Effect of Biochar Treated Sewage Sludge on the Yield and Uptake of Copper and Zinc in Chinese Cabbage (Brassica rapa)
Bibliographic record
Abstract
One of the potential uses of treated sewage sludge is its application as a soil conditioner in agricultural fields. A factorial experiment was conducted to compare the main effects of biochar and sewage sludge and the interaction effect between biochar and sewage sludge on the plant uptake of copper and zinc and vegetable yield. The experiment was done in a green house and Chinese cabbage was used as the test crop. The experiment consisted of two factors namely, biochar and sewage sludge, each of which was applied to the soil at four levels. The copper and zinc concentration were determined in the laboratory based on Atomic Absorption Spectroscopy. A two-way analysis of variance test was performed, and the Tukey’s HSD test was used to separate statistically significant treatment means at 5% level of significance. Results showed a significant interaction effect between biochar and sewage sludge (p = 0.012) on the level of copper concentration in plant tissue. It was observed that sewage sludge had a significant effect on zinc concentration (p < 0.001) in the plant tissue while biochar did not show any significant effect. Further, results showed significant increase in dry matter yield of Chinese cabbage with increasing levels of biochar applied (p < 0.001). This study demonstrates that biochar-treated sewage sludge has potential for use as a soil conditioner in vegetable production. However, it is recommended that care should be taken to avoid overuse by utilizing evaluated and treated sludge for soil amendment.
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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 | 0.001 |
| 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".