Genetic Analysis of Traits in Indian Mustard Using Additive-Dominance Model

The study investigates the genetic basis of key traits in Indian mustard (Brassica juncea) using the additive-dominance model, with a focus on genotype × environment interactions. Conducted over two Rabi seasons (2021-22 and 2022-23) at Sri Karan Narendra College of Agriculture, Rajasthan, the research involved ten genetically diverse mustard genotypes crossed in a 10 × 10 half-diallel mating design. The parents and F 1 hybrids were evaluated under three sowing conditions to simulate different environmental scenarios. Significant genotypic, environmental, and genotype × environment interactions were observed for various traits, including days to flowering, plant height, siliquae per plant, and seed yield per plant. Diallel analysis revealed the suitability of the additive-dominance model for several traits, with both additive and dominant genetic effects playing substantial roles. Dominance gene action predominated for most traits, with overdominance observed for plant height, seed yield, and siliqua length. Genetic diversity among parents was evident, with specific genotypes showing dominance for traits like early flowering, plant height, and seed yield. These findings provide valuable insights into the genetic architecture of mustard traits and offer strategies for improving yield, stress tolerance, and adaptability in mustard breeding programs, ensuring better productivity in varying environmental conditions.

Authors

Publication Details

Journal
Agriculture Association of Textile Chemical and Critical Reviews
Published
2025-03-01
DOI
https://doi.org/10.21276/aatccreview.2025.13.01.266
Primary Topic
Research in Cotton Cultivation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Genetic Analysis of Traits in Indian Mustard Using Additive-Dominance Model

Giovanni Mita, Deepak Gupta, Manisha Sharma, Anil Kumar et al.
Agriculture Association of Textile Chemical and Critical Reviews
Research in Cotton Cultivation
article

Genetic Analysis of Traits in Indian Mustard Using Additive-Dominance Model

Giovanni Mita, Deepak Gupta, Manisha Sharma, Anil Kumar, Anita Anita
article en

Abstract

The study investigates the genetic basis of key traits in Indian mustard (Brassica juncea) using the additive-dominance model, with a focus on genotype × environment interactions. Conducted over two Rabi seasons (2021-22 and 2022-23) at Sri Karan Narendra College of Agriculture, Rajasthan, the research involved ten genetically diverse mustard genotypes crossed in a 10 × 10 half-diallel mating design. The parents and F 1 hybrids were evaluated under three sowing conditions to simulate different environmental scenarios. Significant genotypic, environmental, and genotype × environment interactions were observed for various traits, including days to flowering, plant height, siliquae per plant, and seed yield per plant. Diallel analysis revealed the suitability of the additive-dominance model for several traits, with both additive and dominant genetic effects playing substantial roles. Dominance gene action predominated for most traits, with overdominance observed for plant height, seed yield, and siliqua length. Genetic diversity among parents was evident, with specific genotypes showing dominance for traits like early flowering, plant height, and seed yield. These findings provide valuable insights into the genetic architecture of mustard traits and offer strategies for improving yield, stress tolerance, and adaptability in mustard breeding programs, ensuring better productivity in varying environmental conditions.

Agriculture Association of Textile Chemical and Critical ReviewsVol. 13(1)
Openalex Percentile: Top 90%
Research in Cotton Cultivation
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.