Variability analysis for yield and yield attributes of bread wheat under salt affected condition.

Variability analysis for yield and yield attributes of bread wheat under salt affected condition

S. Dharmendra and K. N. Singh

Division of Crop Improvement

Central Soil SalinityResearch Institute, Karnal-132001, Haryana, India

Corresponding Author: S. K. Singh

E-mail: dsingh4678@rediffmail.com; dsingh4678@gmail.com

Abstract

Phenotypic and genotypic coefficient of variation (PCV and GCV), heritability, genetic advance (GA), correlation and path coefficient analysis for 10 characters were estimated in 20 genotypes of bread wheat (Triticum aestivum L). On pooled over environments high estimates of PCV, GCV, heritability and GA indicated scope for improvement through simple selection for grain-yield component namely grain per spike, grain yield per plant, plant height followed by 1000-grain weight. However, there was little variability and scope for selection in the materials for days to 50 % heading, days to maturity and germination percent. The estimates of correlation coefficient indicated that days to maturity, plant height, spike length, spikelets per spike, tillers per plant, grains per spike and 100-grain weight were positively correlated with grain yield. Considering the effects of each character on grain yield, spikelets per spike had highest positive direct effect followed by tillers per plant, days to maturity and plant height. This suggests that selection for these component characters can help in improvement in yield in bread wheat under different salt stress condition.

Key words: wheat, variation, correlation and path analysis

Introduction

A considering portion of irrigated land resources in arid and semi-arid regions of the world including India where, a large area has been rendered agriculturally unproductive due to high concentration of salts in root zone. According to Bhargava (1998), 10 million hectares of land in India is salt affected. For a tolerant line of bread wheat, one must be aware of crop genetics and physiology and develop an efficient screening system based on stable selection criteria. Development of salt tolerance genotypes/ cultivars is a possible approach to utilize wasteland (Bernstein 1995). The problem of soil salinity occurs frequently in irrigated area of the world (Shannon 2001). Keeping these things in a view, any breeding program aiming for the improvement of wheat must involve assembling, or generation of the improvement of wheat must be thereafter, tested in successive years for their genetic makeup for different characters of economic importance. Efficiency of selection for higher yield depends upon the knowledge of the trait components and their interaction with grain yield. This requires information about nature of magnitude of variability in base population and association of yield components with grain yield. There are many reports on genetic variability and characters association analysis in wheat but quire deficient the study under salinity stress (Kumar et al. 1986; Prakash and Sastry 1999; Dhaual et al. 2003).

Materials and Method

Twenty genotypes of bread wheat were evaluated in randomized complete block design with 3 replication in Microplot at Central Soil Salinity Research Institute, Karnal 132001 (Haryana). Each genotype was grown in a single rows of 1 meter with plant distances 5 cm and row to row distances 23 cm apart. Recommended doses of fertilizer and irrigation were applied to raise a good crop. Five competitive plants were randomly selected from the middle row of each experimental plot for recorded observation on quantitative character on plant basis, while days to 50% heading and days to maturity were recorded on plot basis. Details of environments are as follow: 1) Normal (pH2-8.5), 2) Saline (ECe-5.9ds/m), 3) Sodic low (pH2-9.2) and 4) Sodic high (pH2-9.4). The variance components, genotypic coefficient of variation and genetic advance were determined as suggested by Burton and De-Vane (1953) and Johnson et al. (1955). Phenotypic and genetic correlation coefficient were computed according to the formula of Miller et al. (1958). Direct and indirect path coefficients were calculated as described by Dewey and Lu (1959).

Results and Discussion

Genetic variation:

The variation displayed by the ten characters in this study is shown in Table1. Genotypic differences in most of the characters were significant at 10%, 5% and 1% levels of probability. The difference in grain yield, tillers per plant, spike length, spikelets per spike and 1000-grain weight were significant only in 10 % levels of probability. The highest coefficient of variation was shown by grain yield per plant followed by grains per spike; spikelets per spike, spike length and germination percent (Ehdaie and Waines 1998; Dhonde et al. 2000). The least value was shown by days to maturity followed by days to 50% heading, plant height and 1000-grain weight. The phenotypic and genotypic coefficient of variation (PCV and GCV) estimates of the component of variance, broad sense heritability and genetic advance are shown in Table2. The PCV was generally higher than the GCV for all the characters, but in many cases, the one value differed only slightly. The highest values were shown by grain-yield components namely grain per spike, grain yield per plant, plant height followed by 1000-grain weight. The heritability estimates ranged from 57.88 to 96.75 for germination percent and plant height respectively. High heritability estimates were also shown for days 50% heading, grains per spike, 1000-grain weight, spikelets per spike, spike length, tillers per plant and to maturity. Low estimates were given for germination percent and grain yield per plant (Imbrahim and quick 2001).

The expected genetic advance, expressed as a percentage of mean, varied from 2.04 for days to maturity to grains per spike (29.64). Relatively very low values were shown in germination percent, spikelets per spike, days to 50% heading. Comparatively, high expected genetic advance were observed for plant height, tillers per plant, grain yield per plant and 1000-grain weight (Sharma and Garg 2002).

