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Relationship Studies in Cowpea (Vigna unguiculata L. Walp) Landraces Grown under Humid Lowland Condition



O. Udensi, E.V. Ikpeme, E.A. Edu and D.E. Ekpe
 
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ABSTRACT

Establishing the extent of relationship, identifying the cause and measuring the relative importance of such associations to yield is very crucial for varietal selection, breeding and subsequent improvement of crops, especially cowpea landraces. This research x-rays correlation coefficients and path coefficients of yield and yield-influencing traits in cowpea landraces. Seeds of four varieties of locally grown cowpea were sown in a Randomized Complete Block Design (RCBD) in ten replications. The field study was carried out at the University of Calabar Experimental Farm, University of Calabar, Nigeria, during the 2010-2011 growing season. Correlation coefficients and path coefficients were computed on yield and yield-contributing traits. Results obtained revealed that significant relationships between yield and yield-contributing traits existed which could be indices for selection. Genotypic correlations coefficients were high and more significant than the phenotypic and environmental correlation coefficients. Path coefficient analysis shows that number of pod per plant had the highest direct effects to cowpea yield (0.588). This was followed by number of flowers (0.454), number of seeds per pod (0.366), leaf area at 5 weeks (0.366) and pod length and 100 seed weight (0.316), respectively. Other morphological traits had negative direct effects on seed yield such as vein length at 10 weeks (-0.627), number of leaves at 5 weeks (-0.215), number of leaves at 10 weeks (-0.033), leaf area at 10 weeks -1.124, days to 50% flowering (-0.083) and days to 50% maturity (-0.066). Succinctly, it therefore implies that number of pods per plant, number of leaves per plant, leaf area, number of flowers per plant, pod length and number of seeds per pod are good selection indices for a high yielding variety of cowpea, especially the landraces. This then can be exploited in hybridization programmes involving cowpea.

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O. Udensi, E.V. Ikpeme, E.A. Edu and D.E. Ekpe, 2012. Relationship Studies in Cowpea (Vigna unguiculata L. Walp) Landraces Grown under Humid Lowland Condition. International Journal of Agricultural Research, 7: 33-45.

DOI: 10.3923/ijar.2012.33.45

URL: https://scialert.net/abstract/?doi=ijar.2012.33.45
 
Received: August 04, 2011; Accepted: November 07, 2011; Published: January 03, 2012

INTRODUCTION

The fact that pulses have high adaptability potentials and high nutritive values especially the landraces, should be enough incentives for their exploration and exploitation if food security is anything to accord priority in Nigeria (Udensi et al., 2011a, b). Cowpea (Vigna unguiculata L. Walp) is one of the sixth major cultivated crop species of the family Leguminosae distributed throughout the tropics (Pasquet, 2001). The leaves, stems and seeds have been reported to have antimicrobial properties.

For two decades now, scientists in the field of genetic transformation of cowpea have made great strides with little success to develop reliable transformation systems for this crop that is very important as a good source of protein and energy for people in developing countries of Africa and Asia (Obembe, 2009). Grain legumes generally have been regarded as recalcitrant to transformation because of poor regeneration ability (especially via callus) and in vitro regeneration being genotypic-specific. Worst still, most cowpea cultivars are infrequently amenable to regeneration. There is also the problem of compatible gene delivery system (Somers et al., 2003; Chandra and Pental, 2003; Popelka et al., 2004). Other researchers in this field such as Sahoo et al. (2000) and Ikea et al. (2003) were however, not able to provide molecular evidence of stable transformation with Mendelian transmission of the transgenes to progeny. According to Popelka et al. (2006), Chaudhury et al. (2007), Ivo et al. (2008) and Solleti et al. (2008a, b) there are seeming roads at the end of the tunnel as regarding cowpea transformation and improvement though with little percentage transformation efficiency. These recent successes in cowpea genetic transformation have therefore paved way for the introduction of more agronomic traits to cowpea, thereby enhancing the genetic diversity of the crop and consequently complementing existing breeding programmes (Obembe, 2009). Additionally, molecular (DNA) or markers-assisted selection and improvement through Quantitative Trait Loci (QTLs) mapping has advanced successfully, the need to complement these approaches should not be overemphasized as more often than not local farmers and breeders are deprived of these high yielding genotypes (Udensi et al., 2010). Regrettably, since the Sub-Saharan Africa, indeed Nigeria is bedeviled with institutional and infrastructural problems coupled with the whooping sums of money involved in biotechnological processes, resting all our shoulders on these modern techniques might spell doom to future food security which is topical in vision 2020 agenda of the government in all tiers.

