Genetic variability and character association studies in French bean (Phaseolus vulgaris L.) under North-Western Himalayas

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1 Legume Research, 38 () 015 : Print ISSN: / Online ISSN: AGRICULTURAL RESEARCH COMMUNICATION CENTRE Genetic variability and character association studies in French bean (Phaseolus vulgaris L.) under North-Western Himalayas Jyoti Devi, Akhilesh Sharma, Yudhvir Singh, Viveka Katoch and Kumar Chand Sharma Department of Vegetable Science and Floriculture, College of Agriculture, C.S.K. Himachal Pradesh Agricultural University, Palampur , India. Received: Accepted: DOI: / ABSTRACT An attempt was made to determine the extent of genetic variability, association between different characters, direct and indirect effects of component traits on pod yield of bush French bean based on the evaluation of thirty three genotypes during summer 008 and 009. Sufficient variability was observed for all characters viz., days to flowering, days to first picking, average pod weight, pod length, pods/plant, plant height and pod yield/plant. High phenotypic and genotypic coefficient of variations were recorded for pod yield/plant and pods/plant in both the years and also pooled over years, indicating high potentiality of these traits for effective selection. These traits also showed high heritability coupled with high genetic advance in the respective years and in pooled years which indicated the role of additive gene action for the inheritance of these traits and are likely to respond better to selection. A positive and significant correlation of pod yield with days to flowering, average pod weight, branches/plant, pods/plant and plant height was observed, thereby emphasizing special focus on these traits for the improvement of yield. Path analysis exposed that pods/plant and average pod weight had highest positive direct effect during both the years and pooled over the years. Therefore, it might be concluded that pods/plant, branches/plant and average pod weight should be given due consideration for the improvement of pod yield/plant in French bean. Key words: Correlation, Heritability, Path coefficients, Phaseolus vulgaris L., Variability. INTRODUCTION French bean [(Phaseolus vulgaris L.), syn. kidney bean, haricot bean, snap bean, navy bean, string bean] is one of the most important leguminous vegetable, which is grown for fresh pod consumption and for processing as a frozen vegetable in many countries. It is an annual, diploid (n=x=) species derived from wild ancestors distributed from northern Mexico to north western Argentina (Galvan et al., 003). It is rich source of fiber, protein, vitamins (Dursun, 007) and has a major role as food legume (Salehi et al., 008). In India, it is commercially cultivated in Himachal Pradesh, Jammu and Kashmir, Hills of Uttrakhand, Northeastern states and peninsular India, covering an area of about, 07,500 ha with annual production of 5,8,00 tonnes (Anonymous, 010). Short duration and quick growing habit of plants, high yield, quality of fresh produce and sloughing free cultivars for canning industry, short pods for whole processing and resistance to pest and diseases are the main criteria under consideration for its genetic improvement. Despite constant breeding efforts, its average yield is low due to unsuitable cultivars, genetic drift in the cultivars and *Corresponding author s akhilesh.palampur@yahoo.com. development of new pathogen races. Therefore, to enhance productivity, genetic restructuring of French bean germplasm is required to develop high yielding varieties with desired traits. For the improvement of yield and other desirable characters, a knowledge of the magnitude of variation in the available genotypes, the relation of characters with yield, extent of environmental influences on these traits and the heritability of the characters is essential (Saifullah and Rabbani, 009). Since yield is a complex trait, indirect selection through correlated, less complex and easier measurable traits would be an advisable strategy to increase the yield. Efficiency of indirect selection depends upon the magnitude of association between yield and yield related traits (Esposito et al., 009). Correlation coefficient, in general, shows association among characters (Toker and Cagirgan, 004). However, correlation studies do not provide the exact picture of relative importance of direct and indirect effects of each of the component characters. Path analysis has been used by the breeders (Ali et al., 009) to identify the traits that are useful selection criteria to improve crop yield as it

