Agronomic Efficiency and Phosphate Solubilization of Pseudomonas fluorescens and Bradyrhizobium japonicum in Leaf-Spray Inoculation and Seed Treatment in Soybean
Bibliographic record
Abstract
The use of plant growth promoting bacteria (PGPB) that can solubilize phosphorus (P) has shown potential to improve nutrient availability in many crops such as soybean. This research aimed to evaluate agronomic efficiency and phosphorus solubilization through Bradyrhizobium japonicum and product to be registered Pseudomonas fluorescens (BR 14810) in soybean, at seed and leaf-spray inoculation. Four experiments with soybean (2020/21 crop) were installed in the following locations in the State of Goiás: Experimental Area of the Goiano Federal Institute, in Rio Verde, Bela Vista Farm, in Indiara, Bauzinho Farm, in Rio Verde, and Cachoeira Farm, in Doverlândia. The B. japonicum was inoculated in the seed of all treatments. It was tested three phosphate fertilization doses: 0, 50, and 100% recommended P dose, with and without P. fluorescens, at seed treatment and leaf-spray inoculation. The use of inoculation with P. fluorescens and B. japonicum increases nitrogen (N) content in grains and total N. The P content in dry mass, grains and total are increased using P. fluorescens and B. japonicum, confirming the ability to solubilize phosphates. Inoculation with P. fluorescens and B. japonicum is efficient for increasing shoot dry mass and productivity, can be used as a sustainable soybean management technology. Leaf-spray was more efficient than inoculation in seed treatment and can be used as an alternative mode of application. The results demonstrated that the product under test (P. fluorescens-BR 14810) can be used associated with B. japonicum, in ST or leaf-spray, resulting in increases of agronomic parameters and soybean yield.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".