Bioformulation of Burkholderia sp. MSSP with a multispecies consortium for growth promotion of Cajanus cajan
Bibliographic record
Abstract
The present work was undertaken to formulate an effective bioformulation using Burkholderia sp. strain MSSP, a known plant-growth-promoting rhizobacterium. MSSP was tagged with the reporter gene of green fluorescent protein (gfp) to monitor its population in cost-effective solid carriers, including sugarcane-bagasse, sawdust, cocoa peat, rice husk, wheat bran, charcoal, and rock phosphate, and paneer-whey as liquid carrier. Physical and chemical properties of different low-cost carrier materials were studied. The viability of the green fluorescent tagged variant of MSSP was estimated in different sterile carrier materials. Whey and wheat bran proved to be efficient carrier materials for the bioformulation. Sawdust, rock phosphate, rice husk, and cocoa peat were average, while charcoal and sugarcane-bagasse proved to be inferior carriers. The viability of strain MSSP was also assessed in wheat bran and whey-based consortium, having three other bacterial strains, namely Sinorhizobium meliloti PP3, Rhizobium leguminosarum Pcc, and Bacillus sp. strain B1. Presence of other plant-growth-promoting bacteria did not have any detrimental effect on the viability of MSSP. Efficiency of the wheat-bran-based multispecies consortium was studied on the growth of pigeonpea in field conditions. A considerable increase in plant biomass, nodule number and weight, and number of pods was recorded as compared with individual trials and with the control.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".