2 150 LEGUME RESEARCH identifies the causes, measure and relative importance of the association, and is used to determine the amount of direct and indirect effects of causal components on the effect component (Dewey and Lu, 1959). There are several methods to study genetic diversity using morphological, cytological and biochemical markers and more recently through DNA based technologies (Akbar et al., 010), but knowledge of the phenotype given by morphological and agronomical descriptors is still important (Sudre et al., 010) for the assessment of genetic diversity and considered as a good source of information for the breeders with the target traits (Yadeta et al., 011). In relation to breeding programs, Falconer (1981) emphasizes that when the genotypes are evaluated in more than one season with the objective of quantifying the diversity found in the interaction, evaluation of genetic diversity in more than one environment could bring forth more clarifying results on the behavior of genotypes with a subsequent influence on the performance of these in future breeding programs (Teixeira et al., 004). Considering all the facts described above, study was undertaken using thirty three genotypes of bush type French bean to analyze the relationship between yield component, association among desired traits and their direct and indirect contributions toward the pod yield. MATERIALS AND METHODS The present investigation was undertaken at the Experimental Farm, Department of Vegetable Science and Floriculture, HP Agricultural University, Palampur (190.8 m amsl, with latitude N, longitude E). The experimental material comprised of 33 genotypes (Table 1), laid out in randomized complete block design with three replications for two seasons (March-June 008 and 009). The plot size was two rows of.7 m length with spacing of 0.45 m between rows and 0.15 m between plants within rows. The seeds were sown at a depth of 4-5 cm. The crop was well managed for optimum growth and yield. The observations were recorded on randomly taken ten plants of each genotype for nine traits in each replication viz., days to flowering, days to first picking, pod width (cm), pod length (cm), average pod weight (g), branches/plant, pods/ plant, plant height (cm) and pod yield/plant (g). Analysis of variance was performed for individual season and error variance was tested for homogeneity (Gomez and Gomez, 1983). The combined analysis of variance of two season s data was performed for each trait. The genotypic and phenotypic variations and heritability were estimated by following method of Burton and De Vane (1953). Genetic advance (GA) was calculated as per Burton and De Vane (1953) and Johnson et al. (1955). Coefficients of correlation were calculated as suggested by Al-Jibouri et al. (1958) while path coefficients of different traits with pod yield per plant were carried out as per Dewey and Lu (1959). The parameters of variability were estimated following Burton and De Vane (1953) as: g Genotypic coefficient of variation (GCV %) = 100 X p Phenotypic coefficient of variation (PCV %)= 100 X TABLE 1: List of genotypes used in the experiment collected from different agencies in India Sr. No. Genotypes Source Sr. No. Genotypes Source 1. Arka Suvidha IIHR, Hasarghata 18 KPV- CSKHPKV, Palampur. Arka Anoop IIHR, Hasarghata 19 MFB-1 NEH, ICAR, Barapani 3. DPDFB-1 CSKHPKV, Palampur 0 MFB- NEH, ICAR, Barapani 4. DPDFB-1(M) CSKHPKV, Palampur 1 MFB-3 NEH, ICAR, Barapani 5. DPDFB-(M) CSKHPKV, Palampur MFB-4 NEH, ICAR, Barapani 6. DWDFB-I UAS, Dharwad 3 MFB-5 NEH, ICAR, Barapani 7. DWDFB-53 UAS, Dharwad 4 VLB-8 VPKAS, Almora 8. DWDFB-57 UAS, Dharwad 5 VLB-9 VPKAS, Almora 9. HAFB-1 HARP, Ranchi 6 VLB-003 VPKAS, Almora 10. HAFB- HARP, Ranchi 7 VLFB-130 VPKAS, Almora 11. HAFB-3 HARP, Ranchi 8 Aparna Prabhakar Hybrid Seed Company, Hyderabad 1. HAFB-4 HARP, Ranchi 9 Chandini Sutton and Sons (India) Pvt. Ltd. 13. IVRFB-1 IIVR, Varanasi 30 Falguni Seminis Vegetable Seeds (India) Ltd. 14. IVFB-1 IIVR, Varanasi 31 Surya Solar Seeds 15. IVFB- IIVR, Varanasi 3 Arka Komal IIHR, Hasarghata 16. IVFB-3 IIVR, Varanasi 33 Contender CSKHPKV, Palampur 17. JFB-97-1 GAU, Junagadh

