Printer Friendly

Implications of genetic heterogeneity among cultivated genotypes for global food security in climate change era.

Climate change is threatening the biodiversity

Anthropogenic environmental modifications, such as habitat loss and fragmentation, have already led to changes in the amounts and distribution of genetic diversity. In the UK, such changes are already apparent as species-level responses, including phenological changes and distributional shifts (Parmesan, 2006; Thackeray et al, 2010; Pateman, 2013; Sparks 2013). Climate driven alterations in population size (Leimu et al, 2006; Honnay and Jacquemyn, 2007), geographical connectivity (Aguilar et al., 2008), distribution (Anderson et al., 2008) and selection pressure (Phillimore et al, 2010 and 2012) have been considered as primary changes that influences the genetic diversity and gene flow. The loss of genetic diversity results in narrow mating, allowing the expression of deleterious genetic variants and leads to offspring with lower fitness (Reed and Frankham, 2003; Leimu et al., 2006; Angeloni et al., 2011). Further reduction in population size resulting from the loss of fitness may exacerbate the effects of inbreeding, and this positive feedback of reduced population size on fitness loss is known as an extinction vortex (Frankham et al., 2010 and 2011). The fitness costs associated with inbreeding depression also limit responses to stressful environments (Ketola and Kotiaho, 2009; Fox and Reed, 2011; Bijlsma and Loeschcke, 2012; Dierks et al, 2012).

Food security: The burning issue

The reduced precipitation, together with high evapotranspiration is expected to subject natural and agricultural vegetation at a great risk of severe and prolonged water stress with each passing year (Easterling et al, 2007; Iqbal et al, 2004 and 2013). In semi-arid areas, climate change may extend the dry season of no or very low flows, which particularly affects water users unable to rely on reservoirs or deep groundwater wells (Giertz et al, 2006; Kundzewicz et al, 2010). Agricultural irrigation demand in arid and semi-arid egions of Asia is estimated to increase by at least 10% for an increase in temperature of 1[degrees]C (Fischer et al. 2002; Liu 2002). According to a report by USD A Agriculture Weather Facility (2005), oilseed production in 2005 was down 2% from 2004 due to drier than normal growing season (Rauf and Sadaqat, 2007). In Spain in particular, the sunflower crop suffered substantially from drought, decreasing production by 41%. Similarly in the Americas, drought was a key factor responsible for yield losses of up to 20% (Reddy et al, 2004). In Pakistan, sunflower acreage declined by 25% from 1998-99 to 2002-03, but the total sunflower production declined by 33% during the same period as a result of severe drought (GOP, 2003).Considering the present scenario, there is dire need of cultivars which can cope with aberrant climate, particularly reference to drought and moisture stress, which in turn has necessitated the development of more productive hybrids of diverse genetic background (Dhillon et al., 2010; Shamshad et al., 2014). The investigation considered sunflower, potential oilseed crop worldwide (Machikowa and Saetang, 2008; Ghaffari et al, 2012; Shafi et al., 2013; Kumar et al., 2014; Shamshad et al., 2014; Rao et al., 2015), to tackle the food security issue rose by policy makers to combat climate change. The experiment was undertaken to assess the inherent diversity of the primary gene pool of sunflower (Helianthus annuus L.) following morphophysiological criteria and thereafter validation of these genotypes in the current trend of climate change.

MATERIALS AND METHODS

Variable stress simulation model and Breeding Material

Along with future temperature shifts, current climate models also predict an increase in the frequency of extreme precipitation fluctuations, including flooding and drought throughout the globe (Allan and Soden 2008, Min et al., 2011). Understanding and predicting the consequences of climate change for natural populations is of critical importance. Therefore it was attempted to test the parental stock in stress simulation model by withholding the water at critical crop growth stage viz [W.sub.1]: (control); [W.sub.2]: water stress before button stage and after soft dough stage; W3: stress at 50 percent flowering stage and soft dough stage thereafter and after hard dough stage; W4: stress at anthesis completion stage and after soft dough stage. Apart from secondary yield contributor traits, participation of physiological parameters like canopy temperature (CT) ([degrees]C), leaf area index (LAI), photo synthetic capacity (PS) and leaf water potential (LWP) (mpa) were also assessed. 41 Cytoplasmic and restorer lines were taken for study having sufficient geographical and parental diversity (Table 01).

Statistical background of study

Mahalanobis D2 statistics between two populations estimated on the basis of the 'p' characters is:

[Dp.sup.2] = [p.summation over 1] [p.summation over 1] [W.sup.ij] (X - [X.sub.i2]) ([X.sub.j1] - [X.sub.j2])

Where,

[W.sub.ij] = Variance - covariance matrix [W.sup.ij] is the reciprocal of ([W.sub.ij]), (ij = 1,2 ... p)

[X.sub.i1] = Sample mean for ith character for first sample [X.sub.i2] = Sample mean for ith character for 2nd sample. In the present study characters (P=1-10) were used to perform the above analysis. For conducting the D2 analysis, the computer programme, WINDOSTAT 8.0 cluster analysis was used. The distance from D2 values was calculated for each pair of parents (Malanobis, 1934). The [D.sub.2] values of all the combinations were arranged in descending order. Treating [D.sub.2] as generalized statistical distance, all the genotypes were clustered into six groups. The intra and inter-cluster distances and contribution of individual characters towards divergence were computed (Mohan and Seetharam, 2005).

RESULTS AND DISCUSSION

Morphometric Variability and water stress

In the study, pooled analysis of variance (Table 2a; 2b) revealed that environment differed significantly in respect of all the characters and showed significant interaction with the genotypes. Days to 50 percent flowering were found to be higher in control i.e. [W.sub.1] followed by [W.sub.4], [W.sub.2] and W3 in continuation with earlier reporting of Ghani et al. (2000). In [W.sub.1] the genotype 48-B was the earliest (57 days) and P-111-R was the latest (81 days) to flower (Table 3). Whereas, in [W.sub.2] genotypes P-61-R, P-75-R, P-94-R, P-119-R, 11-B, 50-B and RHA-297 recorded earliest flowering (60 days) and P-112-R registered the (76 days) latest. In W3 48-B recorded to be earliest (56 days) while P-111-R and P-112-R took maximum days (74 days) to flowering. In [W.sub.4], 48-B was observed as earliest (57 days) and P-111-R latest (79 days).Overall, the genotype P-111-R followed by P-112-R took maximum number days to 50 percent flowering and 48-B minimum. Seed yield was maximum in control (Ramchander et al., 2014) and ranged from 10.3g to 54.7g in [W.sub.1], 7.2 to 52.2 in W2, 9.7 to 49.8 in [W.sub.3] and 10.0 to 51.8 in W4.The genotypes P-94-R, P-115-R and P-119-R were found to be severely affected by the treatments, however, 95-C-1-R and P-87-R resisted to water stress and showed minimum reduction in seed yield. Water Stress during the flowering stage causes abortion of ovaries and embryo, sterility of pollen and decrease in leaf area index .This reduces the fertile achene per head and 100 achene weight (Reddy et al. 2004). The average 100-achene weight was significantly high in [W.sub.1] (7.1g) as compared to [W.sub.2] (5.5 g), W3 (5.7 g) and [W.sub.4] (6.1g) Genotype 7-1-B recorded the highest 100seed weight followed by P-75-R and the genotype 95-C-1-R exhibited minimum 100-achene weight followed by and RCR-8297 over the entire respective environment. For the same parameter genotypes P-107-R-Pp P-75-R, 10-B and 45-B were least effected in all environments indicating tolerance. However, the effect of water stress was highly significant in 95-C-1-R, NDLR-1, 7-1-B and RCR-8297. Reduction of head size, plant height, achene weight and achene yield were reported previously (Hossain et al. 2010; Vanaja et al. 2011).