The study of relationships among quantitative traits is important for assessing the feasibility of joint selection of two or more traits and hence for evaluating the effect of selection for secondary traits on genetic gain for the primary traits under consideration (Umar et al., 2010). While correlation measures the mutual association between two variables (traits), path coefficient analysis on the other hand, identifies the cause and measures the relative importance of the association. Additionally, path coefficient analysis provides an effective means of partitioning correlation coefficients into unidirectional pathways and alternate pathways thus permitting a critical examination of specific factors that produce a given correlation which can be successfully employed in formulating an effective selection programme (Salahuddin et al., 2010). Importantly, path coefficient is synonymous to standardized coefficient of regression after a multiple regression analysis using data which are independent of original units of measurement (Cramer and Wehner, 2000b). The technique of path coefficient analysis has been extensively used by Azeem and Azhar (2006), Afiah and Ghoneim (2000), Cramer and Wehner (2000b) and Akinyele and Osekita (2006). Additionally, Iqbal et al. (2003) has used this method in soybean; Yadev et al. (2001), Arshad et al. (2003), Ghafoor et al. (2003) and Arshad et al. (2004) have used the technique in other legumes.

This presented study however, is aimed at selecting superior genotype(s) of cowpea landraces through correlation studies which could be exploited in hybridization programmes to develop and select hybrids with superior traits.

MATERIALS AND METHODS

Four landraces of cowpea-Akidi, Olaudi, Ileje ajaka and Ileje were obtained from dealers in Enugu and Kogi States, Nigeria, respectively. A plot of land measuring 10x10 m was manually cleared in the University of Calabar Experimental Farm, Calabar. Five beds were made with a spacing of 2 m between beds. Three seeds were sown in a hole of 4 cm deep per variety (Center for New Crops and Plants Products, 2002). The 4 varieties were randomized on each bed with 8 replications per variety using Randomized Complete Block Design (RCBD). Spacing was 50x75 cm. After seedling emergence, each stand of individual variety was thinned down to 2 stands. Weeding was done 3 and 5 weeks after planting while staking was done 4 weeks after planting. Days to seedling emergence was noted while data on number of leaves, leaf area and vein length were collected 5 and 10 weeks after planting. Days to 50% flowering and days to 50% maturity were also recorded while number of flowers per plant; pod lengths, inter-node length per plant, number of seeds per pod, number of pods per plant, seed yield per plants and 100 seed weight were obtained at maturity.

Statistical analyses: Data obtained were subjected to correlation and path coefficient analysis using statistical software PASW 18. Path coefficient was taken as the standardized coefficient of regression (direct effect) while the indirect effect was computed by multiplying the path coefficient of individual traits with their corresponding correlation coefficients (Cramer and Wehner, 2000a). The residual effect was estimated while genotypic, phenotypic and environmental correlations were computed according the method of Singh and Chaudhury (1985).

RESULTS

Simple pearson correlation: Our result in Table 1 presents the Pearson correlation coefficients. It shows that there were significant positive correlations between days to seedling emergence and number of leaves at 10 weeks (0.684*), vein length at 5 weeks and days to 50% flowering (0.684*) and pod length per plant and seed yield per plant (0.93***). Conversely, there were also negative significant correlation between leaf area at 5 weeks and pod length (-0.651*) and seed yield per plant (-0.725*); days to 50% flowering and number of seed per plant (-0.918***). However, other morphological traits studied had high correlations but were not significant.

Phenotypic correlation: Phenotypic correlation results revealed that there were positive significant association between number of leaves at 5 weeks and inter-node length (0.665*); leaf area at 5 weeks and number of pods per plant (0.665*); number of flowers and pod length (0.905***); inter-node length and seed yield (0.6300*) while negative significant relationship existed between days to seedling emergence and number of seeds per pod (-0.8473**) (Table 2).

