Background

Cowpea is one of the important crops in the diet of millions of relatively poor people in less developed countries of the tropics. Families in the tropics variously derived food, animal feed and cash income from the production of the crop. Yield increase in crops is a major objective of breeders; hence selecting for best genotypes in an environment where water stress is the most important factor limiting crop production. Cowpea suffer drought stress as a result of erratic rainfall due to climate change resulting in yield loss of up to 35-69% (Shouse et al., 1980; Fatokun et al., 2012). In general new cultivars are traditionally produced by plant breeders selecting directly for yield or yield components in specific environment. For obvious reason this could not be for projected climate change conditions. Thus, the only possible approach could be selection for specific agronomic, morphological and physiological traits in a specific environment. Analysis of target environment, role of potential trait in drought and heat stress tolerance and their genetic variability and heritability furnish the basis for the breeding strategy (Dencic et al, 1997). Genotypic differences in the ability of cowpea to survive imposed drought have been reported (Watanabe et al., 1997; Ahmed et al., 2010). The associations between phenological and morph physiological traits and adaptation to abiotic stress have been studied with the aim of define breeding goals (Arnau, 1995; Acevedo, 1991). Common mitigation through irrigation is ineffective and expensive. This necessitates the development of drought tolerance genotypes. Evaluating cowpea for drought tolerance using genetic parameters is still very few.

Therefore, this study was conducted to evaluate the performance of individual cowpea genotype and to understand the effects of various genetic parameters on the quantitative traits under drought stress.

1 Results

The analysis of variance showed significant difference for all the traits studied under non water stressed (WW) and water stressed (WS) conditions (Table 1; Table 2).

In Table (3~8) statistical analysis revealed a significant reduction of most of the traits under water stress. Significant reductions was observed in plant height ranged between 12.62%-62.18%; terminal leaflet area between 15.87 - 51.24%; number of leaves per plant between 13.46% - 89.10%; number of days to 50% flowering between -5.12%to -24%; number of days to 50% ripe pod between -2.79% to -13.73%; plant vigour between -112.90%to -436.63%; number of pods per plant between -211.96% to 64.83%; number of seed per pod between 3.56%to 51.43%; 100-seed weight between -1.29% to 50%; total seed weight between -20.83% to 82.21%; stomata density between -1.94 to 45.71%; relative water content between 6.39% to 38.56%; number of branches per plant between -25.84 to 35.44%; pod length between -11.74% to 19.37%; root length between 10.8 – 42.9%; root biomass between -23.3 – 42.9%; shoot biomass between 5.9 – 61.2% and plant height at maturity between 9.9 – 53.2%.

Danilla, IT93K-432-1, IT97K-499_35, IT89KD-288 and IT98K-491-4 relatively showed better yield under both environments (Table 5).

The water stress effect showed small effect on relative water content, pod length, 100-seed weight, number of days to first flowering and number of days to first ripe pod.

As expected both phenotypic and genotypic variances were larger in size under water-stressed than well-watered environment, for number of days to 50% flowering, number of days to 50% ripe pod, plant vigour, number of pods per plant, number of seeds per pod and stomata density (Table 9).

Generally the phenotypic and genotypic coefficient of variation were larger under water-stressed than well-watered environment.

Under water-stressed, phenotypic coefficient of variation ranged between 12.34% for relative water content and 84.18% for number of pods per plant, while it ranged between 3.84% for relative water content and 84.34% for number of leaves per plant under well-watered environment. With respect to genotypic coefficient of variation, under water-stressed, it ranged between 7.54% for number of branches per plant and 84.65% for number of pods per plant, while under well-watered, it ranged between 0.00% for plant vigour and 60.69% for number of leaves per plant.

Broad sense heritability estimates (h2) indicated high values almost for all traits, it ranged between 12.43% for number of branches per plant and 99.0% for number of days to 50% flowering under water-stressed, while under well-watered, heritability ranged between 36.20% for relative water content and 98.0% for number of days to 50% ripe pod.