Associations of Cytoplasmic restorer and maintainers

Species diversity has been shown to stimulate productivity, stability, ecosystem services, and resilience in natural (Cadotte et al., 2012; Gamfeldt et al., 2013; Zhang et al., 2012; Cabell and Oelofse, 2012) and in agricultural ecosystems (Kremen and Miles, 2012; Davis et al., 2012; Bonin and Tracy, 2012; Mij atovic et al., 2013). The genetic diversity in these resources allows crops and varieties to adapt to ever-changing conditions and to overcome the constraints caused by pests, diseases and abiotic stresses (Chandirakala et al., 2015). D2 statistics grouped the test genotypes into 6 clusters (Table 4 & fig. 1), on the basis of aggregate differences in characters taken, with variable number of entries in each cluster indicating the presence of genetic diversity in the material. Cluster I comprised of maximum number of genotypes (27 genotypes), followed by cluster II (5 genotypes), cluster III and V (3 genotypes in each), cluster IV (2 genotypes), and cluster VI (1 genotypes). Taklewold et al., (2000), Mohan and Seetharam (2005), Parameshwarappa et al., (2009) and Kumari and Singh (2015) also observed similar clustering pattern of genotypes among clusters, as some clusters were unique having only single genotype. The genotypes included in the same cluster are considered genetically similar in respect to the aggregate effect of the characters examined; the hybridization attempted between these is not expected to yield desirable recombinants (Bandila et al., 2011; Zala et al., 2014). Therefore, putative parents for crossing programme should belong to different clusters characterized by large intercluster distance. The further choice of genotype should be made considering the mean performance of genotype in respect of various characters.

Morphometric traits in divergence

Among the traits evaluated, leaf area index contributed the maximum (18.54%) towards the observed diversity (Fig. 2), followed by early vigour (18.35%), oil content (12.35%), 100 seed weight (10.59), photosynthetic capacity (9.58%), and plant height (9.29%), and leaf water potential (6.16%), achene yield per plant (4.50%), head diameter (4.19%) and canopy temperature (3.16%). Days to 50 per cent flowering and days to maturity contributed very little (1.58 and 0.96 % respectively) towards the divergence. However in previous studies, achene yield per plant (Sasikala, 2000; Loganathan, 2002; Loganathan et al., 2006 and Punitha et al., 2010) plant height, days to 50 percent flowering and days to maturity (Sreedhar et al., 2006; Parameshwarappa et al., 2009) contributed substantially towards genetic divergence.

Association distance of inbreds

Plant genetic resources serves as a source of novel alleles for ongoing plant breeding efforts in a variety of species (Acquaah, 2006; Mandel et al., 2011). Unlocking the full potential of crop germplasm collections, however, requires an understanding of the amount and distribution of genetic variation contained within them. To this end, we analyzed the association nature of inbreds with respect to their genetic closeness (Clustering). The intra cluster distances ranged from 0 (cluster VI) to 2.77 (cluster I) indicating that the single genotype in cluster VI whereas, genotypes in cluster I were more dissimilar in morphological features and performance than other clusters (Table 5a). The members of cluster IV and V exhibited maximum divergence (inter-cluster distance 7.16) followed by the members of cluster V and VI (intercluster distance 7.04), cluster IV and VI (intercluster distance 6.97), cluster II and VI (inter cluster distance 6.16), cluster III and VI (intercluster distance 6.13), cluster III and IV (intercluster distance 5.58) and cluster III and V (intercluster distance 5.29). The members of cluster I and III were least divergent (inter-cluster distance 3.01). The inter-cluster distances were larger than the intra-cluster distances indicating wider genetic diversity between genotypes of the clusters with respect to the traits considered. Therefore, combination with high heterotic response and superior combination may be obtained through hybridization between genotypes across the clusters (Subrahmanyam et al., 2003; Amorim et al., 2007). Gohil and Pandya (2006) have also pointed out in Salicornia brachiata Roxb (a nontraditional Oilseeds) that selection of parents for hybridization should be done from two clusters having wider inter-cluster distance to get maximum variability.

Phenotypic plasticity

Each cluster has its own uniqueness that separated it from other clusters (Table 5b). For example, Cluster I with the largest number of lines was characterized by the lowest mean value for early vigour, seed yield per plant (g), leaf water potential and leaf area index and highest mean value for oil content and leaf water potential. The lowest average for days to maturity and 100 seed weight and highest average for seed yield per plant and photosynthetic capacity among six clusters were characterized by cluster III. Cluster IV included the two genotypes viz. P111R and P112R, which was identical in performance to P107[RP.sub.1] of cluster 2009). Cluster mean analysis indicated the extent of genetic diversity among different clusters and that is of real value in plant breeding (Arshad et al., 2007; Camarano et al., 2010). The genotypes grouped into same cluster displayed the lowest degree of divergence from one another and in case crosses are made between genotypes belonging to the same cluster, no transgressive segregants are expected from such combinations (Tripathi et al., 2013). Therefore, hybridization programmes should always be formulated in such a way that the parents belonging to different clusters with maximum divergence could be utilized to get desirable transgressive segregants (Shekhawat et II and P107[RP.sub.1] of cluster I respectively. However it was distinct for high mean days to 50 percent flowering, plant height and leaf area index. Cluster V harbored three genotypes (P100R, 40B and 50B) with highest number of days to maturity and 100 seed weight. The lowest number of days to flowering, plant height and leaf water potential was also recorded in this cluster. Cluster VI had only one genotype (71B) characterized by highest mean value for early vigour, canopy temperature and head diameter and high mean value for most of the characters. Therefore rather than selecting lines from the cluster which have high inter cluster distance for hybridization, parents should be selected based on the extent of divergence in respect to a character of interest i.e. if breeders intension is to improve achene yield, he should go for selecting parents which are highly divergent with respect to this trait (Parameshwarappa et al., al., 2014). The genotypes with high values of any cluster can be used either for direct adoption or for hybridization, followed by selection.

Validation of heterogeneous populations under water stress

As most of the cultivated hybrids evolved under optimum conditions, breeding for drought tolerance is required. This indeed would depend on the presence of diverse germplasm so that potential sources of drought tolerance might be identified and subsequently used to assure high yield. However, high yield and drought tolerance are two different mechanisms that are often found to oppose each other. Traits, such as small plant size, reduced leaf area, and prolonged stomatal closure, limits the water losses, but also leads to reduced dry matter production and, therefore, reduced final yield. To this end, the heterogeneous population so obtained were subjected to differential levels of water stress to find out whether this heterogeneity is practically applicable to water stress ecology or not. Among observations recorded, optimum plant height and crop duration, higher leaf area index and water potential and lower canopy temperature were found to be critical selection criteria. The results were so surprising that of forty one inbred only eleven were found to be suitable to water stress. Genotypes P69R, P87R, P93R, P115R, NDLR2 (Cluster I), P107[RP.sub.1] (Cluster II), P121R (Cluster III), P111R (Cluster IV), 40B and 50B (Cluster V) and 71-B (Cluster VI) identified as stress tolerant genotypes (Table 6). Hence it is suggested crosses should be attempted among these cytoplasmic and restorers to when drought is expected to occur at respective growth stages. It is also concluded that merely presence of genetic variation is not going to serve in present scenario of challenging food security; researchers need to validate the utility of divergence for stress environments particularly water stress.

Agriculture and climate change are inextricably linked-crop yield, biodiversity and water use as well as soil health are directly affected by changing climate. Development of resilient crop varieties that tolerate temperature and precipitation stress will greatly rely upon crop genetic resource and available heterogeneity among them. Moreover this heterogeneity required subjection to periods of water shortage to evaluate their stress applicability. Our study concludes significance of genetic divergence towards climate change and methodology to validate divergence for water stress. This will be useful for implication of genetic resource towards climate resilient crop breeding.

REFERENCES

(1.) Acquaah, G. Principles of plant genetics and breeding. Blackwell, Oxford., 2006.

(2.) Aguilar, R., Quesada, M., Ashworth, L., Herrerias-Diego, Y. and Lobo, J. Genetic consequences of habitat fragmentation in plant populations: susceptible signals in plant traits and methodological approaches. Molecular Ecology., 2008; 17(24): 5177-5188.

(3.) Ahmad S. B M. and Abdella A. W. H. Genetic yield stability in some sunflower (Helianthus annuus L) hybrids under different environmental conditions in sudan. J. Plant Breeding and Crop Sci., 2009; 1(1): 16-21.

(4.) Allan, R. P. and Soden, B. J. Atmospheric Warming and the Amplification of Precipitation Extremes. Science., 2008; 321:1481-1484.

(5.) Amorim, E. P., Ramos, N. P., Ungaro, M. R. G., Kiihl, A. M. T. Divergencia genetica em genotipos de girassol. Ciencia e Agrotecnologia. Lavras, 2007; 31(6):1637-1644.

