USO DE EFLUENTE DE PLANTA DE BIOGÁS Y MICROORGANISMOS EFICIENTES COMO BIOFERTILIZANTES EN PLANTAS DE CEBOLLA (Allium cepa L., cv. ‘Caribe-71’)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This work evaluated the effect of the application of biogas plant effluent and efficient microorganisms (ME), as biofertilizers in onion culture (Allium cepa L, cv. ‘Caribe-71’). The experiment was carried out at a field scale (in plots of 1,5 x 8,0 m) under a Latin Square design, where four treatments were applied: I. mixture of effluent and ME 5 % (v/v); II. mixture of effluent and ME 10 % (v/v); III. mixture of effluent and ME 15 % (v/v); and IV. Control treatment: with chemical fertilizer (NPK complete formula). A total of 12 foliar applications of the biofertilizers were carried out (two before sowing and then every seven days). The indicators were determined: height of the main leaf, number of bulbs, diameter of pseudostem, diameter of bulb, number of bulbs and fresh mass of plants. The results showed that the foliar application of the biogas plant effluent and the efficient microorganisms in the form of a mixture had a positive effect on the onion culture compared to the chemical fertilization of this one, due to the contribution of nutrients and beneficial microbiota that improves soil conditions and stimulates the growth and development of the plant. This work demonstrates the possibility of incorporating organic fertilization during onion cultivation, in accordance with the principles of agroecology in the context of the necessary sustainable agricultural development
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 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 it