Genetic divergence studies for yield and quality traits in high protein landraces of rice (Oryza sativa L.)

Authors

DOI:

https://doi.org/10.14719/pst.2091

Keywords:

Genetic diversity, Grain yield, Landrace, Mahalanobis D2, Principal component analysis, Protein content quality characters, Rice

Abstract

The present study was undertaken to study the extent of genetic diversity in high protein rice landraces with respect to yield, yield components and quality characters. In this direction, 30 high protein rice landraces, collected from different parts of country by ICAR-Indian Institute of Rice Research (ICAR-IIRR), Hyderabad along with the high protein check, CR DHAN 310 were evaluated during Kharif 2021 at ICAR-IIRR farm located at International Crops Research Institute of Semi Arid Tropics (ICRISAT), Hyderabad. The study examined the genetic divergence of high protein rice cultures for yield, quality and nutritional parameters. Multivariate analysis techniques of Mahalanobis D2 and Principal Component Analysis (PCA) were used to estimate the genetic diversity in the experimental material. In Mahalanobis D2, the 31 high protein rice cultures were divided into six clusters. Cluster I had highest number of rice cultures (19), followed by Cluster III and V with five, four cultures, respectively. The clusters, II, IV, VI were mono-genotypic. It was discovered that grouping of these cultures into several clusters was random and was not related to geographical diversity. Inter-cluster distances between clusters V and VI were maximum. Cluster V had also exhibited higher intra-cluster distance. Further, Cluster VI had showed maximum yield plant-1, grains per panicle-1, zinc content and test weight, while, Cluster V had recorded high protein content. The greatest contribution to genetic divergence was recorded by yield plant-1 (21.60%), followed by iron (10.54%) and zinc content (9.54%). In Principal Component Analysis, the first five Principal Components (PCs) with eigen values >1 accounted for cumulative contribution of 67.69% to the total variability. The three traits, yield plant-1, iron content, and amylose content contributed the most to variability. The 2D scatter diagram exhibited 18 different clusters, out of which 11 clusters were mono-genotypic. Mahalanobis D2 Statistic and PCA concluded maximum genetic diversity between the landraces, JAK 248-3 and JAK 638 with JAK 611.

Downloads

Download data is not yet available.

References

Prasad RKK Suneetha Y and Srinivas T. Genetic diversity studies in rice (Oryza sativa L.). Electronic Journal of Plant Breeding. 2018; 9(4): 1335-1341. https://doi.org/10.5958/0975-928X.2018.00166.7

FAOSTAT. Food and Agricultural Organization of United Nation. 2005. Rome, Italy.

Gearing ME. Good as gold: Can golden rice and other biofortified crops prevent malnutrition. Science in the News, Harvard University. https://sitn.hms.harvard.edu/flash/2015/good-as-gold-can-golden-rice-and-other-biofortified-crops-prevent-malnutrition/

Sahu SK, Kumar SG, Bhat BV, Premarajan KC, Sarkar S, Roy G, Joseph N. Malnutrition among under-five children in India and strategies for control. Journal of natural science, biology, and medicine. 2015 Jan;6(1):18. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4367032/

Faizan U, Rouster AS. Nutrition and hydration requirements in children and adults. https://pubmed.ncbi.nlm.nih.gov/32965878/

Nitrayová S, Brestenský M, Patráš P. Comparison of two methods of protein quality evaluation in rice, rye and barley as food protein sources in human nutrition. Potravinarstvo. 2018 Jan 1;12(1). https://doi.org/10.5219/991

Hossain S, Haque M, Rahman J. Genetic variability, correlation and path coefficient analysis of morphological traits in some extinct local Aman rice (Oryza sativa L). Rice Research: Open Access. 2015 Dec 19. https://doi.org/ 10.4172/2375-4338.1000158.

Arunachalam V. 1981. Genetic distance in plant breeding. Indian Journal of genetics and plant breeding:226-236. https://www.scirp.org/(S(351jmbntvnsjt 1aadkposzje))/reference/ReferencesPapers.aspx?ReferenceID=1001247.

Panse VG, Sukhatme PV. Statistical methods for agricultural workers. Statistical methods for agricultural workers. 1954. https://www. cabdirect.org/cabdirect/abstract/19561604178

Mahalanobis PC. A statistical study at Chinese head measurement. Journal of Asiatic Society of Bengal. 1928. 25(3):301-77. https://www.scirp.org/(S(lz5 mqp453ed%20snp55rrgjct55))/reference/referencespapers.aspx?referenceid=2992694

Banfield CF. Multivariate analysis in genstat. Journal of Statistical Computation and Simulation.1978;6(3-4):211-22. https://doi.org/10.1080/00949657808810190.

Wilk’s SS. Criterian of generalization in the analysis of variance. Biometrical Journal. 1932; 24:471-484. https://doi.org/10.2307/2331979

Rao CR. Advanced Statistical Methods in Biometrical Research. John Wiley and

Sons Inc., New York. 1952; 236-272. https://www.scirp.org/(S(czeh 2tfqyw2orz553k1w0r45))/reference/ReferencesPapers.aspx?ReferenceID=1001255.

Singh RK and Chaudhary BD. Biometrical Methods in Quantitative Genetics Analysis. Kalyani Publishers. New Delhi. 1997; 215-218. https://www.scirp.org/(S(lz5mqp453edsnp55rrgjct55))/reference/ReferencesPapers.aspx?ReferenceID=1435674

Jackson JE. A user’s guide to principal components. John Wiley and Sons. 1991.New York. https://doi.org/10.1002/0471725331.

Ehrenberg ASC. Data Reduction Analysis and Interpreting Statistical Data. John Wiley and Sons Inc., New York. 1985; 24(1):54-56.

Sudeepthi K, Srinivas T, Ravikumar BNVSR JD, Nafeez Umar SK. Genetic divergence studies for yield and yield component traits in rice (Oryza sativa L.). Multilogic in science. 2020. 9: 415-8. https://www.ycjournal.net/ Multilogicinscience/ResearchPapers.aspx

Singh KS, Suneetha Y, Kumar GV, D Rao VS, Raja S, Srinivas T. Genetic divergence studies for yield and quality traits in coloured rice. Journal of Pharmacognosy and Phytochemistry. 2020;9(4):1234-40. https://doi.org/10. 22271/phyto.2020.v9.i4q.11906.

Sri Lakshmi M, Suneetha Y and Srinivas T. 2021. Genetic diversity analysis for grain yield and yield components in rice. International Journal of Chemical Studies. 2021;9(1):1386-1389. https://doi.org/10.22271/chemi.2021.v9.i1t.11416.

Karuppaiyan R, Kapoor C, Gopi R. Variability, heritability and genetic divergence in lowland rice genotypes under the mid-hills of Sikkim. Oryza. 2013:50(1):81-4. https://www.researchgate.net/publication/309033608_Variability_heritability_and_genetic_divergence_in_low_land_rice_genotype_under_the_mid_hills_of_Sikkim

Published

04-02-2023 — Updated on 01-04-2023

Versions

How to Cite

1.
Bhargavi B, Yadla S, Jukanti A kumar, Thati S. Genetic divergence studies for yield and quality traits in high protein landraces of rice (Oryza sativa L.). Plant Sci. Today [Internet]. 2023 Apr. 1 [cited 2024 May 14];10(2):195-204. Available from: https://horizonepublishing.com/journals/index.php/PST/article/view/2091

Issue

Section

Research Articles