(6.) Anderson, S.J., Conrad, K.F., Gillman, M.P., Wiowod, I.P. and Freeland, J.R. Phenotypic changes and reduced genetic diversity have accompanied the rapid decline of the garden tiger moth (Arctia caja) in the U.K. Ecological Entomology.,2008; 33(5): 638-645.

(7.) Angeloni, F., Ouborg, N.J. and Leimu, R. Meta-analysis on the association of population size and life history with inbreeding depression in plants. Biological Conservation., 2011; 144(1): 35-43.

(8.) Arshad, M., Ilias, M. K. and Khan, M. A. Genetic divergence and path coefficient analysis for seed yield traits in sunflower (Helianthu annuus L) hybrids. Pak J Bot., 2007; 39(6):2009-2015.

(9.) Bandila, S., Ghanta, A., Natarajan, S. and Subramoniam, S. Determination of Genetic Variation in Indian Sesame (Sesamum indicum) Genotypes for Agro-Morphological Traits. J of Res in Agri Sci., 2011; 7(2):88-99.

(10.) Bijlsma, R. and Loeschcke, V. Genetic erosion impedes adaptive responses to stressful environments. Evolutionary Applications., 2012 5(2): 117-129.

(11.) Bonin, C.L. and Tracy, B.F. Diversity influences forage yield and stability in perennial prairie plant mixtures. Agric Ecosyst Environ., 2012; 162:1-7.

(12.) Cabell, J.F. and Oelofse, M. An indicator framework for assessing agroecosystem resilience. Ecol Soc., 2012; 17(1):18.

(13.) Cadotte, M.W., Dinnage, R. and Tilman, D. Phylogenetic diversity promotes ecosystem stability. Ecology, 2012; 93(8):223-S233.

(14.) Camarano, L.F., Chaves, L.J., Brasil, E.M. and Borges, E. Genotypic divergence among sunflower populations. Pesq. Agropec. Trop. Goiania, 2010; 40(1):36-44.

(15.) Davis, A.S., Hill, J.D., Chase, C.A., Johanns, A.M. and Liebman, M. Increasing cropping system diversity balances productivity, profitability and environmental health. PLoS ONE., 2012; 7(10):e47149.

(16.) Dhillon, S.K., Phool Chandra., Bajaj R.K. and Singh, P. 2010. Genetic evaluation and characterization of sunflower (Helianthus annuus L) as per DUS guidelines. Ind J Plant Genetic resources. 24(1):23-26.

(17.) Dierks, A., Baumann, B. and Fischer, K. Response to selection on cold tolerance is constrained by inbreeding. Evolution. 2012; 66(8): 2384-2398.

(18.) Easterling, W., Aggarwal, P.K., Batima, P., Brander, K.M., Erda, L., Howden, S.M., Kirilenko, A., Morton, J., Soussana, J.F., Schmidhuber, J., Tubiello, F.N. Food, fibre and forest products. Climate Change 2007: impacts, adaptation and vulnerability. In: Parry ML, Canziani OF, Palutikof JP (eds) Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, 2007; pp. 273-313.

(19.) Fischer, G., Shah, M., Van, V. H. 2002. Climate change and agricultural vulnerability. International Institute for Applied Systems Analysis, Vienna, Austria. Available online at: www. iiasa.ac.at/Research/LUC/JB-Report.pdf

(20.) Fox, C.W. and Reed, D.H. Inbreeding depression increases with environmental stress: an experimental study and meta-analysis. Evolution, 2011; 65(1): 246-258.

(21.) Frankham, R., Ballou, J. and Briscoe, D.A. Introduction to Conservation Genetics. Cambridge University Press: Cambridge., 2010.

(22.) Frankham, R., Ballou, J.D., Eldridge, M.D.B., Lacy, R.C., Ralls, K., Dudash, M.R. et al. 2011. Predicting the probability of outbreeding depression. Conservation Biology., 2011; 25(3): 465-475.

(23.) Gamfeldt, L., et al. 2013. Higher levels of multiple ecosystem services are found in forests with more tree species. Nat Commun., 2013; 4:1340.

(24.) Ghaffari, M., Toorchi, M., Valizadeh, M., and Shakiba, M. R. Morpho-physiological screening of sunflower inbred lines under drought stress condition. Turk J of Field Crops. 2012; 17(2):185-190.

(25.) Ghani, A., Husain, M. and Qureshi, M.S. Effect of different irrigation regimes on Growth and yield of Sunflower. Int J Agric Bio., 2000; 2 (4): 334-335.

(26.) Giertz, S., Diekkruger, B., Jaeger, A. and Schopp, M. An interdisciplinary scenario analysis to assess the water availability and water consumption in the Upper Oum catchment in Benin. Adv Geosci., 2006; 9:1-11

(27.) Gohil, R.H. and Pandya, J.B. Genetic diversity assessment in physic nut (Jatropha curcas L.). Intl J of PlProd, 2008; 2(4):321-326.

(28.) Government of Pakistan. Agriculture statistics of Pakistan. Ministry of Food, Agriculture and Livestock, Economic Wing, Islamabad, Pakistan. 2003.

(29.) Honnay, O. and Jacquemyn, H. Susceptibility of Common and Rare Plant Species to the Genetic Consequences of Habitat Fragmentation. Conserv Bio.2007. 21(3): 823-831.

(30.) Hossain, M.I., Khatun, A., Talukder, M.S.A., Dewan, M.M.R. and Uddin, M.S. 2010. Effect of drought on physiology and yield contributing characters of sunflower. Bangladesh J Agri Res. 35:113-124.

(31.) Iqbal, N. Influence of exogenous glycine betaine on drought tolerance of sunflower (Helianthus annuus L.). Ph. D. thesis, Deptt. Of Bot, Univ. of Agri., Faisalabad. Pakistan., 2004.

(32.) Iqbal, M., Ijaj, U., Smiullah., Iqbal, M., Mahmood, K., Najeebullah, M., Abdullah., Niaz S., and Sadaqat, H. A. 2013. Genetic divergence and path coefficient analysis for yield related attributes in sunflower (Helianthus annuus L.) under less water conditions at productive phase. Plant Knowledge Journal., 2013; 2(1):20-23.

(33.) Ketola, T. and Kotiaho, J.S. Inbreeding, energy use and condition. Journal of Evolutionary Biology., 2009; 22(4): 770-781.

(34.) Kremen, C. and Miles, A. Ecosystem services in biologically diversified versus conventional Forming system: Benefits, externalities and trade-offs. Eco Soc, 2012; 17(4): 40.

(35.) Kumar, P., Dhillon, S. K., Kaur J. and Sao A. Shift in Character Association under Different Water Stress Environments in Sunflower (Helianthus annuus L.). Indian J. Ecol., 2014; 41(1):135-138.

(36.) Kumari S and Singh SK. Assesment of genetic diversity in promising finger millet [Eleusine coracana (L.) Gaertn] genotypes. The Bioscan., 2015; 10(2): 825-830.

(37.) Kundzewicz, Z.W., Mata, L.J., Arnell, N.W., Doll, P., Kabat, P., Jimenez, B., Miller, K.A., Oki, T., Sen, Z., Leimu, R., Vergeer, P., Angeloni, F. and Ouborg, N.J. Habitat fragmentation, climate change, and inbreeding in plants. Annals of the New York Academy of Sciences 1195 (The Year in Ecology and Conservation Biology 2010)., 2010; 84-98.

(38.) Liu, C.Z. Suggestion on water resources in China corresponding with global climate change. China Water Resource., 2002; 2:36-37.

(39.) Loganathan, P. Genetic divergence, diallel analysis and second generation studies in sunflower (Helianthus annuus L). Ph.D. Thesis, Tamil Nadu Agricultural University, Coimbatore., 2002.

(40.) Loganathan, P., Gopalan, A. and Manivannan, N. Genetic divergence in sunflower (Helianthus annuus L). Research on crops., 2006; 7:198-201.

(41.) Machikowa, T. and Saetang, C. Correlation and path coefficient analysis on seed yield in sunflower. Suranaree J Sci Tech.,2008; 15(3):243-248.

(42.) Mahalanobis, PC. On the generalized distance in statistics. Proceedings Society of Animal Production., 1936; 33:293-301.

(43.) Mandel, J.R., Dechaine, J.M., Marek, L.F. and Burke, J.M. Genetic diversity and population structure in cultivated sunflower and a comparison to its wild progenitor (Helianthus annuus L). Theor Appl Genet., 2011; 123:693-704.

