Genotype Selection from Azide-Induced Rice Mutants Using Multitrait Genotype–Ideotype Distance Index (MGIDI): Unveiling Promising Variants for Yield Improvement

• Published in: Advances in agriculture (Hindawi Publishing Corporation) Vol. 2024
• Main Authors: S. M. Abdullah Al Mamun, Nasrin Akter Ivy, Mohammad Ashik Iqbal Khan, Sayda Rehana, Mst. Sabiha Sultana, Sanjoy Kumar Adhikary, Md. Monirul Islam
• Format: Journal Article
• Language: English
• Published: Hindawi Limited 01.01.2024
• ISSN: 2314-7539
• DOI: 10.1155/2024/5719580

Development of high-yielding rice (Oryza sativa L.) is a crucial need for succeeding food security that needs the presence of great genetic variability to be used in breeding programs. Creating new variants through sodium azide mutagenesis can be a better alternative in advancing plant breeding issues. The generation and characterization of mutants represent an effective method for choosing genotypes with desired attributes. In this study, we focused on inducing mutations in the genetic base of a mega rice variety (BRRI dhan28) using sodium azide, evaluating the genetic diversity of the mutants, and identifying promising genotypes among the mutants using quantitative trait analysis and genetic criteria. The mutants exhibited substantial variation, as evidenced by descriptive statistics and analysis of variance. The estimated heritability and genetic advance indicated that nearly all traits had a high level of heritability and followed a complex pattern of inheritance. The strong correlations observed between grain yield and flag leaf length, branch panicle−1, grain panicle−1, 100-grain weight, straw yield hill−1, and harvest index indicate that prioritizing these traits during selection could substantially improve other desirable characteristics. Additionally, we employed the principal component analysis which revealed that the first two components collectively accounted for 32.16% of the total variation, providing essential information about the genetic relatedness of the mutants. The Multitrait Genotype–Ideotype Distance Index (MGIDI) analysis revealed that out of 100 mutants, only eight exhibited noteworthy performance. These findings provide insights into the efficiency of azide in creating genetic variations in rice traits and offer valuable resources for future breeding programs aimed at developing high-performing rice varieties.