Genotypic correlation: Furthermore, the genotypic correlation of yield and yield-related traits showed that there were generally high significant associations among most of the characters studied. The result shows that days to seedling emergence significantly correlated positively with vein length at 10 weeks (0.896**), leaf area at 5 weeks (0.84**), leaf area at 10 weeks (0.62*) and negatively with inter- node length (-0.858**), days to 50% flowering (-0.835**) and number of seeds per pod (-0.919***). It was also observed that vein length at 10 weeks significantly correlated positively with number of pods per plant (0.801**); leaf area at 5 and 10 weeks and days to 50% maturity with number of pods per plant (0.633*, 0.764**, 0.688*), respectively. There were positive significant association between number of leaves at 10 weeks, number of flowers with number of seeds per pod (0.739**, 0.979***). Days to seedling emergence, vein length at 5 weeks correlated negatively with number of seeds per pod (-0.919***, -0.646*) (Table 3).

Table 1: Pearson correlation on yield and yield-related traits in landraces of cowpea (Vigna unguiculata L. Walp)
*p = 0.05, **p = 0.01, ***p = 0.001

Table 2: Phenotypic correlation of yield and yield-contributing traits in cowpea (Vigna unguiculata L. Walp) landraces
*p = 0.05, **p = 0.01, ***p = 0.001

Table 3: Genotypic correlation of yield and yield-contributing traits in cowpea (Vigna unguiculata L. Walp) landraces
*p = 0.05, **p = 0.01, ***p = 0.001

Environmental correlation: Result obtained on environmental correlation revealed that there were positive significant associations between vein length at 10 weeks and days to 50% maturity (0.63*) and seed yield per plant (0.63*) but negatively with 100 seed weight (-0.998***). Positive significant relationship existed between number of leaves and leaf area at 5 weeks (0.859**) and pod length (0.681*) while correlating negatively with number of pod per plant (-0.648*) and 100 seed weight (-0.984***). It was also observed that number of pod per plant correlated positively with seed yield per plant (0.899**). However, other morphological traits had high correlation coefficients (Table 4).

Path coefficients: Direct (path coefficients) and indirect effects of yield-contributing traits to the yield of cowpea are as presented on Table 5. It shows that number of pod per plant had the highest direct effects to cowpea yield (0.588). This was followed by number of flowers (0.454), number of seeds per pod (0.366), leaf area at 5 weeks (0.366) and pod length and 100 seed weight (0.316), respectively. Other morphological traits had negative direct effects on seed yield such as vein length at 10 weeks (-0.627), number of leaves at 5 weeks (-0.215), number of leaves at 10 weeks (-0.033), leaf area at 10 weeks -1.124, days to 50% flowering (-0.083) and days to 50% maturity (-0.066). Some traits exhibited high total genotypic correlation coefficients.

DISCUSSION

It is undoubtedly obvious that genetic dissection and mapping of a Quantitative Traits Loci (QTLs) of any crop to decipher the exact locus of the chromosome where a particular trait could be found for onward improvement is a herculean task and thus needs preliminary work such as relationship studies which will guide selection. According to Umar et al. (2010), relationships study among quantitative traits is important for assessing the feasibility of joint selection of two or more traits. Yield (seed yield) as a complex polygenic trait influenced by many genes and factors working in synergy (Ezeaku and Mohammed, 2006) is the focal point in cowpea breeding and improvement.

According to Akinyele and Osekita (2006), mutual association of traits is often expressed by the phenotypic, genotypic and environmental correlations. Phenotypic correlation is directly proportional to the genotypic and environmental correlations. Present result shows that there were positive significant phenotypic correlation between number of leaves at 5 weeks and inter-node length; leaf area at 5 weeks and number of pod per plant; inter-node length and seed yield and number of flowers per plant and pod length. The broader the leaves, the more leaf surface that will be exposed to photosynthetic activity and the more pod that will be produced. This might be due to the higher photosynthetic efficiency of the varieties (Fagwalawa, 2000; Akinyele and Osekita, 2006). This however, might mean more flowers which might affect the pod lengths and ultimately seed yield. Their facilitatory role contributes significantly to the final yield and thus should be considered during selection to improve yield in cowpea breeding. Conversely, the negative significant phenotypic correlation observed between days to seedling emergence and number of seeds per pod indicates that the time taken for cowpea variety to germinate and emerge into seedling could affect the number of seeds produced per pod. It might suggest that selection of cowpea genotypes should take into cognizance early germination capacity which could lead to higher seed production.

