster by Resmi (1998) does not support this finding. Significant positive correlation of vegetable pod yield with number of pods per cluster, number of cluster per plant, number of pods per plant, pod length, number of primary branches per plant and length of harvesting period imply that selection for these characters would lead to simultaneous improvement of yield in string bean. Path coefficient analysis: Relationship between yield and yield contributing characters were studied in details through path coefficient analysis. Path coefficient analysis performed to disclose the causes and effects of chain relationships of different yield contributing characters with yield. The estimates of direct and indirect effects of these characters on yield based on genotypic and phenotypic correlation are presented in Table 3 and Fig. 1. Path coefficient analysis showed that number of pod per plant had maximum direct effect on pod yield per plant followed by number of cluster per plant, pod length, number of primary branches per plant, length of the harvesting time, days to first flowering, pod girth, number of pod per cluster, number of nodes per plant, and 100 seed weight (Table 3) (Fig. 1). Similar observation made by Jana et al. (1983), Chattopadhyay et al (1997), Resmi (1998),Vardhan & Savithramma (1998b) and Vidya et al. (2002b) whereas days to 50% flowering, days to 95% pod maturity and seed number per pod showed negative direct effect towards pod yield per plant (Table 3). Number of pods per plant showed highest direct effect towards the pod yield per plant via maximum positive indirect effect of number of pods per cluster followed by pod length and number of cluster per plant, and maximum negative indirect effect of days to 50% flowering followed by number of nodes per plant (Table 3).

8 10 Huque et al. Fig. 1. Path diagram of different yield contributing characters on pod yield per plant at genotypic level. PH = Plant height, NN = No. of nodes / plant, NPb = No. of primary branches / plant, DFF = Days to first flowering, D50%F = Days to 50% flowering, D95%M = Days to 95% pod maturity, HT = Harvesting time, PL = Pod length (cm), PG = Pod girth (mm), NC = No. of clusters / plant, NPC = No. of pods / cluster, NPd = No. of pods / plant, SP = Seed no. / pod, SW = Seed weight, YP = Pod yield / plant. Number of pods per cluster exhibited highest positive correlation with pod yield per plant at genotypic level but showed very little direct effect towards vegetable pod yield due to high negative indirect effect via number of nodes per plant followed by days to 95% pod maturity, number of pods per plant and seed number per pod and number of primary branches per plant and number of nodes per plant although exhibited high and positive direct effects on pod yield per plant but their correlations with vegetable pod yield were minimum both at genotypic as well as phenotypic level due high negative indirect effects via days to 95% pod maturity, days to 50% flowering and pod girth (Table 2 & 3). The residual effect of the present study was for genotypic level and for phenotypic level indicating that the characters studied contributed 67.1% of the yield at genotypic level and 75.2% at phenotypic level, respectively. It is suggested that maximum emphasis should be given on the above characters for selecting string bean with higher yield.

9 Genetic variability, correlation, path analysis, yield, string bean 9 Due to high magnitude of genotypic coefficient of variation, heritability and genetic advance recorded for pod yield per plant and number of pods per plant in the present study, it is suggested that worthwhile improvement in these characters can be achieved through selection. Relationship between yield and yield contributing characters in different genotypes of string bean through genotypic and phenotypic correlations and path coefficients suggests that number of pods per plant, pod length, number of cluster per plant, number of primary branches per plant and length of the harvesting time were the most important characters as they exhibited high direct effects on pod yield per plant along with significant genotypic and phenotypic correlation coefficient. Therefore, selection for these characters would give better response to yield improvement. Residual effects and utilization of limited germplasm also suggested that further study should be made with more characters to find out other traits which contribute rest of the percentage of the yield and to provide an authentic picture. REFERENCES: Allard, R.W Principles of plant Breeding. John willey and sons. Inc. New York. pp. 36. Anonymous Yearbook of Agricultural Statistics of Bangladesh. Bangladesh Bureau of Statistics, Ministry of Planning, Govt. of People s Republic of Bangladesh, Dhaka, Bangladesh. pp Anonymous AVNET Final Report, Asian Vegetable Research and Development Center in Southeast Asia, Taipei, pp Burton, G.W Quantitative inheritance in grasses. Proc. Siathi. Int. Grassland Congr. 1: Chattopadhyay, A., Dasgupta, T., Hazra, P. & Som, M.G Character association and path analysis in vegetable cowpea. Madras agric. J. 84: Comstock, R.E. & Robinson, H.E Genetic parameters, their estimation and significance. Proc. 6th Int. Grassland Cong. 1: Dabholkar, A.R Elements of Biometrical Genetics. Concept publishing company, New Delhi, India. pp Dewery, D.R. & Lu, K.H A correlation and path coefficient analysis of components of crested wheat grass seed production. Agron. J. 51: Hossain, M., Sarker, K.A., Islam, R., Anisuzzaman, M. & Alam, F.M Estimates of variability and heritability and genetic advance in black gram (Vigna mungo). Bangladesh J. Genet. Biotech. 1(1): Jana, S., Som, M.G. & Das, M.D Correlation and path analysis of vegetable pod yield components in cowpea (Vigna unguiculata var. sesquipedalis). Haryana J. Hort. Sci. 12: Johnson, H.W., Robinson, H.D. & Comstock, R.E Estimates of genetical and environmental variability in soybeans. Agron. J. 41: Miller, P.A., Williams, J.C., Robinson, H.F. & Comstock, R.E Estimates of genetic and environmental variance and covariance and their implication in selection. Agron. J. 50:

10 10 Huque et al. Rajaravindran, R. & Das, L.D.V Variability, heritability and genetic advance in vegetable cowpea. Madras Agric. J. 84: Resmi, P.S Genetic variability in yard-long bean (Vigna unguiculata subsp. sesquipedalis (L.) Verdcourt). M.Sc.(Ag.) thesis, Kerala Agricultural. University, Thrissur, India. pp. 93. Singh, P.K. & Chaudhary, B.D Biometrical Methods in Quantitative Genetic Analysis. Kalyani publishers. New Delhi, India. pp Sobha, P.P Variability and heterosis in bush type vegetable cowpea (Vigna unguiculata (L.) Walp.). M.Sc.(Ag.) thesis, Kerala Agricultural. University, Thrissur, India. pp Sreekumar, K., Inasi, K.A., Alice, A. & Nair, R.R Genetic variability, heritability and correlation studies in vegetable cowpea (Vigna unguiculata var. sesquipedalis). South Indian Hort. 44(1&2): Vardhan, P.N.H. & Savithramma, D.L Variability, character association, path analysis and assessment of quality parameters in cowpea (Vigna unguiculata) germplasm for vegetable traits. ACIAR Food Legume Newsl. 28: 7-8. Vidya, C & Oommen, S.K. 2002a. Correlation and path analysis in yardlong bean. J. Trop. Agric., 40: Vidya, C., S. K. Oommen & V. Kumar. 2002b. Genetic variability and heritability of yield and related characters in yardlong bean. J. Trop. Agric., 40:

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