3 Volume 38, Issue, Where g, p, and X are genotypic standard deviation, phenotypic standard deviation and population mean, respectively. g Heritability (h ) = 100 bs g + e Where, g and e are genotypic and environmental variance, respectively, and g + e = phenotypic variance. The expected genetic advance (GA) resulting from the selection of 5 % superior individuals was calculated as: GA= k. p.h Where, k =.06 (selection differential at 5% selection intensity) Expected GA Genetic advance (% of mean) = 100 X Limits used for categorizing the magnitude of different parameters are as under: Component High (%) Moderate Low (%) (%) GCV and PCV More than Less than 10 Heritability More than Less than 49 Genetic advance More than Less than 4 RESULTS AND DISCUSSION The genotypes were significantly differ for majority of the characters during both the years and pooled over years with few exceptions viz., pod width and branches/ plant during 008 and 009 along with average pod weight during 009 (Table ). There were significant genotypic x environmental interactions for yield and related traits except pod width and branches/plant. The results showed sufficient genetic variability for these characters. The F-test of homogeneity over years showed significant differences for majority of the traits except pod yield/plant which suggests that interpretation of the results on the basis of pooled over years would not provide clear picture. Hence, the results of the individual years along with pooled over years have been discussed. On the basis of mean performance with respect to character of horticultural importance, the genotypes Arka Suvidha and MFB-5 gave similar performance for earliness to flowering as that of standard check Contender and Arka Komal during 008, 009 and also pooled years (Table 3a). However, VLB-8 took minimum days to first picking. Similar findings with range of variation for earliness with a different set of genetic material at different location have been reported by Singh (006). Consumers prefer round, slender and medium sized pods. Accordingly, significant minimum pod width and pod length was observed for DPDFB-1, Falguni, Chandani and Surya over the years. These genotypes also got less pod weight in comparison to standard check Contender (Table 3b). In general, more number of branches leads to increased number of pods/plant and resulted in high pod yield. This was quite evident from the performance of the genotype Aparna with first rank for pod yield/ plant and pods/plant followed by DPDFB-1 during both the years and pooled over the years. Falguni and Surya had good pod bearing with small and slender pods and had also significantly out yielded both the standard checks. Higher phenotypic coefficient of variation than genotypic coefficient of variation (Table 4) indicated that most of the yield attributes were under the influence of environment (Ghosh et al., 010). Since the phenotypic and genotypic variances do not have clear-cut limits and their categorization as high or low is difficult, therefore, unsuitable for comparing the population when expressed in absolute values. Consequently, high value of PCV and GCV were recorded for pod yield/plant and pods/plant for both the years and pooled over the years, indicating high potential of these traits for effective selection (Burton, 195). High PCV and GCV value for pods/plant were also reported by Kamaluddin (011) TABLE : Analysis of variance for different characters in French beans during the years 008, 009 and pooled over years Characters Replication Genotype (G) Error Genotype (G) I II I II I II Mean sum of squares Pooled over years Environment (E) df G x E Error F-Test (Homogeneity test Days to 50% flowering * 6.84 * * 8.91 * 6.91 * 1.81 *.51 * Days to seed maturity * 0.54 * * * 9.33 * Pods/plant * * * * 3.45 * 4.33 * Pod length (cm) * 8.54 * * * Seeds/pod * Plant height (cm) * 5.68 * * * * 4.94 *.9* 100-seed weight(g) * 83.5 * * * 35.6 * 7.04 * 1.16 Seed yield/ plant (g) * 8.4 * * * * * 1.73 * Significance at 5% level; Where, I and II depicts the respective years 008 and 009

