Effect of plant growth promoting rhizobia on seed germination and seedling traits in Acacia senegal

Abstract

Among arid zone tree species, Acacia senegal and Prosopis cineraria are the most important dryland resources of Western Rajasthan desert ecosystem. Due to ecological, biological and molecular similarities, they are often studied together. The climatic conditions in this region restrict the build-up of soil organic matter and soils are generally deficient in nitrogen. Studies were carried out to isolate and molecularly characterize the diverse group of plant growth promoting rhizobacteria from root nodules of native A. senegal and P. cineraria and their effect on seed germination and seedling traits in two genotypes of A. senegal. The direct sequencing of 16S rDNA region resulted in molecular identification of plant growth promoting rhizobacteria as Bacillus licheniformis, Sinorhizobium saheli isolated from root nodules of A. senegal and S. kostiense and S. saheli isolated from root nodules of P. cineraria. The partial sequences of 16S rDNA were assigned Gen accession numbers HQ738496, HQ738499, HQ738506 and HQ738508. Scarification treatment with sulphuric acid (98%) for 15 minutes was able to break the exogenous seed dormancy and enhanced germination percentage in control treatment to 90% and 92.5% in A. senegal in genotypes CAZRI 113AS and CAZRI 35AS, respectively. The treatments with Bacillus licheniformis or S. kostiense, either inoculated individually or as coinoculants, had positive effect on phenotypic traits of germination. Two A. senegal genotypes exhibited significant differences with regard to all the phenotypic traits. On the other hand, treatments with S. saheli isolated from either A. senegal or P. cineraria had negative effects on germination and related phenotypic traits. Values of the coeffivient of determination (R2) over 80% for root length versus shoot length, root/shoot ratio and seedling weight respectively validate that the observed a- ttributes are inter-dependable and linear progression trend can be predicted.