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  • Title: Estimation of genetic variation in yield, its contributing characters and capsaicin content of Capsicum chinense Jacq. (ghost pepper) germplasm from Northeast India.
    Author: Baruah J, Munda S, Sarma N, Begum T, Pandey SK, Chanda SK, Sastry GN, Lal M.
    Journal: PeerJ; 2023; 11():e15521. PubMed ID: 37366425.
    Abstract:
    Capsicum chinense Jacq. (ghost pepper), a naturally occurring chili species of Northeast India is known throughout the world for its high pungency and a pleasant aroma. The economic importance is due to the high capsaicinoid levels, the main source for pharmaceutical industries. The present study focused on identifying important traits necessary for increasing the yield and pungency of ghost pepper and to determine the parameters for the selection of superior genotypes. A total of 120 genotypes with more than 1.2% capsaicin content (>1,92,000 Scoville Heat Unit, w/w on dry weight basis) collected from different northeast Indian regions were subjected to variability, divergence and correlation studies. Levene's homogeneity test of variance studied for three environments did not show significant deviation and so homogeneity of variance was reasonably met for analysis of variance study. Genotypic and phenotypic coefficient of variation was highest for fruit yield per plant (33.702, 36.200, respectively), followed by number of fruits per plant (29.583, 33.014, respectively) and capsaicin content (25.283, 26.362, respectively). The trait number of fruits per plant had maximum direct contribution to fruit yield per plant and the trait fruit yield per plant towards capsaicin content in the correlation study. High heritability with high genetic advance, which is the most favored selection criteria was observed for fruit yield per plant, number of fruits per plant, capsaicin content, fruit length and fruit girth. The genetic divergence study partitioned the genotypes into 20 clusters, where fruit yield per plant contributed maximum towards total divergence. Principal components analysis (PCA) studied to determine the largest contributor of variation showed 73.48% of the total variability, of which the PC1 and PC2 contributed 34.59% and 16.81% respectively.
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