Correlation between characters:

The phenotypic and genotypic correlation coefficients among the various characters are presented in Table3. In most instances, there was a close agreement between phenotypic and genotypic correlation; while in other cases, the differences were high, signifying the importance of the environmental effects in estimating these parameters. Thought the remainder of this section, references will be made only to phenotypic correlations between various characters. The developmental characters, namely germination percent had positive and highly significant association with days to maturity, plant height and was negatively insignificantly correlated with grain per spike while days to 50% heading had positive and significant correlated with days to maturity, spikelets per spike, grains per spike and was negatively significantly associated with 1000-grain weight. Days to maturity had negative and significant association with 1000-grain weight, spike length and yield per plant while plant height had positive and highly significantly correlated with tillers per plant, 1000-grain weight and grain yield per plant. Spike length showed positive significant association with grains per spike, spikelets per spike and was negatively significantly correlated with tillers per plant while spikelets per spike had positive and significant association grains per spike and negatively insignificantly interrelated with tillers per plant, 1000-grain weight and grain yield per plant, but tillers per plant showed positive and significant association with 1000-grain weight, grain yield per plant and negatively significant correlated with grains per spike. Grains per spike had negatively significant association with 1000-grain weight but a positive and significant interrelated with grain yield per plant also reported in Kumar et al. (1986) and Dhaual et al. (2003).

Path –coefficient analysis:

The genetic correlations were analyzed further by the path-coefficient technique. This technique involves a method of partitioning the correlation coefficient into direct effect and indirect effects via alternate characters or pathways. Grain yield being the complex outcome of different characters was considered as the resultant variable and germination percent, days 50 % heading, days to maturity, plant height spike length, spikelets per spike, tillers per plant and grains per spike as causal variables. The direct and indirect effect of the nine grain yield related characters are shown in Table4.

Considering the effect of each characters on grain yield, spikelets per spike had highest positive (3.718) direct followed by tillers per plant (1.204), days to maturity (0.680) and plant height (0.516). It is interesting to note that indirect effect via spikelets per spike was also higher when compared with any other indirect effect which is in agreement with the observation reported by Berwal et al. (1997), Jalam et al. (1997), Singh et al. (1998), Kumar and Sastry (1999). Days to 50 % heading showed maximum (1.671) indirect effect on grain yield via spikelets per spike followed by grain per spike (2.590) and spike length.

References:

Bernstein L (1995) Effect of salinity and sodicity on plant. Ann Rev Phytopathol 13: 295-312.

Berwal OP, Rana UPS, Yadava PK (1997) Association analysis for yield and its components under high and low input environments in a group diallel involving genotype of different height in wheat (Triticum aestivum L.em. Thell.). Crop Res 13: 365-368.

Bhargava (1998) Salt affect soil of India, A Sources of book, Oxford and IBH. Publishing Company, NewDelhi, pp. 261.

Burton GW, De Van EH (1953) Estimating heritability in tall fescue fescue (Festuca arundinacea L) from replicated clonal material. Agron J 45: 478-481.

Dewey DR, Lu KH (1959) A correlation and path coefficient analysis of component of crested wheatgrass seed production. Agron J 51: 515-518.

Dhaual LS, Sastry EVD, Jakhar ML (2003) Character association in wheat (Triticum aestivum L) grown under normal and saline conditions. Crop Improv 30: 95-98.

Dhonde SR, Kute NS, Kanawde DG, Sarode ND (2000) Variability and Character association in wheat (Triticum aestivum L.). Agric Sci Digest 20: 99-101.

Ehdaie B, Waines JG (1998) Genetic variation, heritability and path analysis in landraces of bread wheat from Southwestern Iran. Euphytica 41: 183-190.

Imbrahim AMH, Quick JS (2001) Heritability of heat tolerance in winter and spring wheat. Crop Sci 41: 1401-1405.

Jalam RS, Tandon JP, Singh M (1997) Coreelation studies in tall versus dwarf population of bread wheat (Triticum aestivum L). Indian J Agric Res 31:19-22.

Johnson HW, Robinson HF, Comstock RE (1955) Estimates of genetic and environmental variability in soybean. Agron J 47: 314-318.

Kumar D, Sharma SC, Gupta SC (1986) Correlation and path studies in wheat under normal and saline condition. Wheat Inf Serv 61/62: 64-67.

Kumar V, Sastry EVD (1999) Correlation and character association in wheat under moderate salinity. Agric Sci Digest 19: 175-178.

Miller PA, Williams JC, Robinson HF, Comstock RE (1958) Estimates of genetic and environmental variances and covariances in upland cotton and their implications in selection. Agron J 50: 126-131.

Shannon MC (2001) Breeding, selection and the genetics of salt tolerance. In: Staple RC, Toeniessen GA (eds), Salt tolerance in plant - Strategis for crop Improvement. Wiley, New York, USA pp. 231-254.

Sharma AK, Garg DK (2002) Genetic Variability in wheat (Triticum aestivum L) crosses under different normal and saline environment. Annals Agric Res 23: 497-499.

Singh RP, Garg DK, Sharma PC (1998) Character association in wheat (Triticum aestivum L). Indian J Agric Res 58: 219-222.