2 Discussion

There were significant effects of environments (water regime) and their interactions on the morphological and agronomical characteristics. The significant differences observed between the two environments resulted in varying degree of reduction across the parental genotypes studies for all characters. This indicated the presence of genetic variability among the parental genotypes used, thus, suggesting the good scope for selection of suitable basic material for breeders for further improvement. This results also showed that under well-watered condition, cowpea genotypes significantly gave better seed yields than under water-stressed conditions. Seed yield have been reported to be the function of the number of pods per plant, number of grains per pod and the extent to which grains are filled and the reduction in seed yield under water stress was associated with dramatic decrease in all these yield components (Ahmed et al., 2010). Ludlow and Mushow, 1990 and Gwathmey et al. 1992 also attributed the reduction in seed yield under water stress to the reduction in number of pods per plant, number of seeds per pod and seed weight. The water stress effect showed small effect on relative water content, pod length, 100-seed weight, number of days to first flowering and number of days to first ripe pod, this was in agreement with Silva, 1978, who reported that seeds/pod and 100-seed weights were not significantly affected by either the water or the nitrogen fertilizer treatments. Babalola (1980) and Shouse et al. (1980) observed similar effects during different phases of the crop’s phenological cycle. Labanauskas et al. (1981) reported that water deficiency during flowering and pod filling reduced productivity by 44% and 29%, respectively, but were not significantly affected by water stressed during vegetative period.

Estimates of genetic components are basic information needed for the breeders to improve the crops by adopting appropriate method of selection based on variability that exist in the material, hence partition the total variability into heritable and non-heritable components viz., phenotypic and genotypic variances and phenotypic and genotypic coefficients of variation and broad sense heritability. In the present study, the sizes of phenotypic and genotypic variance vary across the characters and the environments. Generally, phenotypic variance was higher than the genotypic variance across the characters and the environments. As expected both phenotypic and genotypic variances were larger in size under water-stressed than well-watered environment, for number of days to 50% flowering, number of days to 50% ripe pod, plant vigour, number of pods per plant, number of seeds per pod and stomata density. This may be due to the effects of environment. The phenotypic coefficient of variation was higher than genotypic coefficient of variation which was also demonstrated by (Assefa et al 1999), but the values were not significantly different in some cases under both environments. However, generally the phenotypic and genotypic coefficient of variation were larger under water-stressed than well-watered environment, indicating large environment effects in estimating these traits under water stressed environments. Furthermore, both phenotypic and genotypic coefficients of variation were higher for number of leaves per plant, number of pods per plant and total seed weight. Selvi et al. (1994) revealed moderate genotypic and phenotypic coefficient of variation for plant height; Apte et al. (1987) reported moderate genotypic coefficient of variation (17.39%) and high phenotypic coefficient of variation (79.18%) for the number of branches per plant while Rangaiah and Nehru (1998) reported high genotypic and phenotypic coefficient of variations. Apter et al. (1987) reported low genotypic and phenotypic coefficient of variations for days to maturity; Sarvamangala (2004) reported moderate to high for both based on 50 genotypes for number of pods per plant; Mathur (1995) however reported very extremely high genotypic and phenotypic coefficient of variations (103.93%) values. Selvam et al. (2000) reported moderate genotypic and phenotypic coefficient of variations for number of seeds per plant; Mathur (1995) in a variability study, among F2 population recorded high genotypic and phenotypic coefficient of variations for total seed weight