Table 4: Environmental correlation of yield and yield-contributing traits in cowpea (Vigna unguiculata L. Walp) landraces
*p= 0.05, **p= 0.01, ***p= 0.001

Table 5: Direct (bold) and indirect effects of yield-contributing traits in cowpea landraces (Vigna unguiculata L. Walp)

A positive genetic correlation between two desirable traits makes selection easy for improving both traits simultaneously while the reverse is the case for negative correlation. Results obtained show that the genotypic correlation coefficients were very high as compared to the phenotypic and environmental effects. This indicates greater contribution of genotypic factor in the growth and development of these trait associations. It also show that vein length at 10 weeks significantly correlated positively with number of pods per plant leaf area at 5 and 10 weeks and days to 50% maturity with number of pods per plant, respectively. There were also positive significant associations between numbers of leaves at 10 weeks, number of flowers with number of seeds per pod. This corroborates the report of Cramer and Wehner (2000a, b). High and significant genotypic correlation coefficients are an indication that selection of cowpea landraces for future breeding programmes should be fundamentally based on the superiority of the genotypes alongside with their phenotypic expression. These according to Akinyele and Osekita (2006) are very important in determining the yield of the crop. This implies that these traits should be given high priority during selection. Traits with negative genotypic correlation imply that a lot of breeding programmes are needed to develop such traits. The significant relationship between days to 50% flowering and days to 50% maturity is suggestive that there is a strong relationship between the stage of plant growth at which flowering is initiated and the time taken to complete the crop’s life cycle (Akinyele and Osekita, 2006).

The implication of significant positive relationship of environmental correlation is that environmental factors favour the performance of cowpea and thus should be selected for as a component of yield. Interestingly, our result revealed positive significant environmental correlations between number of leaves at 10 weeks and leaf area at 5 weeks; leaf area at 10 weeks and number of flowers per plant; number of leaves at 10 weeks and pod length; nein length at 10 weeks and seed yield; number of pod per plant and seed yield and number of seeds per pod and 100 seed weight. This means that environmental factors prevailing during the growing season of these cowpea genotypes favoured the production of longer vein, leaf production and broader leaf surface area which might have culminated to higher flower numbers, longer pods and most importantly the seed yield. However, other traits with negative but significant correlation coefficients imply that environmental factors could have exerted great impediments to the growth and development of the traits. This obviously will be detrimental to the crop productivity. Additionally, although some of these characters that exercise negative correlations with one another will be difficult to select for in characterization of desired traits, those with negative association but non-significant correlation will be disregarded in selection for crop or variety improvement (Henry and Krishna, 1990; Akinyele and Osekita, 2006).

Accordingly to Cramer and Wehner (2000a), a large path coefficient indicates that the change will result in a proportional or inversely proportional change in another correlated trait, whereas a weak coefficient indicates that the change will have little effect on the second trait. Using (Cramer and Wehner, 2000a) statistical test for the importance of path coefficient (strong = 0.7 to 1.0 or -0.7 to -1.0; weak = -0.69 to 0.69), our result fall below their mark. This notwithstanding, other authors in the field reported path coefficients lesser than Cramer and Wehner (2000a) hypothesis but asserting their strong effects on yield (Vange and Moses, 2009; Akinyele and Osekita, 2006). The trait-contributing the highest direct effect was number of pods per plant which also corroborates with the earlier reports of Khan et al. (2000), Singh and Yadava (2000) and Shrivastava et al. (2001) in soybean. The high positive direct effects of number of pod per plant, number of flowers, number of seeds per pod, pod length, days to seedling emergence, leaf area and 100 seed weight on seed yield suggests that with other variables held constant, an increase in the above-mentioned morphological traits might increase seed yield per plant. This was also the position of Akinyele and Osekita (2006) in their report on Abelmoschus esculentus. The positive direct effects of 100 seed weight on seed yield corroborates reports of Yadev et al. (2001) in wheat; Ashraf et al. (2002) in urdbean and Arshad et al. (2004) in chicken pea.

Furthermore, according to Singh and Chaudhury (1985), if the total genotypic correlation coefficient is positive with negative or negligible direct effect, the indirect effects might be the causal factor of correlation. Critically, the seed yield of cowpea landraces might not be attributed directly by the morphological traits investigated rather via their alternative pathways (indirect routes) (Table 5). This according to Salahuddin et al. (2010) should be considered simultaneously for during selection.

