Assessment and role of genetic diversity of component traits for improving grain yield and heat tolerance in bread wheat (Triticum aestivum)

ANKIT KUMAR; PRADEEP KUMAR; GYANENDRA SINGH

doi:10.56093/ijas.v89i7.91692

Authors

ANKIT KUMAR M Sc Student, Sardar Vallabhbhai Patel University of Agriculture & Technology, Meerut 250 110
PRADEEP KUMAR Senior Research Fellow, ICAR-Indian Institute of Wheat and Barley Research, Karnal 132 001
GYANENDRA SINGH Principal Scientist, ICAR-Indian Institute of Wheat & Barley Research, Karnal 132 001

https://doi.org/10.56093/ijas.v89i7.91692

Keywords:

Bread wheat, Genetic diversity, Genetic parameters, Grain yield, Multivariate analysis

Abstract

The present investigation was carried out in a randomized block design (RBD) with 20 diverse wheat (Triticum aestivum L.) genotypes grown under three environments i.e. 25th November, 2012 (Environment-I, timely sown), 24th December, 2012 (Environment-II, late sown) and 15th January 2013 (Environment-III, very late sown). The environment wise analysis of variance for grain yield and its contributing traits indicated highly significant differences among the genotypes for all the traits under study. High heritability along with high genetic advance and high coefficient of variation (PCV and GCV) for grain yield across three environments indicated substantial contribution of additive gene action in the expression of desirable traits and thus selection would be effective for genetic improvement of grain yield in wheat. On the basis of multivariate analysis, 20 genotypes were grouped into five clusters based on D2 value. The cluster V contained the maximum number of genotypes (6) in Environment-I,whereas cluster II included six genotypes in Environment-II, cluster IV included 07 genotypes in Environment-III and on pooled analysis basis cluster V had 07 genotypes. The highest inter cluster values were observed between cluster II and III (2690.75), followed by cluster I and II (2494.51), cluster II and V (1334.53), cluster III and V (730.74) in the first, second, third environments as well as pooled analysis basis, respectively, and thus genotypes included in these clusters showed wide genetic diversity and thus may be utilized in hybridization programme targeting wheat breeding for obtaining transgressive segregants to improve grain yield under varying environments. Based on the cluster mean analysis, genotype K 512 in E-I (timely sown) and E-II (late sown) while AAI 13 in E-II (late sown), E-III (vary late sown) and also in pooled analysis were rated better performing for multiple yield traits and these genotypes can be considered in breeding programme as well as for further study for developing superior wheat genotypes.

Downloads

Download data is not yet available.

References

Anonymous. 2018. Progress Report of all India Coordinated Wheat and Barley Improvement Project. Director’s Report. ICAR-Indian Institute of Wheat and Barley Research, Karnal, pp 1–5.

Burton G W and Vane de E H. 1953. Estimating heritability in tall fescue (Festuca arundinacea L.) from replicated clonal material. Agronomy Journal 45: 478–81. DOI: https://doi.org/10.2134/agronj1953.00021962004500100005x

Das B. 2014. Genetic diversity, variability and correlation studies of spike characters in bread wheat under boron deficient soil condition. Electronic Journal of Plant Breeding 5(1): 77–81.

Dhakar M R, Jat B L, Bairwa L N and Gupta J K. 2012.Genetic variability, heritability, genetic advance and genetic divergence in wheat (Triticum spp.). Environment & Ecology 30(4A): 1474–80.

Emeka C O, Christain U A, Michael I U and Francis C O. 2016. Germplasm evaluation of heat tolerance in bread wheat in Tel Hadya, Syria. Chilean Journal of Agricultural Research 76 (1): 9–17. DOI: https://doi.org/10.4067/S0718-58392016000100002

Johnson H W, Robinson H F and Comstock R E. 1955. Estimates of genetic and environmental variability in soybeans. Agronomy Journal 47(7): 314–8. DOI: https://doi.org/10.2134/agronj1955.00021962004700070009x

Kumar Pradeep, Singh Gyanendra, Kumar Sarvan, Kumar Anuj and Ojha Ashish. 2016. Genetic analysis of grain yield and its contributing traits for their implications in improvement of bread wheat cultivars. Journal of Applied and Natural Science 8(1): 350–7. DOI: https://doi.org/10.31018/jans.v8i1.799

Mahalanobis P C. 1936. On the generalized distance on statistics, a statistical study of Chinese head measurement. Journal of the Asiatic Society of Bengal (25): 301–7.

Panse V G and Sukhatme P V. 1969. Statistical Methods of Agricultural Workers, pp 381. ICAR Publication, New Delhi, India.

Rao C R. 1952. Advance Statistical Methods in Biometrical Research, p. 383. John Wiley and Sons Inc., New York.

Singh B N, Soni S K, Srivastava A and Yadav V K. 2012. Multivariate analysis to architecture model plant type for saline soil in bread wheat (Triticum aestivum L. em Thell.). Environment & Ecology 30(1): 179–82.

Singh Girnam, Kumar Pradeep, Kumar Ravi and Gangwar L K. 2018. Genetic diversity analysis for various morphological and quality traits in bread wheat (Triticum aestivum L.). Journal of Applied and Natural Science 10(1): 24–9. DOI: https://doi.org/10.31018/jans.v10i1.1572

Singh Gyanendra, Kulshreshtha N, Singh B N, Setter T L, Singh M K, Saharan M S, Tyagi B S, Verma Ajay and Sharma Indu. 2014. Germplasm characterization, association and clustering for salinity and waterlogging tolerance in bread wheat (Triticum aestivum). Indian Journal of Agricultural Sciences 84(9): 1102–10.

Singh M K, Sharma P K, Tyagi B S and Singh Gyanendra. 2013. Genetic analysis for morphological traits and protein content in bread wheat (Triticum aestivum L.) under normal and heat stress environments. Indian Journal of Genetics and Plant Breeding 3(3): 320–4. DOI: https://doi.org/10.5958/j.0975-6906.73.3.047

Spark D N. 1973. Euclidean cluster analysis. Algorithm A. 58. Applied Statistics (22): 126–30. DOI: https://doi.org/10.2307/2346321

Tewari R, Jaiswal J P, Gangwar R P and Singh P K. 2015. Genetic diversity analysis in exotic germplasm accessions of wheat (Triticum aestivum L.) by cluster analysis. Electronic Journal of Plant Breeding 6(4): 1111–7.

Verma P N, Singh B N, Singh G, Singh M K and Setter T L. 2014. Genetic diversity analysis for yield and other agronomic traits in bread wheat under water logged sodic soil condition. Journal of Wheat Research 6(1): 51–8.