Diversity of nitrogen-fixing and phosphorus-solubilizing bacteria associated with the rhizosphere of Andean maize in Ecuador
Bibliographic record
Abstract
A great diversity of microorganisms in the soil plays an important role in the sustainability of agricultural production systems. Among these microorganisms are bacteria that have the ability to fix atmospheric nitrogen or mineralize phosphorus, thus making it easily assimilable for plants. Maize is the main crop in the highlands of Ecuador (above 2000 meters) and it is predominantly traditional, using native seeds and very little or no agrochemicals. The National Institute of Agricultural Research (INIAP) has a collection of bacteria collected from the rhizosphere of maize in the highlands of Ecuador that has not been taxonomically identified. This research aimed to carry out a biochemical and genetic characterization to establish the identity of the collected nitrogen-fixing and phosphorus-solubilizing bacteria and to understand better the diversity of microorganisms present in the root biome of Andean maize. The hypothesis consisted of determining if there is a difference in the bacteria associated with the rhizosphere of maize in the Andean region of Ecuador compared with other regions. The bacteria underwent classical biochemical characterization based on catalase, oxidase, urease, sulfates, indole, sulfate-indole motility (SIM), and lactose, among others, and genetic identification by 16S rDNA ribosomal gene sequencing, PCR, and SANGER sequencing. A great diversity of microorganisms associated with the rhizosphere of the crop was found, including the genera Agrobacterium, Bacillus, Stenotrophomonas, Acinetobacter, Brevundimonas, Pseudomonas, and Pseudoxanthomonas. INIAP conserves these bacteria in a bank of microorganisms associated with crops of economic importance. They are useful for the development of biofertilizers that could contribute to a more sustainable agriculture in the region.
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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 | 0.001 | 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".