CONCLUSION

Succinctly, it therefore implies that number of pods per plant, number of leaves per plant, leaf area, number of flowers per plant, pod length and number of seeds per pod are good selection indices for a high yielding variety of cowpea, especially the landraces. This then can be exploited in hybridization programmes involving cowpea.

REFERENCES
Afiah, S.A.N. and E.M. Ghoneim, 2000. Correlation, stepwise and path coefficient analysis in Egyptian cotton under saline condition. Arab Univ. Agric. Sci., 8: 607-618.

Akinyele, B.O. and O.S. Osekita, 2006. Correlation and path coefficient analyses of seed yield attributes in okra (Abelmoschus esculentus (L.) Moench). Afr. J. Biotechnol., 5: 1330-1336.
Direct Link  |  

Arshad, M., A. Bakhsh and A. Ghafoor, 2004. Path coefficient analysis in chickpea (Cicer arietinum L.) under rainfed conditions. Pak. J. Bot., 36: 75-81.
Direct Link  |  

Arshad, M., A. Bakhsh, M. Zubair and A. Ghafoor, 2003. Genetic variability and correlation studies in chickpea (Cicer arietinum L.). Pak. J. Bot., 40: 637-647.

Ashraf, M., A. Ghafoor, N.A. Khan and M. Yousaf, 2002. Path coefficient in wheat under rainfed conditions. Pak. J. Agric. Res., 17: 1-6.
Direct Link  |  

Azeem, I.K. and S.F.M. Azhar, 2006. Estimates of heritability and pattern of association among different characters of Gossypium hirsutum (L.). Pak. J. Agric. Sci., 37: 1-2.

Center for New Crops and Plants Products, 2002. Cajanus cajan (L.) Millsp. Purdue University, USA.

Chandra, A. and D. Pental., 2003. Regeneration and genetic transformation of grain legumes: An overview. Curr. Sci., 84: 381-387.
Direct Link  |  

Chaudhury, D., S. Madanpotra, R. Jaiwal, R. Saini, P.A. Kumar and P.K. Jaiwal, 2007. Agrobacterium tumefaciens-mediated high frequency genetic transformation of an Indian cowpea (Vigna unguiculata L. Walp.) cultivar and transmission of transgenes into progeny. Plant Sci., 172: 692-700.
CrossRef  |  

Cramer, C.S. and T.C. Wehner, 2000. Path analysis of the correlation between fruit number and plant traits of cucumber populations. HortScience, 35: 708-711.
Direct Link  |  

Cramer, C.S. and T.C. Wehner, 2000. Fruit yield and yield component correlations of four picking cucumber populations. Cucurbit Genet. Coop. Rep., 23: 12-15.

Ezeaku, I.E. and S.G. Mohammed, 2006. Character association and path analysis in grain sorghum. Afr. J. Biotech., 5: 1337-1340.
Direct Link  |  

Fagwalawa, L.D., 2000. Agro-physiological characterization of some early, medium and late maturing varieties of cowpea under sole and intercropping systems. Ph.D. Thesis, Department of Biological Sciences, Bayero University, Kano.

Ghafoor, A., F.N. Gulbaaz, M. Afzal and M. Arshad, 2003. Inter-relationship between SDS-Page markers and agronomic characters in chickpea (Cicer arietinum L.). Pak. J. Bot., 35: 613-624.

Henry, A. and G.V. Krishna, 1990. Correlation and path coefficient analysis in pigeon pea. Madras Agric. J., 77: 443-446.

Ikea, J., I. Ingelbrecht, A. Uwaifo and G. Thottappilly, 2003. Stable gene transformation in cowpea (Vigna aconitifolia L. walp) using particle gun method. Afr. J. Biotechnol., 2: 211-218.

Iqbal, S., T. Mahmood, M. Tahira, M. Ali, M. Anwar and M. Sarwar, 2003. Path analysis in mash (Vigna mungo L.). Pak. J. Bot., 22: 160-167.

Ivo, N.L., C.P. Nascimento, L.S. Vieira, F.A. Campos and F.J. Aragao, 2008. Biolistic-mediated genetic transformation of cowpea (Vigna unguiculata) and stable Mendelian inheritance of transgenes. Plant Cell Reports, 27: 1475-1483.
PubMed  |  Direct Link  |  

Khan, A., M. Hatam and A. Khan, 2000. Heritability and interrelationship among yield determining components of soybean varieties. Pak. J. Agric. Res., 116: 5-8.