Broad sense heritability estimates (h²) indicated high values almost for all traits. These reports suggest that, most of the quantitative traits observed are under genetic control with least effects of genotype×environment interactions. It also suggests effective selection for breeding programs. Falconer (1989) described heritability as a proportion of a character only for the population and of the environmental circumstance to which the individual are subjected. Hence its values depend on the magnitude of all the components of variance and a change in any of this will affect it. (Patil and Patil, 1986) reported moderate heritability for plant height; Apte et al., 1987 and Rangaiah and Nehru 1998 indicated low heritability (5.61%); Madhusudhan (1994) reported high heritable values of 96.21% in F1 materials, while Balraju (1997) reported low heritability (14.2%) for number of branches per plant; Sarvamangala (2004) revealed high heritability for number of days to 50% flowering; report based on F1 generation indicated high heritability for number of days to 50% ripe pod (Marangappanavar, 1984); Mathur (1995) reported very high heritability (98.0%) for number of pods per plant, he also found high heritability for pod length; Heritability in number of seed per pods ranged from 31.3% (Selvam et al., 2000) to 98.8% (Tyagi et al., 2000) based on studies of 24 and 50 cowpea genotypes; Heritability of hundred seed weight ranged from 14.47 % (Rangaiah and Nehru, 1999) to 99.2% (Selvi et al., 1994); Some reports indicated higher estimates of heritability (Biradar et al., 1993; and Tyagi et al., 2000 ) for total seed weight in cowpea.

Each cowpea genotype used expressed unique reaction under terminal water stressed. This, then revealed that, there is large genetic variance to indicate selection for improvement in the cowpea genotypes studied. Thus, considerable progress in cowpea breeding could be achieved by exploiting these traits. Furthermore, in term of seed yield, Danilla, IT92KD-357-3, IT93K-432-1, IT97K-499-35 and IT99K-513-21 appeared promising to be used in breeding programme for drought tolerance in cowpea.

3 Materials and Methods

Ten cowpea genotypes were used for this study. The cowpea genotypes planted were; Danilla, IT93K-452, IT97K-499-35, IT89KD-288, IT98K-205-8, TVU7778, TVU12349, IT92KD-357-2, IT98K-491-4, IT99K-573-2-1. They are cowpea genotypes collections maintained by genetic resource unit, International Institute of Tropical Agriculture, Ibadan Nigeria. The ten parental genotypes were evaluated in a randomized complete block design with three replications under two water regime; well-watered and water-stressed environments. This experiment was conducted for two years during the dry season between November and February 2011/2012 and 2012/2013 at Teaching and Research Farm, University of Ibadan, Nigeria. Each row was 3m long spaced at 75cm apart and a within-row spacing of 20cm. Four- row plot was used per genotype for each replicate. All the plants were watered regularly for two weeks until the emergence of the first trifoliate leaves after which watering was suspended for the water stressed plots. Non- stressed plots were continuously irrigated whenever water is required, while in the other plot it was completely held throughout the growing season. The physical properties of the soils for the experiments showed the content of sand was 81.0%, silt was 11.4%, clay as 7.6%, while the chemical properties results of the soils were: Ca; 11.60 Cmol/kg, Mg: 5.81 Cmol/kg, Na; 1.32 mg/kg, K; 1.08 mg/kg, Mn; 233.00 mg/kg, Fe; 171.00 mg/kg, Cu; 0.40 mg/kg, Zn; 16.70 mg/kg, P; 41.23 mg/kg and PH; 6.4. The soil moisture contents were estimated on regular interval i.e. 10 days throughout the growing season. Crop management was uniform following recommended production package. Morphological and agronomic characteristics like plant height at six weeks, plant leaflet area, number of leaves per plant at six weeks, plant vigor at six weeks, number of branches per plant at six weeks, number of days to 50% flowering, number of days to 50% ripe pod, number of pods per plant, number of seeds per pod, 100-seed weight, total seed weight, root length, root biomass, shoot biomass and plant height at maturity were randomly sampled for and estimated for each environment separately at appropriate period for all the cowpea genotypes.

