Improvement of growth, yield and associated bacteriome of rice by the application of probiotic Paraburkholderia and Delftia
Bibliographic record
Abstract
Plant probiotic bacteria enhance growth and yield of crop plants when applied at the appropriate time and dose. Two rice probiotic bacteria, Paraburkholderia fungorum strain BRRh-4 and Delftia sp. strain BTL-M2 promote growth and yield of plants. However, no information is available on application of these two bacteria on growth, yield, and diversity and population of bacteriome in roots and rhizosphere soils of the treated rice plants. This study aimed to assess the effect of BRRh-4 and BTL-M2 application on growth, yield and bacteriome in roots and rhizosphere soil of rice under varying doses of N, P and K fertilizers. Application of BRRh-4 and BTL-M2 strains significantly (p < 0.05) increased seed germination, growth and yield of rice compared to an untreated control. Interestingly, the grain yield of rice by these bacteria with 50% less of the recommended doses of N, P, and K fertilizers were statistically similar to or better than the rice plants treated with 100% doses of these fertilizers. Targeted amplicon (16S rRNA) sequence-based analysis revealed significant differences (PERMANOVA, p = 0.00035) in alpha-diversity between the root (R) and rhizosphere soil (S) samples, showing higher diversity in the microbial ecosystem of root samples. Additionally, the bacteriome diversity in the root of rice plants that received both probiotic bacteria and chemical fertilizers were significantly higher (PERMANOVA, p = 0.0312) compared to the rice plants treated with fertilizers only. Out of 185 bacterial genera detected, Prevotella, an anaerobic and Gram-negative bacterium, was found to be the predominant genus in both rhizosphere soil and root metagenomes. However, the relative abundance of Prevotella remained two-fold higher in the rhizosphere soil metagenome (52.02%) than in the root metagenome (25.04%). The other predominant bacterial genera detected in the rice root metagenome were Bacillus (11.07%), Planctomyces (4.06%), Faecalibacterium (3.91%), Deinococcus (2.97%), Bacteroides (2.61%), and Chryseobacterium (2.30%). On the other hand, rhizosphere soil metagenome had Bacteroides (12.38%), Faecalibacterium (9.50%), Vibrio (5.94%), Roseomonas (3.40%), and Delftia (3.02%). Interestingly, we found the presence and/or abundance of specific genera of bacteria in rice associated with the application of a specific probiotic bacterium. Taken together, our results indicate that improvement of growth and yield of rice by P. fungorum strain BRRh-4 and Delftia sp. strain BTL-M2 is likely linked with modulation of diversity, structures, and signature of bacteriome in roots and rhizosphere soils. This study for the first time demonstrated that application of plant growth promoting bacteria significantly improve growth, yield and increase the diversity of bacterial community in rice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".