Obembe, O.O., 2009. Exciting times for cowpea genetic transformation research. Aust. J. Basic Applied Sci., 3: 1083-1086.
Direct Link  |  

Pasquet, R., 2001. Vigna savi. In: Flora Zambesiaca: Phaseoleae, In: Mackinder, B., R. Pasquet, R. Polhill and B. Verdcourt (Eds.). Vol. 3 Part 5, Royal Botanic Gardens, Kew, UK., pp: 121-156.

Popelka, J.C., N. Terryn and T.H.V. Higgins, 2004. Gene technology for grain legumes: Can it contribute to the food challenge in developing countries?. Plant Sci., 167: 195-206.

Popelka, J.C., S. Gollasch, A. Moore, L. Molvig and T.J.V. Higgins, 2006. Genetic transformation of cowpea (Vigna unguiculata L.) and stable transmission of the transgenes to progeny. Plant Cell Rep., 25: 304-312.
Direct Link  |  

Sahoo, L., T. Sushma-Sugla, N.D. Singh and P.K. Jaiwal, 2000. In vitro plant regeneration and recovery of cowpea (Vigna unguiculata) transformants via Agrobacterium-mediated transformation. Plant Cell Biotechnol. Mol. Biol., 1: 47-54.

Salahuddin, S., S. Abro, M.M. Kandhro, L. Salahuddin and S. Laghari, 2010. Correlation and path coefficient analysis of yield components of upland cotton (Gossypium hirsutum L.) sympodial. World Applied Sci. J., 8: 71-75.

Shrivastava, M.K., R.S. Shukla and P.K. Jain, 2001. Path coefficient analysis in diverse genotype of soybean (Glycine max L.). Adv. Plant Sci., 4: 47-51.

Singh, J. and H.S. Yadava, 2000. Factors determining seed yield in early generation of soybean. Crop Res. Hisar, 20: 239-243.

Singh, R.K. and B.D. Chaudhury, 1985. Biometrical Methods in Quantitative Analysis. Kalyani Publishers, New Dehli, India pp: 318.

Solleti, S.K., S. Bakshi and L. Sahoo, 2008. Additional virulence genes in conjunction with efficient selection scheme, and compatible culture regime enhance recovery of stable transgenic plants in cowpea via Agrobacterium tumefaciens-mediated transformation. J. Biotechnol., 135: 97-104.
PubMed  |  

Solleti, S.K., S. Bakshi, J. Purkayastha, S.K. Panda and L. Sahoo, 2008. Transgenic cowpea (Vigna unguiculata) seeds expressing a bean α-amylase inhibitor 1 confer resistance to storage pests, bruchid beetles. Plant Cell Rep., 27: 1841-1850.

Somers, D.A., D.A. Samac and P.M. Olhoft, 2003. Recent advances in legume transformation. Plant Physiol., 131: 892-899.
Direct Link  |  

Udensi, O., E.A. Edu, U.J. Umana and E.V. Ikpeme, 2011. Estimation of genetic variability in locally grown pulses (Cajans cajan (L.) Millsp and Vigna unguiculata (L.) Walp): A panacea for sourcing superior genotypes. Pak. J. Biol. Sci., 14: 404-407.
CrossRef  |  Direct Link  |  

Udensi, O., E.J. Umana, E.A. Edu and E.V. Ikpeme, 2011. Screening locally grown pulses for proximate, anti-nutritive and mineral compositions: Indices for conservation and improvement. Int. J. Agric. Res., 6: 504-510.
CrossRef  |  Direct Link  |  

Udensi, O., E.V. Ikpeme, A.A. Markson, E.A.B. Edu, U.J. Umana and I.S. Urua, 2010. Selection of soybean genotypes using morphological markers. Int. J. Curr. Res., 7: 5-8.
Direct Link  |  

Umar, M.L., M.G. Sanusi and F.D. Lawan, 2010. Relationships between some quantitative characters in selected cowpea germplasm (Vigna unguiculata [L] Walp). Notulae Sci. Biol., 2: 125-128.

Vange, T. and O.E. Moses, 2009. Studies on genetic characteristics of pigeon pea germplasm at Otobi, Benue State of Nigeria. World J. Agric. Sci., 583: 714-719.

Yadev, G.C., PK. Singh, BB. Singh and R. Verma, 2001. Genetic variability and path coefficients in Urdbean. Indian J. Pulses Res., 14: 143-144.

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