What question did this study set out to answer?

This study aims to identify elite rice lines with superior breeding values for grain yield under irrigation systems.

February 8, 2026Open Access

Identification of elite rice lines with better breeding values using genomic prediction and multi-trait genotype ideotype distance index (MGIDI) for grain yield under irrigation cropping system

Key Points

This study aims to identify elite rice lines with superior breeding values for grain yield under irrigation systems.
Evaluated 200 advanced breeding lines and checks during two growing seasons.
Utilized alpha lattice design with two replications.
Performed heritability and genetic advance analyses.
Calculated correlation coefficients for yield-related traits.
Conducted principal component analysis to assess variability.
Identified significant genetic variation among the rice lines.
Calculations revealed positive relationships between yield and panicle length, spikelet fertility, days to maturity, and days to flowering.
Observed total genetic gains of 28.51% and 25.86% for respective growing seasons.
Selected several rice genotypes as superior for parental breeding with high genomic estimated breeding values.
Achieved maximum yields of 8.67 t/ha in the 2023 season, outperforming standard checks.

Abstract

For a rice breeding program to produce the desired genotypes, parental selection is the most important factor. To select elite parental materials, this study evaluated 200 International Rice Research Institute (IRRI) developed advanced breeding lines during 2022 Wet Season (WS-T. Aman) and 2023 Dry Season (DS-Boro) along with two sets of check (10 global and 6 different local for each season) using an alpha lattice design with two replications in the research field of Gazipur Agricultural University, Gazipur-1706. Among the breeding lines, significant genetic variation was found and according to heritability and genetic advance analysis, additive gene action controls plant height (PH), panicle length (PL), spikelet fertility (SF), thousand grain weight (TGW), and grain yield (t/ha) (GYTH). Correlation coefficients revealed that in both season yield has a positive relationship with panicle length (0.20**, 0.35***), spikelet fertility (0.19**, 0.23***), days to maturity (DTM) (0.37***, 0.24***), and days to 50% flowering (DFF) (0.34***, 0.29***). In this study, Principal Component Analysis (PCA) revealed 4 & 3 PCs in 2022WS and 2023DS contributing to 66.90% & 61.90% of total variability with eigenvalues>1. The Multi-Trait Genotype–Ideotype Distance Index (MGIDI) analysis results a total genetic gain of 28.51% & 25.86% in 2022WS & 2023DS and identified IR19A8066, IR19A8052, IR19A7440, IR19A9061, and IR19A9054 genotypes as valuable resources for developing recombinant populations, aligning with sustainable and effective crop improvement strategies. For parental selection, IR19A8054, IR19A8052, IR19A7501, IR19A8047, IR19A8066, IR19A7531, IR19A7523, IR19A7541, IR19A7510 with Genomic Estimated Breeding Value (GEBV)>0.50 for yield are preferred. The maximum yield (5.34 t/ha) in 2022WS was generated by check RABI dhan1, while 5.12 t/ha was produced by IR19A7664, and more than 4.50 t/ha was produced by IR19A9054, IR19A7408, and IR19A7440. When compared to check BRRI dhan89 (7.97 t/ha), IR19A7339 delivered the highest in 2023DS (8.67 t/ha), followed by IR19A7510, IR19A7523, IR19A8047, and IR19A8066 (>8 t/ha). With positive GEBVs of 0.19, 0.32, and 0.62, respectively, IR19A9054, IR19A9212, and IR19A8066 demonstrated superior yield in both rice growing seasons.

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Identification of elite rice lines with better breeding values using genomic prediction and multi-trait genotype ideotype distance index (MGIDI) for grain yield under irrigation cropping system

Key Points

Abstract

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