Quantitative Trait Loci (qtl) Mapping for Drought Tolerance and Yield in Nigerian Groundnut (arachis Hypogaea) Varieties
Year: 2024
Type: article
Abstract: This study investigates the genetic basis of drought tolerance and yield in Nigerian groundnut (Arachis hypogaea) varieties through Quantitative Trait Loci (QTL) mapping and phenotypic analysis. Addressing the critical need for improved drought tolerance, it employs modern molecular breeding techniques to identify key genomic regions associated with resilience and productivity under water stress, supporting sustainable agriculture in Nigeria's challenging climatic conditions. A diverse panel of groundnut genotypes was evaluated under drought-stressed and well-watered conditions across multiple locations in Nigeria. Significant differences were observed in wilting scores, root lengths, and pod yields among the genotypes, with local landrace G3 and improved variety V2 demonstrating superior drought tolerance. Specifically, G3 maintained a pod yield of 3200 kg/ha under drought stress, while the exotic variety E1 yielded only 1900 kg/ha. QTL mapping identified four major QTLs significantly associated with drought tolerance traits: qDT1 (root length), qDT2 (stomatal conductance), and qYLD1 (pod yield under drought), explaining 35%, 28%, and 40% of the phenotypic variance, respectively. High heritability estimates for root length (0.75), wilting score (0.68), and pod yield under drought (0.62) suggest that these traits can be effectively improved through selection. The positive correlations between root length and pod yield (r = 0.58) and relative water content (RWC) with stomatal conductance (r = 0.62) further indicate that selecting for these traits could enhance yield stability under drought conditions. These findings underscore the potential of utilizing QTL mapping and marker-assisted selection to develop drought-resistant, high-yielding groundnut varieties tailored to Nigeria's diverse agro-climatic conditions, contributing to...
Source: FUDMA Journal of Sciences
Language: English
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W4410948843