4 15 LEGUME RESEARCH TABLE 3(a): Mean performances of different genotypes for phonological and pod characters Genotypes Days to flowering Days to first picking Pod width (cm) Pod length (cm) I II Pool I II Pool I II Pool I II Pool Arka Suvidha Arka Anoop DPDFB DPDFB-1 (M) DPDFB- (M) DWDFB-I DWDFB DWDFB HAFB HAFB HAFB HAFB IVRFB IVFB IVFB IVFB JFB KPV MFB MFB MFB MFB MFB VLB VLB VLB VLFB Aparna Chandini Falguni Surya Arka Komal Contender CD (P 0.05) Where, I and II depicts the respective years 008 and 009 in his study. Further, these estimates were moderate for average pod weight and branches/plant. High heritability estimates were observed for pod yield/plant and pods/plant for both the years and pooled over the years. Hence, high magnitude of it indicates the reliability with which a genotype can be recognized by its phenotypic expression (Lush, 1940). Such a high heritability was also reported by Rai et al. (010) and Junaif et al. (011). Johannsen (1909) stressed that for estimating the actual effects of selection, heritability alone could not be the sole guideline for improvement since high heritability does not mean high expected genetic advance. Hence, prediction on the basis of both the estimates could be more useful. In this context, high heritability and high genetic advance were noticed for pod yield/plant and pods/plant which indicated the role of additive gene action for the inheritance of these traits and are likely to respond better to selection. Correlation study for pod yield showed a positive and significant correlation with days to flowering, average pod weight, branches/plant, pods/plant and plant height on pooled basis, suggesting improvement of yield by giving special focus to these traits (Table 5). Mishra et al. (008)

5 Volume 38, Issue, TABLE 3(b): Mean performances of different genotypes for pod yield and related traits Genotypes Average pod Branches/plant Pods/plant Plant height(cm) Pod yield/ plant(g) weight (g) I II Pool I II Pool I II Pool I II Pool I II Pool Arka Suvidha Arka Anoop DPDFB DPDFB-1M DPDFB-M DWDFB-I DWDFB DWDFB HAFB HAFB HAFB HAFB IVRFB IVFB IVFB IVFB JFB KPV MFB MFB MFB MFB MFB VLB VLB VLB VLFB Aparna Chandini Falguni Surya Arka Komal Contender CD (P 0.05) Where, I and II depicts the respective years 008 and 009 also reported high correlation of pod yield with pods/plant. Similarly, correlation between other traits showed a positive association between days to flowering and days to first marketable picking indicating that early flowering genotypes would be an appropriate selection criterion to get early yield. These findings corroborate the earlier observations of Sharma et al. (010). Similarly, a positive association of plant height and branches/plant with number of pods/plant revealed that improvement in these traits would enhance pods/plant and ultimately yield. Path analysis on pooled basis exposed that pods/ plant and average pod weight have highest positive direct effect, suggesting the importance of these traits in selection programme for improving yield (Table 6). High direct effect of pods/plant on pod yield/plant was also reported by Rai et al. (010). The study showed that pods/plant had maximum indirect contribution on total association of days to flowering, branches/plant and plant height which resulted into significant positive correlation of these traits with pod yield/plant. The low magnitude of residual effects indicated that the traits included in the present investigation accounted for most of the variation present in the dependent variable. In view of the direct and indirect contributions of component traits, selection on the basis of average fruit weight, plant height and pods/plant would be a paying preposition for evolving high yielding genotypes. It may be concluded that pods/plant, branches/plant and average pod weight should be given due consideration for the improvement of pod yield/plant in French bean.

