Genetic Association and Path Coefficient Analysis in rice (Oryza sativa L.) Genotype

The experiment was conducted in a Randomized Block Design with three replications during the Kharif season 2023 at Field experimentation centre, Department of Genetics and Plant Breeding, Naini Agriculture Institute, Sam Higginbottom University of Agriculture, Technology and Sciences, Naini, Prayagraj, U.P. the plant-to-plant distance was 20 cm and row to row distance was 15 cm. The data were recorded from randomly selected five plants for each genotypes for each replications for thirteen characters viz. days to 50% flowering, days to maturity, plant height (cm), flag leaf length (cm), flag leaf width (cm), number of tillers per hill, number of panicles per hill, panicle length (cm), spikelets per panicle, biomass (g), harvest index (%), test weight (g), and grain yield per hill (g). From the present investigation, it is concluded that analysis of variance showed significant variation among different genotypes for all characters studied. Positive and significant correlation was observed for plant height, flag leaf length, flag leaf width, spikelets per panicle, biomass, test weight and harvest index with grain yield per hill at genotypic and phenotypic levels. Days to maturity, number of panicles per hill, biomass, harvest index, test weight and flag leaf width exhibited direct positive effect at phenotypic level. This indicated that grain yield was mainly a product of direct and indirect effects of the above attributing characters and priority should be given to these characters during selection for improvement in rice.

Authors

Publication Details

Journal
International Journal of Science and Research (IJSR)
Published
2025-06-18
DOI
https://doi.org/10.21275/sr25614200155
Primary Topic
Rice Cultivation and Yield Improvement
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Genetic Association and Path Coefficient Analysis in rice (Oryza sativa L.) Genotype

Gera Roopa Lavanya, S. Nandi, x Mayank
International Journal of Science and Research (IJSR)
Rice Cultivation and Yield Improvement
article

Genetic Association and Path Coefficient Analysis in rice (Oryza sativa L.) Genotype

Gera Roopa Lavanya, S. Nandi, x Mayank
article en

Abstract

The experiment was conducted in a Randomized Block Design with three replications during the Kharif season 2023 at Field experimentation centre, Department of Genetics and Plant Breeding, Naini Agriculture Institute, Sam Higginbottom University of Agriculture, Technology and Sciences, Naini, Prayagraj, U.P. the plant-to-plant distance was 20 cm and row to row distance was 15 cm. The data were recorded from randomly selected five plants for each genotypes for each replications for thirteen characters viz. days to 50% flowering, days to maturity, plant height (cm), flag leaf length (cm), flag leaf width (cm), number of tillers per hill, number of panicles per hill, panicle length (cm), spikelets per panicle, biomass (g), harvest index (%), test weight (g), and grain yield per hill (g). From the present investigation, it is concluded that analysis of variance showed significant variation among different genotypes for all characters studied. Positive and significant correlation was observed for plant height, flag leaf length, flag leaf width, spikelets per panicle, biomass, test weight and harvest index with grain yield per hill at genotypic and phenotypic levels. Days to maturity, number of panicles per hill, biomass, harvest index, test weight and flag leaf width exhibited direct positive effect at phenotypic level. This indicated that grain yield was mainly a product of direct and indirect effects of the above attributing characters and priority should be given to these characters during selection for improvement in rice.

International Journal of Science and Research (IJSR)
Zero hunger
Openalex Percentile: Top 90%
Rice Cultivation and Yield Improvement
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.