Statistical procedures

Standard statistical procedures were used to obtain means and variances for each environment separately (Steel et al., 1997). The data were analyzed considering genotypes as random effects and environments as fixed effects. The broad sense heritability (h²) was estimated as the ratio of genotypic variance to the phenotypic variance, using the formula; h2 = ∂g2/ ∂g2+∂ge + ∂e, where, ∂g2= genotypic variance, ∂2gs = the genotype × environmental variance and ∂e = the pool error variance. The genotypic and phenotypic coefficient of variation are estimated according to Kumar et al., (1985), GCV = (∂2g)1/2/z) × 100 and PCV = (∂2p)1/2/z) × 100, GCV and PCV are the genotypic and phenotypic coefficient of variation respectively and ∂2g is the genotypic variance, ∂2p is the phenotypic variance and z is the general mean of a trait.

References

Acevedo E., 1991, Improvement of winter cereal crops in Mediterranean environments, Use of yield, morphological and physiological traits, In E.Acevedo, A.P. Conesa, P. Monneveux and J.P. Srivastava, eds., Physiology-Breeding of Winter Cereals for Stressed Mediterranean Environments, Inra,Paris, pp.273-305

Ahmed F.E., and Suliman A.S.H., 2010. Effect of water stress applied at different stages of growth on seed yield and water-use efficiency of Cowpea. Agric. Biol. J. N. Am., 2010, 1(4): 534-540

Apte U.B., Chavan S.A., and Jadhav B.B., 1987, Genetic variability and heritability in cowpea. Indian Journal of Agricultural Sciences, 57: 596 – 598

Arnau G., and Monneveux P., 1995, Physiology and genetics of terminal water stress tolerance in barley. J. Genet. & Breed. 49: 327-332

Assefa K., Ketema S., Tefera H., Nguyen H.T., Blum A., Ayele M., Bai G., Sumane B. and Kefyalem T., 1999, Diversity among germplasm Lines of Ethiopian cereal tef (Eragnosis tef (Zucc) Trotter) Euphytica; 106:87-97

Babalola O., 1980, Water relations of three cowpea cultivars (Vigna unguiculata (L.) Plant soil, 56(1) 59-69

Balraju., 1997, Genetics of yields and its attributes and related physiological parameters incowpea (Vigna unguiculata [L.] Walp.). M.Sc. (Agri.) Thesis, University of Agricultural Sciences, Bangalore

Biradar B.D., Goud J.V., and Patil S.S., 1993, Components of variances heritability and genetic gain in cowpea (Vigna unguiculata (L.) Walp.). Annals of Agricultural Research, 14 : 434-437

Dencic S., Kerecki B., Skuric D., Kovacfv L., Ivanovic M. 1997. The possibilities of genetic and breeding in increasing of tolerance to drought stress. Proc. Inter. Swamp, drought and plant production. Lepenski Vir, Yogouslavia Vol 11. Pg 18-23

Falconer D.S., 1989. Introduction to quantitative genetics. 3rd ed., Longman, London

Fatokun C.A., Boukar O., and Muranaka S., 2012. Evaluation of cowpea (Vigna unguiculata (L.) Walp.) Germplasm lines for tolerance to drought. Plant Genetic Resources / Volume 10 Issue 03, pp.171-176

https://doi.org/10.1017/S1479262112000214

Gwathmey C.O., Hall A.E., and Madore M.A., 1992, Adaptive attributes of cowpea genotypes with delayed monocarpic leaf senescence traits, Crop Sci 32: 765-772

https://doi.org/10.2135/cropsci1992.0011183X003200030039x

Guimaraes CM, Araujo JPP and WattEE, 1983, Irrigado de caupi em diferentes estagiios, de desemvolvimento e densidades de plantic, Research in progress 42 Goidiana EMBRAPA CNPAF 3p

IITA., 2000, Challenges and opportunities for enhancing sustainable cowpea production Ed; Fatokun et al. Jackai, L.E.N., Singh, S.R., Rehaja, A.K and Windvjk, F. (1985). Recent trends in the control of cowpea pests in Africa pp.235-243. In;SR Singh and KO Rachie (eds), Cowpea Research Production and Utilization Wiley New York

Kumar S., and Singh., Onkar., 1995, Inheritance of seed size in chickpea. Journal of Genetics and Breeding, 49(2): pp.99-103