(44.) Mijatovic, D., Van Oudenhoven, F., Eyzaguirre, P. and Hodgkin, T. The role of agricultural biodiversity in strengthening resilience to climate change: Towards an analytical framework. Int J Agric Sustain., 2013; 11 (2):95-107.

(45.) Min, S.K., Zhang, X., Zwiers, F.W. and Hegerl, G.C. 2011. Human contribution to more-intense precipitation extremes. Nature., 2011; 470:378-381.

(46.) Mohan, G.S. and Seetharam, A. Genetic divergence in lines of sunflower derived from interspecific hybridization. J Genet and Breed., 2005; 37(2):77-84.

(47.) Parameshwarappa, S.G., Salimath, PM. and Palakshappa, M.G. Assessment of genetic diversity in niger (Guizotia abyssinica (L) Cass). Karnataka J. Agric. Sci., 2009; 22(4):879-880.

(48.) Parmesan, C. Ecological and evolutionary responses to recent climate change. Annu. Rev. Ecol. Evol. Syst, 2006; 37:637-69.

(49.) Pateman, R. The effects of climate change on the distribution of species in the UK. Technical Paper 6, Terrestrial Biodiversity Climate Change Report Card. 2013.

(50.) Phillimore, A.B., Hadfield, J.D., Jones, O.R. and Smithers, R.J. Differences in spawning date between populations of common frog reveal local adaptation. Proceedings of the National Academy of Sciences, 2010; 107(18): 8292-8297.

(51.) Phillimore, A.B., Stalhandske, S., Smithers, R.J., Bernard, R. Dissecting the contributions of plasticity and local adaptation to the phenology of a butterfly and its host plants. The American Naturalist., 2012; 180(5): 655-670.

(52.) Punitha, B., Vindhiyavarman, P. and Manivannan, N. Genetic divergence study in sunflower (Helianthus annuus L.). Electron. J. Plant Breed, 2010; 1(4):426-430.

(53.) Ramchander, S., Raveendran, M. and Robin, S. Performance of backcross inbred lines of rice (Oryza sativa L.) across different water regimes and their genome analysis. The Bioscan., 2014; 9(4): 1683-1687.

(54.) Rauf, S. and Sadaqat, H. A. Effects of varied water regimes on root length, dry matter partitioning and endogenous plant growth regulators in sunflower (Helianthus annuus L.). Journal of Plant Interactions. 2007; 2(1):1080.

(55.) Reddy, A.R., Chaitanya, K.V., Vivekanandan, M. Drought-induced responses of photosynthesis and antioxidant metabolism in higher plants. J. Plant Physiol., 2004; 161: 1189-1202.

(56.) Reed, D.H. and Frankham, R. Correlation between Fitness and Genetic Diversity. Conservation Biol., 2003; 17(1): 230-235.

(57.) Sasikala, M. Variability studies in interspecific hybrid derivatives of sunflower. M.Sc. (Agri.) Thesis, Tamil Nadu Agricultural University, Coimbatore., 2000.

(58.) Shafi, M., Bakht, J., Yousaf, M. and Khan, M. A. Effects of irrigation regime on growth and seed yield of sunflower (Helianthus annuus L.). Pak J Bot, 2013; 45(6):1995-2000.

(59.) Shamshad, M., Dhillon, S.K., Tyagi, V. and Akhatar, J. Assessment of Genetic Diversity in Sunflower (Helianthus annuus L.) germplasm. Int J of Agri and Food Sci Tech., 2014; 5(4):267-272.

(60.) Shekhawat N, Jadeja G. C., Singh J and Ramesh. Genetic diversity analysis in relation to seed yield and its component traits in Indian mustard (Brassica juncea L. czern & coss). The Bioscan., 2014; 9(2): 713-717.

(61.) Sparks, T.H. 2013. The implications of Climate Change for phenology in the UK .Technical Paper 12, Terrestrial Biodiversity Climate Change Report Card sunflower (H. annuus L.). The Andhra Agric. J., 2013; 51: 39-43.

(62.) Sreedhar, R.V., Ganagaprasad, S., Ravikumar, R.L., and Salimath, P.M. Assessment of genetic diversity in niger, Guizotia abyssinica (L.) Cass. J. Oilseeds Res, 2006; 23(2):191-193.

(63.) Subrahmanyam, S.V.R., Kumar, S.S. and Ranganatha, A.R.G. Genetic divergence for seed parameters in sunflower (Helianthus annuus L.). Helia., 2003; 26 (38):73-80.

(64.) Taklewold, A., Jayaramaiah, H. and Gowda, J. Genetic divergence study in sunflower (HelianthusannuusL.). Helia., 2000; 23(32):93-104.

(65.) Thackeray, S.J., Sparks, T.H., Frederiksen, M., Burthe, S., Bacon, P.J., Bell, J.R. et al. Trophic level asynchrony in rates of phenological change for marine, freshwater and terrestrial environments. Global Change Biology., 2010; 16(12): 3304-3313.

(66.) Tripathi, A., Bisen, R., Ahirwal, R. P., Paroha, S., Sahu, R. and Ranganatha, A. R. G. Study on genetic divergence in Sesame (Sesamum indicum L.) germplasm based on morphological and quality traits. The Bioscan., 2013; 8(4): 1387-1391.

(67.) Turhan, H. and Basar, I. Invitro and invivo water stress in sunflower (Helianthus annuus L). Helia., 2004; 27: 227-236.

(68.) USDA, Agricultural Weather Facility. Global crop production review, 2005. http:// www.usda.gov/oce/weather/pubs/Annual/ CropProduction2005.pdf.

(69.) Vanaja, M., Yadav, S.K., Archana, G., Lakshmi, J. N., Ram Reddy, P. R., Vagheera, P.,. Abdul Razak, S. K., Maheswari, M. and Venkateswarlu, B. Response of C4 (maize) and C3 (sunflower) crop plants to drought stress and enhanced carbon dioxide concentration. Plant Soil Environ., 2011; 57:207-215.

(70.) Zala, H., Bosamia, T., Kulkarni, K. and Shukla, Y. 2014. Assessment of molecular diversity in wheat (Triticum aestivum L. and Triticum durum L.) genotypes cultivated in semi-arid region of Gujarat. The Bioscan., 2014; 9(2): 731-737

(71.) Zhang, Y, Chen, H.Y.H. and Reich, P.B. 2012. Forest productivity increases with evenness, species richness and trait variation: A global meta-analysis. J Ecol., 2012; 100(3): 742-749.

Prafull Kumar [1] *, S.K. Dhillon [2], Abhinav Sao [1], A.K. Thakur [1], Poonam Kumari [1], R.R. Kanwar [1] and R.K. Patel [1]

[1] S.G. College of Agriculture and Research Station, Jagdalpur, CG, India.

[2] Punjab Agricultural University, Ludhiana, Punjab, India.

(Received: 26 February 2016; accepted: 16 April 2016)

* To whom all correspondence should be addressed.

E-mail: prafull397@gmail.com

Caption: Fig. 1. Genetic distance of genotypes
Table 1. Geographical and parental
diversity among test genotypes

S. No   Genotypes/Source

1       P61R/RHA-61
2       R273/DOR, Hyderabad
3       P93R/[GP.sub.2]-378
4       95C1R/Bangalore
5       P91R/[GP.sub.4]-357
6       P107[RP.sub.2]/OPH
7       P107[RP.sub.1]/OPH
8       P69R/IL-50-1
9       3376R/DOR, Hyderabad
10      P100R/LIPO-8-1
11      P110R/RHA 855
12      P87R/OPH-15-1
13      P89R/[GP.sub.4]-280
14      P75R/OPH-34-1-1
15      P94R/[GP.sub.2]-661
16      P111R/[GP.sub.2]-2861
17      P112R/DRS1-414
18      P115R/[GP.sub.2]-237
19      P119R/1538-1
20      P121R/[GP.sub.6]-35
21      P124R/OPH-29-4-1
22      NDLR2/Nandyal
23      NDLR1/Nandyal
24      44B/--
25      40B/PAU, Ludhiana
26      10B/PAU, Ludhiana
27      234B/Bangalore
28      11B/PAU, Ludhiana
29      304B/Bangalore
30      395B/Perendovic 301
31      7-1-B/Andhra Pradesh
32      45B/PAU, Ludhiana
33      47B/PAU, Ludhiana
34      48B/PAU, Ludhiana
35      49B/PAU, Ludhiana
36      50B/PAU, Ludhiana
37      52B/PAU, Ludhiana
38      53B/PAU, Ludhiana
39      36B/PAU, Ludhiana
40      RCR8297/DOR, Hyderabad
41      RHA297/DOR, Hyderabad

