Assessment of Genetic Variability and Heritability in Okra [Abelmoschus esculentus (L.) Moench.] Genotypes

AbstractOkra is a nutritionally and economically important crop, yet its genetic potential is underexploited due to limited knowledge of variability among genotypes. This study aimed to assess genetic variability, heritability, and genetic advance in okra to identify key traits for targeted improvement. This comprehensive analysis examined genetic variation across 25 okra genotypes, alongside the check variety Arka Anamika, to pinpoint advantageous characteristics for advanced breeding programs targeting yield optimization and quality enhancement. Executed during summer 2019 at Horticultural Research Centre (H.N.B. Garhwal University), the trial utilized a triple-replicated randomized complete block design (RCBD) to maximize experimental reliability. Statistical analysis of 15 agronomic and biochemical traits included evaluations of phenotypic/genotypic variation of coefficients (PCV/GCV), broad-sense heritability (h2) and genetic advancement metrics (GA, GAM). The key outcome revealed marked genetic differentiation in key characteristics like number of primary branches, total soluble solids content, seed yield per fruit, and physiological loss demonstrated high GCV/PCV ratios and high heritability with high genetic gains. These findings highlighted additive genetic effects, making these traits optimal for traditional phenotypic selection. Conversely, chlorophyll content, leaf length and petiole diameter showed moderate to low heritability and genetic gain, suggesting environmental susceptibility or epistatic genetic regulation that may necessitate biotechnological interventions like CRISPR-based editing or transcriptomic profiling to bypass traditional breeding constraints. The research underscored the untapped genetic reservoir within existing okra germplasm, offering an actionable framework for crop improvement. High-heritability traits warrant immediate selection protocols, while polygenic characteristics could benefit from integrated genomic selection models or haplotype-based breeding.