Isolation and Characterization of Plant Growth Promoting Bacteria Isolated from Andean Soil as Potential Inoculants of Soybean Seeds
Bibliographic record
Abstract
Argentina is the leading exporter of soybean oil and flour, and the third largest producer of grain. Since, the crop is a matter of great importance to the national economy. Their production depends on the soil as their main resource to ensure a good productive capacity, so it is necessary to preserve the physical, chemical and biological properties of the soil. Although, the indiscriminate use of chemical fertilizers, disturb them. In recent years, there has been a trend towards cleaner production to reduce the use of chemical. One of the alternatives involves biological means through the use of plant growth promoting bacteria. These group of bacteria colonize the rhizosphere of plants and stimulate the plant growth by several mechanisms. The objective of this work was to characterize, identify and evaluate the growth promoting effect of 13 strains isolated from the Andean vegetation rhizosphere. The bacterial isolates were Enterobacteria, Stenotrophomonas, Pseudomonas, Nocardiodes, Bacillus, Exiguobacterium, Acinetobacter and Lactococcus genera. The results of the biochemical characterization determined that from the 13 bacterial strains, which produce siderophores, 11 possess the catalase enzyme, 10 fixate nitrogen, 12 produce the protease enzyme, 12 solubilize phosphorus, and 11 produce indoleacetic acid. The application of different inoculums to the seeds, allowed to obtain plants with longer stem length, more developed roots, larger and more intense coloration leaves than the control plants. The results encourage deeper studies to achieve the formulation of inoculums to use as a biofertilizer, which would replace chemical fertilizers or reduce their doses.
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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".