ADDITIVE MAIN EFFECT AND MULTIPLICATIVE INTERACTION ANALYSIS FOR PRODUCTION TRAITS IN RICE RECOMBINANT INBRED LINES USING AMMI BIPLOT TECHNIQUE

Year 2023, , 213 - 220, 24.12.2023

Aziz Ur Rahman Faiz Ur Rehman , Syed Mehr Ali Shah Muhammad Ali Shah Syed Majid Rasheed

https://doi.org/10.17557/tjfc.1325433

Abstract

The experiment was performed to assess the performance of 87 rice recombinant inbred lines (RILs), identify
the productive environments and quantify genotype × environment interaction (GEI) effects on yield and yield
related traits across four locations of the Khyber Pakhtunkhwa Province in Pakistan between 2021 and 2022.
The pooled ANOVA showed significant differences of GEI for all traits. Across the studied environments, RIL
AUP-3 took minimum days to heading (139) and produced the highest grain yield (4.1 t ha-1). AUP-3 and AUP30 displayed the highest kernel number in panicle of 214 and 226, respectively. Based on AMMI1 and AMMI2
biplots, RIL AUP-3 was unanimously declared as the most stable and the highest yielding genotype. AMMI
biplot analysis cumulatively explained 55.3%, 46.3% and 52.1% of total variation due to GEI for days to
maturity, grains panicle-1 and grain yield, respectively. The AMMI biplot analysis confirmed the differential
response of genotypes across environments, suggesting environment-based expression of genes. The AMMI
biplot also manifested AUP-3 and AUP-30 as ideal genotypes for grains panicle-1 and grain yield, respectively.
The Peshawar (E-1 and E-5) and Mingora (E-2) were the most discriminating and representative environment
for grains panicle-1 and grain yield. Application of various stability models in this study identified AUP-3 and
AUP-30 as the most stable and widely adapted genotype for grain yield and its components. The AMMI analysis
identified genotypes both for specific and wide adaptation. Based on stability and yield performance, said
genotypes were identified with superior performance than check cultivars. Therefore, recommended for
commercialization. Also environments were clustered regardless of their geographical location, which revealed
unpredictable nature of agro-climatic conditions across four tested locations.

Keywords

Biplot technique, genotype by environment interaction, multi-environments, rice inbreed lines, yield related traits.

Supporting Institution

University of Agriculture Peshawar, Pakistan

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