Growth and nutritional responses of Sesbania sesban (L.) Merr. to rock phosphate, biofertilizer and rhizobial applications
Bibliographic record
Abstract
Continuous crop cultivation without adequate fertilizer input has led to poor yields and soil degradation in the tropics. To restore soil fertility through agroforestry practices, N2-fixing tree fallows are planted to produce nutrient-rich biomass that is incorporated in soils. The quantity and quality of biomass produced can be improved by phosphorus fertilization, inoculation with rhizobia or use of biofertilizers. My study examined the effects of rhizobial inoculation, biofertilizer and rock phosphate applications and their interactions on growth and nutrition of S. sesban planted in potted acidic soils of western Kenya. Rhizobial inoculation improved nodulation only when rock phosphate was added. Although biofertilizer failed to stimulate root nodulation, it enhanced plant nutrient absorption. Fertilization with rock phosphate enhanced growth and nutrition of S. sesban most and is recommended for use in agroforestry. There was a small but significant beneficial interaction between rock phosphate and biofertilizer use on Sesbania growth and nutrition.
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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".