Abstract

Njavara (shashtika in Sanskrit), a rice (Oryza sativa L.) landrace described in ancient Sanskrit treatises of Ayurveda for its nutritive and medicinal properties, is traditionally used in Kerala for Ayurveda treatments. We characterized the genetic resources of Njavara using 24 morphological traits and 664 amplified fragment length polymorphic (AFLP) markers. Different multivariate methods revealed four morphologically distinct types (morphotypes) in the Njavara germplasm, which were highly differentiated (Qst > 0.65) for several quantitative variables. Eight quantitative variables together with glume or bran color stably discriminated the four morphotypes. In accordance with ancient literature, most Njavara accessions exhibit a short maturity (<90 days). AFLP analysis supported the morphological grouping; however, it resolved morphotype I into three distinct clusters, revealing six genotypes under the four morphotypes identified. The genotypes were highly differentiated (Fst = 0.7276; Gst = 0.7202) and highly homozygous. Qst—Fst comparison revealed a possible role for natural selection in structuring quantitative variables among Njavara populations. Data suggest that the Njavara germplasm represents a composite of highly homozygous genetically isolated units. The distinctness of Njavara accessions in the AFLP dendrogram in relation to other traditional rice strains further demonstrates that the genotypes are nevertheless genetically cohesive and perpetuated with minimum genetic admixing. Stabilizing selection traditionally performed by farmers for short maturity coupled with autogamous breeding may have retained the genetic purity and governed the genetic structure of Njavara. The morphotypes identified were named long yellow, short yellow, intermediate yellow and short black, after culm length and glume color, which differ strikingly among the Njavara accessions. The present comprehensive description, the first of this kind in Njavara, yields vital insight into the genetic resources of this crop, which is relevant for designing methods for its effective utilization in different fields of research.

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