Exploration of genetic variability in Garcinia [<i>Garcinia gummi-gutta</i> L.(Robson)] germplasm based on growth, yield and quality traits

Abstract

Eleven Garcinia germplasm along with local check of Pechiparai were evaluated and underwent principal component analysis to assess genetic divergence and variation patterns during 2019 to 2022. The first two principal components, contributing significant Eigen values, explained 71.20% of the total variability. The Acc. Gg 9 was the top performer, exhibiting favourable yield and growth traits with lower pest and disease incidence, high biochemical compounds viz., hydroxy citric acid and tartaric acid compared to local check. Cluster analysis revealed four major clusters, offering diversity for breeding programs. Correlation studies highlighted traits such as number of fruits per tree, rind thickness, and tartaric acid showing significant positive correlations with yield per tree. Selection based on identified key traits was deemed crucial for enhancing effectiveness. Additionally, DNA fingerprinting analysis indicated the potential use of RAPD markers (OPA03570) for differentiating Kudampuli cultivar PPI (K) 1 from the local check. Overall, the present investigation provides insights into optimizing Garcinia breeding programs, emphasizing trait-based selection and DNA fingerprinting for varietal differentiation.