Genetic variability, association and diversity analysis of yield and its component traits in rice (Oryza sativa) germplasm

VAIBHAV  PATHAK; C H  PRASUNA; B  UMAKANTH; K  SUREKHA; L V  SUBBARAO; G  PADMAVATHI

doi:10.56093/ijas.v94i7.146835

Authors

VAIBHAV PATHAK ICAR-Indian Institute of Rice Research, Hyderabad, Telangana 500 030, India
C H PRASUNA ICAR-Indian Institute of Rice Research, Hyderabad, Telangana 500 030, India
B UMAKANTH ICAR-Indian Institute of Rice Research, Hyderabad, Telangana 500 030, India
K SUREKHA ICAR-Indian Institute of Rice Research, Hyderabad, Telangana 500 030, India
L V SUBBARAO ICAR-Indian Institute of Rice Research, Hyderabad, Telangana 500 030, India
G PADMAVATHI ICAR-Indian Institute of Rice Research, Hyderabad, Telangana 500 030, India

https://doi.org/10.56093/ijas.v94i7.146835

Keywords:

Correlation, Genetic divergence, Genetic variability, Heritability, Rice

Abstract

An experiment was conducted during winter (rabi) season of 2022 at ICAR-Indian Institute of Rice Research, Hyderabad, Telangana to evaluate extent of genetic variability, heritability, diversity and the relationship between yield and its component traits in a collection of 60 rice germplasm accessions. Results showed that germplasm accessions exhibited ample genetic variability and diversity for yield traits. Based on per se performance, inter crosses between the genotypes IC458483 with high grain yield, IC210775 with more panicle length, IC75919 with high 100-grain weight, IC75980 with more productive tillers and IC75965 with high protein content could produce positive transgressive segregants for improving respective traits. Plant height, total and effective tillers, grain yield and 100-grain weight traits which exhibited the highest heritability and genetic advance could be vital for selection in hybridization programmes. Crossing among genotypes of diverse clusters specifically VI, VII and VIII is suggested as this could create a broad variation useful for selecting genotypes with both high yield and long panicles.

Downloads

Download data is not yet available.

References

Allard R W. 1960. Principles of Plant Breeding, 1st edn. John Wiley and sons Inc, New York, USA.

Banumati S, Manimaran R, Sheeba A, Manivannan N, Ramya B, Kumar D and Ramasubramanian G V. 2010. Genetic diversity analysis of rice germplasm lines for yield attributing traits. Electronic Journal of Plant Breeding 1(4): 500–04.

Bhargavi M, Shanthi P, Reddy V L N, Mohan Reddy D and Ravindra Reddy B. 2021. Estimates of genetic variability, heritability, and genetic advance for grain yield and other yield attributing traits in rice (Oryza sativa L.). The Pharma Innovation Journal 10(5): 507–11.

Boranayaka M B, Lokesha R, Latha H C and Mahanth Shivayogayya

K. 2020. Genetic variability, character association, frequency and normality distribution studies for F2 population of BPT- 5204 × WAB-450 cross in rice (Oryza sativa L.) International Journal of Current Microbiology and Applied Science 9(5): 278–95.

Brar D S and Khush G S. 2002. Transfering genes from wild species into rice. Quantitative Genetics, Genomics and Plant Breeding, pp. 197–217. M S Kang (Ed). A CABI Publication, Wallingford, UK.

Burton G W. 1952. Quantitative inheritance in grasses. (In) Proceedings of International Grassland Congress 1: 277–83.

FAO. 2022. Food Inspection. Food safety and quality. FAO, Rome, Italy.

Huang M, Zhang H, Zhao C, Chen G and Zou Y. 2019. Amino acid content in rice grains is affected by high temperature during the early grain-filling period. Scientific Reporter 9(1): 2700.

Jackson P E, Krol J, Heckenberg A L, Mientijes M and Staal W. 1991. Determination of total nitrogen in food, environmental and other samples by ion chromatography after kjeldahl digestion. Journal of Chromatography 546: 405–10.

Johnson H N, Robinson H F and Comstock R E. 1955. Estimates of genetic and environmental variability in soybean. Agronomy Journal 27: 314–18.

Kiran A, Sharma D J, Subbarao L V, Gireesh C and Agrawal A P. 2023. Correlation coefficient and path coefficient analysis for yield, yield attributing traits and nutritional traits in rice genotypes. The Pharma Innovation Journal 12(2): 1978–83.

Krishnaveni B and Rani N S. 2015. Association of grain yield with quality characteristics and other yield components in rice. Oryza 43(4): 320–22.

Kritika Williams, Aman Mishra, Akansha Verma, B G Suresh and Lavanya G R. 2021. Genetic variability and correlation studies for yield and yield related traits in rice (Oryza sativa L.) genotypes. International Journal of Current Microbiology and Applied Science 10(1): 752–64.

Mahalanobis P C. 1936. On the generalized distance in statistics. Proceedings of the National Institute of Sciences of India 2: 49–55.

Panse V G and Sukhatme P V. 1985. Statistical Methods for Agricultural Workers. ICAR, New Delhi.

R Development Core Team. 2020. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Available at: http://www.R-project.org Rao C R. 1952. Advanced Statistical Methods in Biometrical Research. John Wiley and Sons, New York, USA.

Srujana G, Suresh B G, Lavanya G R, Jalandhar Ram B and Sumanth V. 2017. Studies on genetic variability, heritability and genetic advance for yield and quality components in rice (Oryza sativa L.). Journal of Pharmacognosy and Phytochemistry 6(4): 564–66.

Supriya K, Vanisri S, Jagadeeswar R and M Sreedhar. 2017. Genetic diversity for yield: Its contributing characters in rice (Oryza sativa). International Journal of Current Microbiology and Applied Sciences 6(10): 2424–28.

Venkata Lakshmi M, Suneetha Y, Yugandhar G and Venkata Lakshmi N. 2014. Correlation studies in rice (Oryza sativa L.). International Journal of Genetic Engineering and Biotechnology 5(2): 121–26.

Yadav R, Rajpoot P, Verma O P, Singh P K, Singh P and Pathak V. 2017. Genetic variability, heritability and genetic advance in rice (Oryza sativa L.) for grain yield and its contributing attributes under sodic soil. Journal of Pharmacognosy and Phytochemistry 6(5): 1294–96.