Table 2(a): Analysis of variance under differential water stress

Parameter                        Mean sum of squares
                      [W.sub.1]                    [W.sub.2]
                Source of variation           Source of variation
             Rep     Genotype    Error    Rep    Genotype    Error
            df=2      df=40      df=80   df=2      df=40     df=80

EV          1.02     1.65 **     0.43    0.58     1.35 **    0.35
CT          0.97     3.64 **     0.98    8.61     3.5 **      0.9
PS          0.25     2.75 **      0.2    0.35     1.25 **    0.02
LAI         0.04     0.26 **     0.01    0.01     0.06 **    0.01
LWP         0.01     0.14 **     0.01    0.49     0.47 **    0.18
DF          4.84     17.09 **     3.5    25.58   29.34 **     5.2
DM          5.51     14.79 **    0.93    0.62     9.66 **    0.85
PH          16.95   1263.92 **   9.39    21.98   1203.6 **   11.33
HD          0.16     11.00 **     0.4     0.2    10.03 **    0.27
SY          0.38    287.02 **    1.37    1.87    247.46 **   2.77
SW          0.08     4.57 **      0.1    0.06     4.39 **    0.09
OC          4.84     17.09 **     3.5    25.58   29.34 **     5.2

Parameter                        Mean sum of squares
                      [W.sub.3]                   [W.sub.4]
                Source of variation          Source of variation
            Rep     Genotype    Error    Rep     Genotype    Error
            df=2     df=40      df=80   df=2      df=40      df=80

EV          1.93    1.46 **     0.39     0.1     1.85 **     0.44
CT          1.37    2.65 **     0.58    3.87     2.45 **     0.55
PS          0.29    2 75 **      0.3    0.38     2.23 **     0.38
LAI         0.03    0.10 **     0.01    0.05     0.15 **     0.01
LWP         0.61    0.23 **      0.2    0.29     0.15 **     0.12
DF          4.3     16.47 **    4.67    28.19    48.97 **    3.41
DM          2.08    26.18 **    1.01    0.03     8.94 **     0.85
PH          4.77   1016.95 **   9.11    20.45   1219.89 **   9.23
HD          0.28    8.39 **     0.34    0.11     13.64 **    0.38
SY          4.83   256.38 **    1.75    4.05    246.45 **    1.65
SW          0.09    3.34 **     0.09    0.15     6.09 **     0.09
OC          4.3     16.47 **    4.67    28.19    48.97 **    3.41

*, **--significant at 5% and 1% level respectively

W1--control; W2--first water stress environment; W3--second water
stress environment; W4--third water stress environment

EV: Early Vigour; CT: Canopy Temperature; PS: Photosynthetic capacity;
LAI: Leaf Area Index; LWP: Leaf Water Potential; DL: Days to 50%
flowering; DM: Days to Maturity; PH: Plant Height; HD: Head Diameter;
SY: Seed Yield per plant; SW: 100 Seed Weight; OC: Oil content

Table 2(b). Analysis of variance for various morphophysiological
traits pooled over environments

                                                Mean Squares
               df      EV          CT         PS        LAI       WP

Replication     8    2.46 **     3 7**       0.07      0.01     0.35 *
  (in env)
Env.            3    8.55 **   1422.11 **   0.80 **   0.57 **   0.84 **
Genotypes      40    5.35 **     3.74**      0.08     0.46 **   0.44 **
Geno. X env    120   2.66 **     2.83**     0.90 **   0.03 **   111 **
Pooled error   320    0.41        0.76       0.08      0.01       0.2

                                Mean Squares
                  DF         DM          PH          HD         SY

Replication    3.16 **    2.06 **     16.04 *       0.19      2.78 *
  (in env)
Env.           37.28 **   68.11 **   2763.73 **   47.22 **   469.41 **
Genotypes      174.7 **   40.51 **   4432.31 **   38.53 **   960.95 **
Geno. X env    5.27 **    6.35 **     90.68 **    1.51 **    25.45 **
Pooled error     1.23       0.91        9.77        0.34       1.88

                    Mean Squares
                  SW         OC

Replication     0.1 **    15.73 **
  (in env)
Env.           20.41 **   243.22 **
Genotypes      15.01 **   52.61 **
Geno. X env    1.12 **    19.75 **
Pooled error     0.09        4.2

Table 3. Morphometric diversity among test genotypes in four treatments

Inbred line                       Canopy Temperature ([degrees]C)
                         [W.sub.1]   [W.sub.2]   [W.sub.3]   [W.sub.4]

P-61-R                     27.56       28.11       29.28       33.95
R-273                      26.87       29.09       28.58       35.24
P-93-R                     27.01       27.44       29.95       32.65
95-C-1-R                   26.98       27.67       28.62       34.47
P-91-R                     27.74       27.94       29.20       35.43
P-107-R-[P.sub.2]          27.73       28.21       29.55       35.23
P-107-R-[P.sub.1]          26.48       27.40       29.23       34.04
P-69-R                     26.93       28.67       28.33       34.80
3376-R                     26.82       26.97       29.55       35.27
P-100-R                    26.07       28.48       28.87       35.35
P-110-R                    27.05       27.82       29.27       34.10
P-87-R                     25.88       27.53       29.22       35.50
P-89-R                     25.94       28.85       27.72       35.11
P-75-R                     27.52       27.81       29.22       33.50
P-94-R                     27.28       26.80       30.40       34.07
P-111-R                    26.58       27.41       29.02       35.03
P-112-R                    26.90       27.57       28.28       34.20
P-115-R                    26.84       27.86       29.55       34.23
P-119-R                    26.60       28.41       29.20       34.05
P-121-R                    26.23       27.73       28.93       34.05
P-124-R                    26.74       26.06       29.07       33.50
NDLR-2                     26.23       26.82       29.68       34.43
NDLR-1                     26.05       28.31       28.13       33.53
44-B                       26.44       28.24       28.85       34.38
40-B                       26.42       27.22       29.58       34.83
10-B                       26.89       28.09       28.72       34.75
234-B                      25.96       28.62       28.52       33.34
11-B                       26.73       27.73       28.02       33.67
304-B                      27.21       27.66       28.93       34.57
395-B                      26.68       27.83       29.38       33.33
7-1-B                      26.31       27.54       27.88       33.82
45-B                       26.92       29.90       29.18       34.78
47-B                       26.46       27.37       28.28       33.00
48-B                       27.05       27.80       28.45       35.27
49-B                       26.33       29.38       28.30       33.73
50-B                       25.61       27.29       28.20       34.51
52-B                       27.04       27.33       28.73       33.08
53-B                       26.91       27.48       28.57       34.70
36-B                       27.10       28.22       28.07       34.64
RCR-8297                   26.88       27.67       28.53       35.09
RHA-297                    26.74       27.09       27.83       35.03
Exp Mean                   26.72       27.84       28.85       34.35
P-61-R                      63          60          59          63
R-273                       67          62          63          66
P-93-R                      68          63          64          68
95-C-1-R                    65          63          60          64
P-91-R                      65          62          62          65
P-107-R-[P.sub.2]           64          62          65          64
P-107-R-[P.sub.1]           68          63          64          65
P-69-R                      68          63          59          66
3376-R                      64          64          63          64
P-100-R                     63          63          61          62
P-110-R                     61          61          60          61
P-87-R                      62          62          59          63
P-89-R                      64          68          63          65
P-75-R                      62          60          60          62
P-94-R                      63          60          59          63
P-111-R                     81          74          74          79
P-112-R                     79          76          74          78
P-115-R                     66          63          64          64
P-119-R                     62          60          59          60
P-121-R                     61          61          62          61
P-124-R                     69          65          67          67
NDLR-2                      62          61          62          62
NDLR-1                      76          72          73          75
44-B                        64          63          62          63
40-B                        65          63          61          63
10-B                        67          66          66          66
234-B                       68          63          65          67
11-B                        63          60          59          63
304-B                       63          61          60          64
395-B                       68          64          66          66
7-1-B                       69          65          66          66
45-B                        67          64          64          65
47-B                        64          59          58          62
48-B                        57          56          56          57
49-B                        62          59          58          60
50-B                        63          60          62          62
52-B                        65          65          62          64
53-B                        67          64          64          65
36-B                        67          66          64          66
RCR-8297                    67          65          66          66
RHA-297                     66          60          62          66
Exp Mean                    65          63          62          64

