Genetic variability, association and path analysis for yield and fruit quality components in yellow- berried nightshade (Solanum surattense)
A study was conducted to investigate the selection criteria in 54 kantakari accessions based on 14 morphological and qualitative traits employing correlation, path analysis, principal component analysis and cluster analysis. The traits viz., plant spread (N-S), plant spread (E-W), number of branches per plant, number of flower clusters per plant, number of berries, fresh berry yield per plant, dry berry yield per plant, dry berry yield per hectare, total proteins, total phenols, total flavonoid content, total antioxidant activity, FRAP activity and solasodine were recorded. For seven quantitative attributes, simple descriptive statistics revealed a normal distribution. Plant spread (N-S) (1.309), fresh berry production per plant (0.751), dry berry yield per plant (0.808), dry berry yield per hectare (0.816) and total flavonoid content (1.215) were all significant and showed positive skewnesses. Plant spread, branches per plant, flower clusters per plant, number of berries per plant, fresh berry yield per plant, total flavonoid content and total proteins all exhibited highly positive significant correlations with dry berry yield per plant. The quantity of berries per plant, total protein content, total flavonoid content and fresh berry yield per plant all showed a significant direct effect on yield. Quantity of berries per plant and fresh berry yield revealed as the primary incidental variables for positive or negative correlation of a number of features with dry berry yield per plant. Principal component analysis revealed that the first five components with Eigen values greater than one accounted for a maximum of 74.32 percent of the variability. Number of berries per plant (0.901), fresh berry yield per plant (0.938), dry berry yield per plant (0.962), and dry berry yield per hectare were the attributes contributing to the most variance in PC1, which was responsible for 26.97% of the overall variation (0.964). The accessions were divided into two main clusters using the Wards method of hierarchical cluster analysis. Cluster II contributed more significantly to berry quality and solasodine content than Cluster I, which comprised of high yielding accessions. To effectively exploit promising genotypes in future breeding programmes, it would be advantageous to categorise kantakari accessions based on numerous yield and quality parameters.
Keywords: Variability, correlation, path, Solanum surattense
Genetic variability, association and path analysis for yield and fruit quality components in yellow- berried nightshade Solanum surattense. 2023. Electronic Journal of Plant Breeding, 14 2, 419-428. Retrieved from https://ejplantbreeding.org/index.php/EJPB/article/view/4701
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