6 154 LEGUME RESEARCH TABLE 4: Parameters of genetic variability for pod yield and related traits of French bean Characters Coefficients of variation Heritability (h )(%) Genetic advance(% of mean) Phenotypic (PCV) Genotypic (GCV) I II Pool I II Pool I II Pool I II Pool Days to flowering Days to first picking Pod width(cm) Pod length (cm) Average pod weight (g) Branches/ plant Pods/ plant Plant height (cm) Pod yield/ plant (g) Where, I and II depicts the respective years 008 and 009 Trait Days to flowering Days to first picking TABLE 5: Phenotypic correlation coefficients for pod yield and other traits in French bean Days to first picking Pod width Pod length Average pod weight * Significance at 5% level; Where, I and II depicts the respective years 008 and 009 Branches/ plant Pods/ plant Plant height Pod yield/ plant I * * * * * * II * * Pool * -0.0 * * * 0.6 * I * * 0.15 II * * Pool * Pod width I II * * * Pool 0.9 * Pod length I II * * 0.3 * Pool 0.05 * -0.7 * Average pod weight I * II * Pool * Branches/ plant I * 0.81 * 0.41 * II * 0.53 * * Pool 0.43 * 0.68 * * Pods / plant I 0.06 * * II * 0.90 * Pool * * Plant height I 0.36 * II * Pool *

7 Volume 38, Issue, TABLE 6: Path coefficient analysis of different characters with pod yield/ plant Trait Days to Days to Pods Pod Average Branches/ Pods/ Plant flowering first width length pod plant plant height picking weight Days to I flowering II Pool Days to I first picking II Pool Pods width I II Pool Pod length I II Pool Average I pod weight II Pool Branches/ I plant II Pool Pods/ plant I II Pool Plant height I II Pool Correlation I * * 0.41 * * 0.36 * with pod II * 0.9 * 0.47 * yield/plant Pool 0.9 * * * * * Residual effect: 0.19 (I), 0. (II) and 0.4 (Pool) Where, I and II depicts the respective years 008 and 009; * Significance at 5% level REFERENCES Akbar, N., Ahmad, H., Ghafoor, S., Begum, K., Afridi, S.G., Muhammad, I. and Khan, I.A. (010). Estimation of genetic diversity in capsicum germplasm using randomly amplified polymorphic DNA. Asian J. Agric. Sci. (): Ali, M.A., Nawad, N.N., Abbas, A., Zulkiffal, M. and Sajjad, M. (009). Evaluation of selection criteria in Cicer arietiunum L. using correlation coefficients and path analysis. Australian J. Crop Sci. 3() : Al-Jibouri, H.A., Millar, P.A. and Robinson, H.F. (1958). Genotypic and environmental variances and covariances in an upland cotton cross of interspecific origin. Agron. J. 50: Anonymous. (010). Food and Agricultural Organization of United Nations : Economic And Social Department : The Statistical Devision. Burton, G.M. (195). Quantitative inheritance in grasses. Proc. 6 th Int. Grassland Cong. 1: Burton, G.W. and De Vane, E.H. (1953). Estimating heritability in tall fescue (Festuca arundinaceae) from replicated clonal material. Agron. J. 54: Dewey, D.R. and Lu, K.H. (1959). A correlation and path analysis of components of crested wheat-grass seed production. Agron. J. 51: Dursun, A. (007). Variability, heritability and correlation studies in bean (Phaseolus vulgaris L.) genotypes. World J. of Agric Sci. 3(1): Esposito, M.A, Martin, E.A, Cravero, V.P, Liberatti, D., Lopez, A., Fernando, S. and Cointry, E.L. (009). Relationship among agronomical traits and seed yield in pea. J. Basic and Appl.Gen. 0(1): Falconer, D.S. (1981). Introducao a genetica quantitativa. Traduçao MA Silva and JC Silva. Imprensa Universitária, Viçosa, 79p.

