Synergistic effects of biochar and poultry manure on soil and cucumber (Cucumis sativus) performance: A case study from the southeastern Nigeria
Bibliographic record
Abstract
This study explores the suitability of different biomass feedstocks for biochar production and their effects on soil health and crop yield. Two planting seasons were conducted, involving cucumber as the test crop and eleven treatments combining biochar and poultry manure. Soil analysis revealed initial soil conditions with high sand content and low pH. Poultry manure and biochar exhibited pH, organic carbon, and nutrient level variations. Significant differences in cucumber growth and yield were observed, with the longest vine length in plots treated with palm kernel husk biochar and poultry manure. Residual effects in the second planting season displayed similar trends. Soil pH, organic carbon, and total nitrogen remained consistent between seasons, while available phosphorus increased significantly in plots amended with goat manure biochar and poultry manure. Calcium, magnesium, potassium, and sodium contents also varied. Fruit length, weight, and yield were significantly improved by biochar treatments, with the combination of palm kernel husk biochar and poultry manure yielding the highest fruit weight. Correlation and structural equation analyses (p < 0.05) highlighted the relationships between plant characteristics, soil properties, and fruit indices, emphasizing the importance of nitrogen and phosphorus in supporting fruit development. The study suggests that biochar application enhances soil nutrients, crop growth, and fruit yields while reducing reliance on chemical fertilizers. It recommends considering biochar for land reclamation and as an alternative to traditional fertilizers, supported by appropriate regulations.
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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 | 0.001 |
| 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".