                                        Seed Yield per plant (g)
                         [W.sub.1]   [W.sub.2]   [W.sub.3]   [W.sub.4]

P-61-R                     26.5        20.5        19.2        21.4
R-273                      19.5        16.0        12.4        16.2
P-93-R                     39.3        32.8        32.7        37.0
95-C-1-R                   10.3         7.2         9.7        10.0
P-91-R                     23.4        21.3        23.3        21.5
P-107-R-[P.sub.2]          34.1        26.0        26.6        28.0
P-107-R-[P.sub.1]          47.1        42.0        38.8        42.4
P-69-R                     34.1        24.8        29.6        32.5
3376-R                     20.9        17.1        13.4        17.1
P-100-R                    26.0        23.6        23.8        25.0
P-110-R                    26.6        22.1        23.7        26.8
P-87-R                     54.7        52.2        49.8        51.8
P-89-R                     44.2        37.1        40.8        31.6
P-75-R                     46.2        36.5        35.8        36.5
P-94-R                     34.3        21.0        31.3        33.1
P-111-R                    46.7        40.3        44.2        45.5
P-112-R                    35.6        22.1        15.0        30.0
P-115-R                    39.0        32.6        32.7        36.8
P-119-R                    39.3        19.7        30.5        37.5
P-121-R                    46.1        32.7        36.8        41.6
P-124-R                    37.1        31.9        23.7        34.2
NDLR-2                     46.4        37.7        27.0        41.0
NDLR-1                     31.3        21.4        18.2        28.8
44-B                       33.7        30.4        26.4        27.4
40-B                       38.4        32.5        33.4        34.3
10-B                       32.4        23.2        27.6        29.1
234-B                      34.3        23.4        24.9        30.0
11-B                       33.5        28.2        29.3        31.2
304-B                      15.6        12.7        13.2        13.5
395-B                      30.6        16.7        20.5        26.3
7-1-B                      28.8        18.7        21.0        23.9
45-B                       32.9        27.4        24.2        28.6
47-B                       33.7        28.4        28.0        30.4
48-B                       33.5        23.9        26.9        31.2
49-B                       36.3        27.9        27.0        34.2
50-B                       28.2        23.1        24.5        26.2
52-B                       29.1        18.5        17.6        25.5
53-B                       39.4        34.2        35.5        29.0
36-B                       30.4        23.6        15.5        24.9
RCR-8297                   14.9        12.5        12.9        12.7
RHA-297                    15.2        12.8        13.0        13.3
Exp Mean                   32.9        25.7        25.8        29.2

Inbred line                           Photosynthetic Capacity
                         [W.sub.1]   [W.sub.2]   [W.sub.3]   [W.sub.4]

P-61-R                     0.74        0.66        0.68        0.64
R-273                      0.71        0.62        0.69        0.65
P-93-R                     0.76        0.63        0.68        0.72
95-C-1-R                   0.76        0.71        0.64        0.72
P-91-R                     0.77        0.70        0.70        0.71
P-107-R-[P.sub.2]          0.69        0.64        0.64        0.67
P-107-R-[P.sub.1]          0.70        0.57        0.68        0.62
P-69-R                     0.76        0.73        0.71        0.73
3376-R                     0.73        0.72        0.65        0.71
P-100-R                    0.74        0.69        0.66        0.73
P-110-R                    0.73        0.65        0.63        0.72
P-87-R                     0.75        0.69        0.63        0.67
P-89-R                     0.75        0.69        0.62        0.70
P-75-R                     0.74        0.70        0.67        0.71
P-94-R                     0.74        0.67        0.70        0.73
P-111-R                    0.78        0.67        0.65        0.73
P-112-R                    0.76        0.67        0.68        0.70
P-115-R                    0.74        0.72        0.65        0.68
P-119-R                    0.75        0.67        0.68        0.69
P-121-R                    0.75        0.65        0.62        0.67
P-124-R                    0.69        0.63        0.65        0.66
NDLR-2                     0.73        0.67        0.65        0.69
NDLR-1                     0.69        0.63        0.64        0.67
44-B                       0.75        0.62        0.60        0.69
40-B                       0.77        0.70        0.67        0.71
10-B                       0.74        0.57        0.63        0.65
234-B                      0.72        0.65        0.63        0.66
11-B                       0.77        0.65        0.62        0.72
304-B                      0.76        0.66        0.63        0.71
395-B                      0.76        0.69        0.68        0.74
7-1-B                      0.72        0.60        0.66        0.69
45-B                       0.69        0.59        0.58        0.65
47-B                       0.72        0.69        0.67        0.69
48-B                       0.72        0.65        0.62        0.68
49-B                       0.75        0.62        0.63        0.74
50-B                       0.71        0.65        0.64        0.69
52-B                       0.75        0.62        0.59        0.70
53-B                       0.78        0.68        0.66        0.70
36-B                       0.71        0.61        0.59        0.62
RCR-8297                   0.74        0.69        0.68        0.70
RHA-297                    0.72        0.63        0.65        0.68
Exp Mean                   0.74        0.66        0.65        0.69
P-61-R                      93          88          85          89
R-273                       93          90          92          91
P-93-R                      95          92          90          93
95-C-1-R                    95          88          89          94
P-91-R                      95          87          87          93
P-107-R-[P.sub.2]           99          93          92          96
P-107-R-[P.sub.1]           92          89          90          91
P-69-R                      93          91          92          92
3376-R                      90          86          85          89
P-100-R                     89          85          86          89
P-110-R                     94          90          92          91
P-87-R                      93          89          88          91
P-89-R                      93          88          87          91
P-75-R                      94          86          87          92
P-94-R                      95          90          91          92
P-111-R                     96          91          93          92
P-112-R                     94          90          90          92
P-115-R                     93          92          89          92
P-119-R                     89          83          85          88
P-121-R                     94          91          90          92
P-124-R                     94          88          89          92
NDLR-2                      93          91          92          92
NDLR-1                      94          91          92          92
44-B                        95          92          89          93
40-B                        90          87          86          89
10-B                        95          91          88          92
234-B                       94          88          89          93
11-B                        95          91          93          92
304-B                       94          92          93          92
395-B                       90          85          86          90
7-1-B                       93          90          91          92
45-B                        90          87          89          88
47-B                        92          98          86          91
48-B                        92          90          91          91
49-B                        95          92          92          93
50-B                        90          88          89          88
52-B                        96          93          92          94
53-B                        97          90          91          95
36-B                        94          85          88          91
RCR-8297                    98          93          90          94
RHA-297                     92          89          91          90
Exp Mean                    93          91          92          91

                                       100 Achene Weight (g)
                         [W.sub.1]   [W.sub.2]   [W.sub.3]   [W.sub.4]

P-61-R                      7.7         6.0         5.8         6.2
R-273                       6.3         4.7         4.7         5.8
P-93-R                      7.7         5.3         8.0         6.2
95-C-1-R                    5.0         2.2         4.0         3.2
P-91-R                      6.5         5.2         5.3         3.6
P-107-R-[P.sub.2]           7.1         5.6         5.8         6.7
P-107-R-[P.sub.1]           6.3         5.4         5.1         5.8
P-69-R                      7.3         5.7         6.0         6.8
3376-R                      5.2         3.2         4.7         2.7
P-100-R                     6.8         5.2         5.6         6.2
P-110-R                     7.1         6.2         5.5         4.4
P-87-R                      6.4         4.7         5.5         4.4
P-89-R                      8.4         6.8         6.7         6.8
P-75-R                      7.4         5.4         5.7         6.1
P-94-R                      8.3         5.1         7.2         6.7
P-111-R                     7.6         6.9         6.3         5.0
P-112-R                     7.2         5.2         4.7         6.2
P-115-R                     6.9         5.8         6.4         6.7
P-119-R                     6.4         4.9         4.7         5.7
P-121-R                     6.5         5.7         5.3         6.1
P-124-R                     7.8         6.4         6.7         7.0
NDLR-2                      6.6         6.3         6.2         6.4
NDLR-1                      7.2         4.1         5.1         6.4
44-B                        7.1         5.4         6.4         7.0
40-B                        8.5         5.7         5.7         6.2
10-B                        6.9         6.7         6.1         6.5
234-B                       7.2         5.0         6.7         6.6
11-B                        7.7         6.1         6.4         7.2
304-B                       7.4         5.9         4.6         5.9
395-B                       7.1         5.4         4.8         3.9
7-1-B                      12.8        10.5         9.6        10.9
45-B                        6.9         6.2         6.1         5.9
47-B                        7.0         5.2         5.4         6.7
48-B                        6.3         5.7         5.3         5.3
49-B                        7.6         5.7         6.2         5.1
50-B                        6.7         5.8         5.3         5.6
52-B                        7.3         5.2         6.3         6.9
53-B                        7.9         6.3         5.8         6.7
36-B                        7.2         6.4         5.7         4.8
RCR-8297                    5.1         3.9         4.2         4.0
RHA-297                     4.9         4.8         4.1         3.5
Exp Mean                    7.1         5.5         5.7         5.8

