Background: Rhizoctonia solani AG1 IA is an important pathogen of rice (Oryza sativa L.) that causes rice sheath blight (RSB). Since control of RSB by conventional measures has failed, novel strategies like application of plant growth-promoting rhizobacteria (PGPR) can be an e cient alternative.Method and Results: mRNA sequences of rice were retrieving from NCBI for candidate reference genes selction, and seven candidate reference genes (RGs), namely 18SrRNA, ACT1, GAPDH2, UBC5, RPS27, eIF4aand CYP28, were selected for their stability in real-time quantitative PCR (RT-qPCR). Different algorithms were exploited, Delta Ct, geNorm, NormFinder, BestKeeper, and Comprehensive ranking by RefFinder, to evaluate RT-qPCR of rice in tissues infected with R. solani and treated with the PGPR strains, Pseudomonas saponiphilia and Pseudomonas protegens, and potassium silicate (KSi) alone or in combination with each PGPR strain. RGs stability was affected by each treatment and treatment-speci c selection was approved and validated for nonexpressor of PR-1(NPR1) for each treatment. Conclusion: Overall, ACT1 was the most stable RG with R. solani infection alone, GAPDH2 with R. solani infection plus KSi, UBC5 with R. solani infection plus P. saponiphilia, and eIF4a with R. solani infection plus P. protegens. Both ACT1 and RPS27 were the most stable with the combination of KSi and P. saponiphilia, while PRS27 was the most stable with the combination of KSi and P. protegens 51. Pfa MW (2001) A new mathematical model for relative quanti cation in real-time RT-PCR. Nucleic acids research 29(9): e45-e45
To date, there has been little agreement on supporting the hypothesis that how some key vegetative traits of camelina (Camelina sativa (L.) Crantz var. 'Soheil') are dependent on plant biomass. Therefore, the main aim of this investigation was to quantify the relationship between the size of camelina plants and seed production across a broad-range of plant densities through modelling approaches. To make a wide range of plant densities, a fan design was used in eight replicates in an experimental field at Sari Agricultural Sciences and Natural Resources University, Iran. To quantify the relation between plant density and other plant traits, a regression analysis was carried out and the coefficient of determination (R 2 ) was considered to evaluate the goodness of fit model. A power model (y = ax b ) could describe well the relationship between plant density (ranged 113-2905 plants m À2 ) and plant biomass, seed production, number of seeds per plant, stem diameter, and siliques number, with the coefficient of determination (R 2 ) values of 0.85, 0.87, 0.65, 0.64, and 0.90, respectively. The harvest indexes were 13.8%-26.9%, depending on plant density. Seed production per plant was positively correlated to the siliques number (r = 0.85), the branch number (r = 0.80), and the seed number (r = 0.99) which could be key components of camelina seed production per plant. Furthermore, no significant correlation was found among plant height, thousand-seed weight, and harvest index with seed production per plant. In conclusion, plant biomass could be considered an important trait to predict plant growth models of camelina. Also, a lower plant density of camelina can be compensated by a greater number of siliques, branches and seeds per plant.
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