Labanauscas C.K. Shouse P. and Stolzy L.H., 1981. Effect of water stress at various growth stages on seed yield and nutrients concentrations of field grown cowpea. Soil Sci. 131(4):249-265

https://doi.org/10.1097/00010694-198104000-00009

Ludlow M.M. and Muchow R.C., 1990, A critical evaluation of traits for improving crop yields in water limited environments, Advances in Agron43: 107-153

https://doi.org/10.1016/S0065-2113(08)60477-0

Madhusudan K., 1994, Investigations on combining ability and gene action for seed yieldand its attributes in cowpea (Vigna unguiculata [L.] Walp.). Ph.D. Thesis, University of Agricultural Sciences, Bangalore

Marangappanavar L.R., 1984, Genetic diversity gene action and character associationin cowpea (Vigna unguiculata (L.) Walp.). Ph.D. Thesis, University of Agricultural sciences, Bangalore

Mathur R., 1995, Genetic variability and correlation studies in segregating generations of cowpea, Madras Agricultural Journal, 82: 150–152

Morgan J.M., 1983. Osmoregulation as a selection criterion for drought tolerance in wheat. Aust.J.Agric. Res., 34; 607-614

https://doi.org/10.1071/AR9830607

Nachit M., and Jarrah M., 1986. Association of some morphological characters to grain yield in durum wheat under Mediterranean dry land conditions. Rachis, 5(2); 33-34

PatilL R.B.,and Patil, R.S., 1986, Genetic studies in cowpea. Journal of Maharashtra Agricultural Universities, 11: 51 – 53

Rangaiah S., and Nehru S.D., 1998, Genetic variability correlation and path analysis in cowpea. Karnataka Journal of Agricultural sciences, 11: 927 – 932

Sarvamangala S., Cholin, 2004, Genetic studies on different plant types of cowpea [Vigna unguiculata (L.) Walp.]. M. Sc. (Agri.) Thesis, University of Agricultural Sciences, Dharwad

Selvam Y.A., Manivannan N., Murugan S., Thangavelu P., and Ganeshan J., 2000, Variability studies in cowpea (Vigna unguiculata (L.) Walp.). Legume Research, 23: 279-280

Selvi B., Rangaswamy P., Nadarajan N., ramalingam J. and Vannirajan C., 1994, Genetic variability in cowpea. Annals of Agricultural Research, 15: 248- 249

Shouse P., Dasberg S., Jury W.A., Stolzy L.H, 1980. Water Deficit Effects on Water Potential, Yield, and Water Use of Cowpeas, Agronomy Journal. Vol. 73 No. 2, pp.333-336

https://doi.org/10.2134/agronj1981.00021962007300020021x

Silva M.A., da, 1978, Elito da Lamina de Agua e da Adubacao Nitrogenada sobre a Producao de Feijao-de-corda (Vigna sinensis L. Savi), utilizandoo sistema de irrigacao por Aspersao em Linha. Master’s Thesis, Vicosa, Universidade Federal do Vicosa, pp.53

Steel R.G.D., Torrie J.H., and Discky D.A., 1997, Principles and procedures of statistics: A Biometrical approach, 3rd ed. McGraw Hill Book Co., New York

TYAGI P.C., KUMAR N., AND AGARWAL M.C., 2000, Genetic variability and association ofcomponent characters for seed yield in cowpea (Vigna unguiculata (L.) Walp.) Legume Research, 23: 92-96

Watanabe I., Hakoyama S., Terao T., and Singh B.B., 1997, Evaluation methods for drought tolerance of cowpea pages 141-146 in Advances in cowpea research, edited by B.B. Singh, D.R. Mohan Raj., K.E. Dachiell and L.E.N. Jackai, Co publication of International Institute of Tropical Agriculture (IITA) and Japan International Research Center for Agricultural research Science (JIRCRS) IITA< Ibadan, Nigeria