8 156 LEGUME RESEARCH Galvan M.Z., Bornet, B., Balatti, P.A. and Branchard, M. (003). Inter simple sequence repeat (ISSR) markers as a tool for the assessment of both genetic diversity and gene pool origin in common bean (Phaseolus vulgaris L.). Euphytica. 13: Ghosh, K. P., Islam, A. K. M. A., Mian, M. A. K. and Hossain, M. M. (010). Variability and character association in F segregating population of different commercial hybrids of Tomato (Solanum lycopersicum L.). J. Appl. Sci. Environ. 14(): Gomez, A.A. and Gomez, K.A. (1983). Statistical Procedure for Agriculture Research, nd Ed. John Willey and Sons, Inc. New York, p Johannsen, W.L. (1909). Elemente der exakten Erblickkeits lehre, Fisher, Jewa. Johnson, H.W., Robinson, H.F. and Comstock, R.E. (1955). Estimation of genetic and environmental variability in soybean. Agron. J. 47: Junaif, N., Wani, K.P., Khan, S.H., Jabeen, N., Mushtaq, F. and Ummyiah, H.M. (010). Genetic variability in dwarf French bean (Phaseolus vulgaris L.). Asian J. Hort. 5(1): Kamaluddin, A.S. (011).Variability, correlation and path analysis for seed yield and yield related traits in common beans. Indian J. Hort. 68(1): Lush, J.L. (1940). Inter-sire correlation and regression of offspring on damasasa method of estimating heritability characters. Proc. Amer. Soc. Anim. Prod. 33: Mishra, S., Kumar, M. and G.S. Sahu. (008). Relationships among yield contributing characters in pole type Frenchbean (Phaseolus vulgaris L.). Orissa J. Hort. 36(): Rai, N., Singh, P.K., Verma, A., Yadav, P.K and Choubey, T. (010). Hierarchical analysis for genetic variability in pole type french bean. Indian J. Hort. 67 (special issue): Saifullah, M. and Rabbani, M.G. (009). Evaluation and characterization of okra (Abelmoschus esculentus L. Moench.) genotypes. SAARC J. Agri. 7(1): Salehi, M., Faramarzi, A. and Mohebalipour, N. (010).Evaluation of different effective traits on seed yield of common bean (Phaseolus vulgaris L.) with path analysis. American Eurasian J. Agri.and Env. Sci. 9(1): Sharma, V.K., Semwal, C.S. and Uniyal, S.P. (010). Genetic variability and character association analysis in bell pepper (Capsicum annuum L.). J.Hort and Forestry. (3): Singh, A.K. (006). Genetic divergence in french bean (Phaseolus vulgaris L.). Vegetable Science 33(1): Sudre, C.P. Gonçalves, L.S.A., Rodrigues, R., Amaral-Junior, A.T. do., Riva-Souza, E.M. and and Bento, C.D.S. (010). Genetic variability in domesticated Capsicum spp as assessed by morphological and agronomic data in mixed statistical analysis. Genetics and Molecular Res. 9(1): Teixeira, A.B., Amaral-Junior, A.T. do., Rodrigues, R., Pereira, T.N.S. and Bressan-Smith, R.E. (004). Genetic divergence in snap-bean (Phaseolus vulgaris L.) evaluated by different methodologies. Crop Breed. and Applied Biotec. 4:57-6. Toker, C. and Cagirgan, M.I. (004). Use of phenotypic correlations and factor analysis in determining characters for grain yield selection in chickpea (Cicer arietinum L.). Hereditas. 140():6-8. Yadeta, B., Belew, B., Gebreselassie, W. and Marame, F. ( 011). Variability Heritability and genetic advance in Hot pepper (Capsicum annuum L.) genotypes in West Shoa,Ethiopia. American- Eurasian J.Agric. and Environ.Sci. 10(4):

Studies on Genetic Variability, Association of Characters and Path Analysis in French Bean (Phaseolus vulgaris L.)

Studies on Genetic Variability, Association of Characters and Path Analysis in French Bean (Phaseolus vulgaris L.) Available online at www.ijpab.com Lad et al Int. J. Pure App. Biosci. 5 (6): 1065-1069 (2017) ISSN: 2320 7051 DOI: http://dx.doi.org/10.18782/2320-7051.5757 ISSN: 2320 7051 Int. J. Pure App. Biosci. 5