Electronic Journal of Plant Breeding
Open Access
SCOPUS
  • Year: 2023
  • Volume: 14
  • Issue: 1

Genetic studies on false smut disease resistance and yield components in rice (Oryza sativa. L)

  • Author:
  • N. Ramya Selvi1, R. Saraswathi2,*, S. Geetha3, C. Gopalakrishnan4
  • Total Page Count: 11
  • Page Number: 96 to 106

1Department of Genetics and Plant Breeding, Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India

2Department of Plant Genetic Resources, Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India

3Department of Pulses, Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India

4Department of Plant Pathology, Centre for Plant Protection Studies, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India

*E-Mail: sarasrice2004@yahoo.co.in

Online published on 17 April, 2023.

Abstract

The present investigation was performed to explain the genetic variability and association parameters of twenty traits in 30 F1s involving six parents difering in resistance against false smut in rice. Breeding materials were evaluated at hotspot location viz., HREC, Gudalur. The ANOVA revealed signifcant diferences among the studied variables. Higher PCV over other coefcients of variation suggest the role of environment in trait expression. Disease related traits viz., NIP, NIT, NIGPa, PIT, PIGPa and agronomic traits viz., TNFPa, NCGPa, SSP, PH, HGW and SPY showed high magnitude of values for GCV, heritability and GAM indicating the role of additive gene action. Hence, selection of these traits may be efective. Correlation studies indicated that HGW and SPW showed positive signifcant association with SPY. Path analysis revealed that NIT, NIGPa, NIGP and PIP had negative direct efect and DFF, NPT, TNFPa, SSP, NSRPa and SPW had positive direct efect towards single plant yield.

Keywords

Rice, False smut resistance, Yield, Variability, Association analysis