Inbred line                             Leaf Area Index
                         [W.sub.1]   [W.sub.2]   [W.sub.3]   [W.sub.4]

P-61-R                      0.5         0.3         0.4         0.4
R-273                       0.5         0.3         0.3         0.5
P-93-R                      0.5         0.3         0.3         0.4
95-C-1-R                    0.4         0.3         0.3         0.4
P-91-R                      0.5         0.2         0.4         0.4
P-107-R-[P.sub.2]           0.6         0.3         0.4         0.5
P-107-R-[P.sub.1]           0.5         0.4         0.4         0.5
P-69-R                      0.5         0.3         0.4         0.4
3376-R                      0.7         0.4         0.3         0.6
P-100-R                     1.2         0.7         0.7         1.1
P-110-R                     1.0         0.4         0.6         0.8
P-87-R                      0.7         0.4         0.4         0.6
P-89-R                      0.5         0.3         0.4         0.5
P-75-R                      0.6         0.3         0.3         0.6
P-94-R                      0.7         0.5         0.5         0.6
P-111-R                     0.6         0.3         0.3         0.6
P-112-R                     1.3         0.4         1.0         1.1
P-115-R                     0.4         0.3         0.2         0.4
P-119-R                     0.5         0.2         0.2         0.3
P-121-R                     0.7         0.3         0.6         0.6
P-124-R                     0.6         0.4         0.3         0.5
NDLR-2                      0.6         0.5         0.4         0.5
NDLR-1                      0.5         0.3         0.3         0.4
44-B                        0.6         0.5         0.5         0.5
40-B                        1.5         0.7         0.6         1.3
10-B                        0.7         0.3         0.5         0.6
234-B                       0.6         0.4         0.4         0.4
11-B                        0.5         0.2         0.2         0.4
304-B                       0.7         0.3         0.5         0.6
395-B                       0.6         0.3         0.4         0.5
7-1-B                       0.4         0.3         0.3         0.4
45-B                        0.4         0.4         0.3         0.3
47-B                        0.5         0.2         0.3         0.4
48-B                        0.4         0.3         0.3         0.4
49-B                        0.7         0.3         0.4         0.5
50-B                        0.7         0.5         0.4         0.6
52-B                        0.6         0.2         0.4         0.5
53-B                        0.4         0.2         0.3         0.4
36-B                        1.2         0.8         0.9         0.9
RCR-8297                    0.5         0.3         0.3         0.4
RHA-297                     1.3         0.7         0.8         1.0
Exp Mean                   0.66        0.37        0.42        0.56
P-61-R                      127         116         112         125
R-273                       127         102         125         120
P-93-R                      131         118         124         125
95-C-1-R                    148         132         134         143
P-91-R                      135         131         126         132
P-107-R-[P.sub.2]           120         109         115         118
P-107-R-[P.sub.1]           132         125         121         128
P-69-R                      98          90          94          98
3376-R                      130         121         119         128
P-100-R                     122         115         115         121
P-110-R                     123         85          110         119
P-87-R                      140         127         110         132
P-89-R                      146         131         134         140
P-75-R                      150         122         119         140
P-94-R                      128         87          118         123
P-111-R                     168         144         131         163
P-112-R                     207         182         192         203
P-115-R                     124         114         117         121
P-119-R                     135         125         122         127
P-121-R                     96          87          84          90
P-124-R                     110         98          99          105
NDLR-2                      131         121         125         125
NDLR-1                      144         126         125         134
44-B                        142         123         118         138
40-B                        127         108         108         120
10-B                        130         98          94          120
234-B                       130         111         117         126
11-B                        107         95          94          102
304-B                       95          66          81          89
395-B                       117         94          107         113
7-1-B                       135         123         123         131
45-B                        166         130         136         156
47-B                        146         123         121         138
48-B                        117         103         105         111
49-B                        105         88          91          99
50-B                        128         120         115         123
52-B                        131         107         115         124
53-B                        139         116         121         131
36-B                        104         89          87          94
RCR-8297                    133         121         123         128
RHA-297                     125         102         110         120
Exp Mean                    130         112         115         124

                                            Oil Content (%)
                         [W.sub.1]   [W.sub.2]   [W.sub.3]   [W.sub.4]

P-61-R                     42.6        38.3        40.7        35.1
R-273                      45.2        37.3        34.6        31.1
P-93-R                     42.7        37.3        36.7        42.0
95-C-1-R                   44.8        38.3        38.1        40.6
P-91-R                     43.9        38.8        40.5        41.6
P-107-R-[P.sub.2]          44.1        36.4        36.5        39.9
P-107-R-[P.sub.1]          40.4        32.9        33.4        36.6
P-69-R                     44.1        39.0        38.0        41.9
3376-R                     40.6        35.3        38.1        30.7
P-100-R                    44.5        37.6        40.7        42.4
P-110-R                    43.3        38.6        38.4        41.9
P-87-R                     45.6        38.8        38.8        42.4
P-89-R                     45.3        41.2        37.7        41.9
P-75-R                     41.8        40.4        40.4        36.9
P-94-R                     39.1        35.4        34.9        36.9
P-111-R                    45.0        39.8        38.3        42.2
P-112-R                    42.2        36.3        38.2        38.3
P-115-R                    43.7        40.4        39.6        42.4
P-119-R                    44.3        36.5        39.3        38.9
P-121-R                    40.7        35.4        36.3        39.6
P-124-R                    45.1        40.8        39.4        35.3
NDLR-2                     43.2        38.7        38.7        40.9
NDLR-1                     39.7        35.7        35.1        38.3
44-B                       44.3        36.7        36.9        35.9
40-B                       44.7        39.5        42.1        39.0
10-B                       41.6        37.3        35.8        29.6
234-B                      45.3        38.1        40.8        41.6
11-B                       43.2        30.9        35.8        29.4
304-B                      43.8        40.8        40.8        41.9
395-B                      42.4        40.1        37.8        41.0
7-1-B                      44.9        37.7        38.5        31.0
45-B                       41.5        36.9        37.8        40.2
47-B                       42.6        42.1        31.8        39.0
48-B                       47.6        41.6        40.4        36.0
49-B                       42.2        45.0        40.2        38.8
50-B                       44.0        40.0        38.7        42.7
52-B                       46.7        40.0        41.8        41.7
53-B                       34.1        35.5        40.2        32.0
36-B                       44.3        37.9        42.4        34.1
RCR-8297                   42.7        49.9        38.4        38.8
RHA-297                    46.4        39.2        38.4        43.6
Exp Mean                   43.2        38.5        38.3        38.3

Inbred line                           Leaf Water Potential (mpa)
                         [W.sub.1]   [W.sub.2]   [W.sub.3]   [W.sub.4]

