Genetic diversity analysis and redundant identification in 48 core collections of Zingiber officinale Rosc. (Zingiberaceae)

Abstract

Ginger (Zingiber officinale Rosc.) rhizome has great demand in food and pharmaceutical industry. Odisha is the second largest ginger-cultivating state, and considered as best suitable after Kerala, in India. Forty-eight germplasm from 10 agro-climatic zones of Odisha were genetically characterized and potential duplicates were identified employing 25 polymorphic markers (RAPD, ISSR, SSR). These markers together amplified 170 polymorphic, 136 monomorphic, and 2 unique bands. SSR markers were the most efficient in generating highest primer resolving power (44.85), primer index (10.28), and number of polymorphic bands (67). Genotype–environment interaction was clearly demonstrated from UPGMA dendrogram based on Jaccard’s similarity coefficients and SAHN clustering which divided 48 samples into 8 sub-clusters (showing 80 % congruence with their places of geographical origin). H (0.211), I (0.38), and Gst (0.239) indices revealed genetic diversity within and genetic differentiation among 10 populations. AMOVA showed higher genetic variability among populations (64 %) than within populations (36 %). Ginger accessions having a mean genetic distance less than 0.21 (threshold average genetic distance) were considered redundant. Forty-eight samples could be reduced to 11 genetically diverse groups (each group contains duplicates but is different from each other) which confirmed 77 % of the collection to be redundant. Identification of duplicates can be useful to eliminate confusion regarding synonyms among farmers, help selection of suitable ginger seed material, and facilitate judicious management of germplasm in conservatory. Genetic diversity analysis unraveled the scope of genetic improvement and breeding program. Clustering analysis showed grouping of majority of samples to respective agro-climatic zones and established the possible interaction between genotype and environment.