P-61-R                     -2.35       -2.77       -2.96       -2.56
R-273                      -2.77       -3.29       -3.17       -2.96
P-93-R                     -2.71       -3.96       -3.28       -3.15
95-C-1-R                   -2.30       -3.83       -3.32       -2.55
P-91-R                     -2.33       -3.21       -3.56       -2.88
P-107-R-[P.sub.2]          -2.33       -2.71       -3.25       -2.70
P-107-R-[P.sub.1]          -2.26       -2.55       -2.40       -2.50
P-69-R                     -2.74       -3.07       -3.13       -2.98
3376-R                     -2.86       -2.96       -3.31       -2.64
P-100-R                    -2.57       -3.01       -2.92       -2.60
P-110-R                    -2.79       -2.86       -2.98       -2.81
P-87-R                     -2.59       -2.91       -2.77       -2.82
P-89-R                     -2.35       -2.84       -2.98       -2.81
P-75-R                     -2.67       -2.99       -2.94       -2.81
P-94-R                     -2.74       -3.20       -2.93       -3.64
P-111-R                    -2.80       -2.85       -3.21       -3.02
P-112-R                    -2.38       -2.76       -2.98       -3.09
P-115-R                    -2.26       -3.73       -2.43       -2.78
P-119-R                    -2.59       -3.35       -3.34       -3.31
P-121-R                    -2.64       -2.73       -3.31       -3.30
P-124-R                    -2.71       -3.34       -3.41       -3.44
NDLR-2                     -2.13       -3.26       -3.69       -3.45
NDLR-1                     -2.76       -3.16       -3.19       -3.25
44-B                       -2.53       -2.80       -2.83       -2.68
40-B                       -2.53       -3.48       -3.33       -3.50
10-B                       -2.67       -3.27       -3.03       -3.48
234-B                      -2.33       -2.74       -2.56       -3.01
11-B                       -2.68       -3.33       -3.73       -3.44
304-B                      -2.83       -2.77       -3.04       -3.01
395-B                      -2.72       -3.59       -3.57       -3.44
7-1-B                      -2.46       -2.70       -3.21       -3.26
45-B                       -2.50       -3.47       -3.34       -2.57
47-B                       -2.60       -2.64       -2.56       -3.04
48-B                       -2.47       -3.61       -3.72       -3.44
49-B                       -2.49       -3.11       -3.28       -2.67
50-B                       -2.80       -3.77       -3.55       -2.92
52-B                       -2.73       -3.27       -3.13       -3.05
53-B                       -2.71       -3.36       -3.26       -2.86
36-B                       -2.34       -3.73       -3.41       -3.50
RCR-8297                   -2.51       -3.29       -3.34       -3.15
RHA-297                    -2.55       -3.39       -3.60       -2.85
Exp Mean                   -2.56       -3.16       -3.17       -3.02
P-61-R                     11.7         9.6         9.4        10.1
R-273                      10.5         9.3         9.3        10.2
P-93-R                     16.5        13.0        12.9        16.1
95-C-1-R                   10.4         9.7         9.2         8.5
P-91 -R                    15.4        14.7        14.4        15.1
P-107-R-[P.sub.2]          14.4        12.5        12.1        13.5
P-107-R-[P.sub.1]          14.5        13.2        13.2        13.7
P-69-R                     16.4        14.0        13.4        14.9
3376-R                      9.7         8.4         9.1         7.5
P-100-R                    12.9        11.5        11.6         9.8
P-110-R                    13.0        11.5        10.4        12.5
P-87-R                     17.1        13.9        14.1        15.2
P-89-R                     14.5        12.9        12.7        14.1
P-75-R                     15.5        13.5        13.3        15.1
P-94-R                     14.6        10.9        12.9        14.3
P-111-R                    16.0        13.7        13.1        14.1
P-112-R                    15.3        15.0        13.6        15.7
P-115-R                    16.4        12.8        13.5        15.4
P-119-R                    14.9        11.7        10.8        13.0
P-121-R                    15.4        12.7        13.2        15.0
P-124-R                    13.9        13.2        13.0        13.0
NDLR-2                     15.5        14.4        13.9        14.2
NDLR-1                     15.9        14.4        14.0        14.8
44-B                       15.3        13.2        13.2        13.7
40-B                       14.5        11.9        11.9        13.3
10-B                       13.4        10.8        11.0        11.7
234-B                      14.6        12.8        12.7        13.9
11-B                       14.3        12.4        10.4        13.4
304-B                      13.1        10.7        10.3        12.4
395-B                      14.9        10.8        11.4        14.2
7-1-B                      17.9        15.6        15.5        16.3
45-B                       13.6        11.6        11.6        12.8
47-B                       15.8        13.9        13.7        15.7
48-B                       14.6        13.4        12.3        13.7
49-B                       15.3        12.7        12.3        12.9
50-B                       16.5        14.6        10.6        15.5
52-B                       13.8        12.0        12.4        13.3
53-B                       16.2        14.2        14.5        15.5
36-B                       16.3        12.3        12.2        15.4
RCR-8297                   10.0         8.3         8.8         9.3
RHA-297                    13.1         9.1        10.2        11.5
Exp Mean                   14.4        12.3        12.1        13.4

Table 4. Association of inbreds as per genetic closeness and utility
under stress

Cluster        Inherent genetic diversity        Stress tolerant
               among inbreds                     heterogeneous inbreds

I         27   P61R, R273, P93R, 95C1R, P91R,    P93R, P69R, P87R,
                 P107RP, P69R, 3376R, P110R,       PI 15R, NDLR2
                 P87R, P89R, P75R, P94R,
                 P115R, P119R, P124R, NDLR2,
                 44B, 234B, 11B, 47B, 48B,
                 49B, 52B, 36B, RCR8297,
                 RHA297
II        5    P107[RP.sub.1], NDLR1,395B,       P107[RP.sub.1]
                 45B, 53B
III       3    P121R, 10B, 304B                  P121R
IV        2    P111R, P112R                      P111R
V         3    P100R, 40B, 50B                   40B, 50B
VI        1    7-1B                              7-IB

Table 5. Association divergence between and among clusters

      5a. Inter and intra cluster distance
       I      II    III     IV     V      VI

I     2.77   3.05   3.01   5.19   4.17   5.50
II           2.59   4.18   4.41   5.05   6.16
III                 1.96   5.58   5.29   6.13
IV                         2.15   7.16   6.97
V                                 2.18   7.04
VI                                       0.00

      5b. Variability of morphophysiological parameters (mean value)
       EV     CT      PS     LAI     LWP     DF       DM

I     2.30   22.40   0.78   0.50    -2.35   63.22   91.19
II    4.00   21.53   0.65   0.70    -2.71   69.23   95.46
III   2.70   18.47   0.81   1.60    -2.67   63.45   90.15
IV    2.30   19.53   0.77   1.70    -2.80   75.89   92.44
V     3.00   21.57   0.78   1.20    -2.83   61.49   98.16
VI    4.30   26.96   0.64   0.350   -2.61   66.58   91.58

      5b. Variability of morphophysiological parameters (mean value)
        PH       HD      SY      SW      OC

I     127.15   11.89    22.40   7.31    43.90
II    146.15   13.00    26.50   10.92   40.80
III   128.26   14.20    44.22   6.04    37.60
IV    207.45   12.63    32.11   7.83    32.90
V     113.19   15.31    26.89   12.80   44.90
VI    127.92   16.33    23.10   0.95    38.04

Table 6. Promising genotypes for various levels of water stress

Stress Levels                  Stress Resistant Genotypes
                         Cytoplasmic Male          Restorer Line
                        Sterile/maintainer
                               line

At normal rainfall           304 A/B            P87R, P89R, P107RP2,
                                                     P61R, P69R
Stress at button and      234 A/B, 40A/B        P75R, P107RP2, P93R
  soft dough stage
Stress at flowering           11A/B           P89R, 3376R, P91R, P94R
  and hard dough
  stage
Stress at anthesis        40A/B, 304A/B              P69R, P93R
  completition stage

Fig. 2. Contribution of parameters towards total
divergence

HD      4%
SY      5%
SW      11%
OC      12%

PH      9%
DM      1%
DF      2%
LWP     6%
LAI     19%
PS      10%
CT      3%
EV      18%
Other   32%

Note: Table made from bar graph.
COPYRIGHT 2016 Oriental Scientific Publishing Company
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2016 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Kumar, Prafull; Dhillon, S.K.; Sao, Abhinav; Thakur, A.K.; Kumari, Poonam; Kanwar, R.R.; Patel, R.K.
Publication:Journal of Pure and Applied Microbiology
Article Type:Report
Date:Sep 1, 2016
Words:10047
Previous Article:Characterization and plant growth promoting aspects of a novel phosphate solubilizing brown sarson endophyte Pseudomonas fluorescens strain smppsap5...
Next Article:Eubacterial diversity and Oxalate Metabolizing Bacterial Species (OMBS) reflect oxalate metabolism potential in Odontotermes gut.
Topics:

Terms of use | Privacy policy | Copyright © 2020 Farlex, Inc. | Feedback | For webmasters