WOOD-DERIVED BIOCHAR INFLUENCES NUTRIENT USE EFFICIENCY OF HEAVY METALS IN SPINACH (SPINACIA OLERACEA) UNDER GROUNDWATER AND WASTEWATER IRRIGATION
Bibliographic record
Abstract
Present study analysed the influence of slow-pyrolyzed wood-derived biochar on growth performance and heavy metal accumulation in the leaves of spinach grown under groundwater and wastewater irrigation. Biochar was applied in soil as 5% (~30 t·ha−1) and 10% (~60 t·ha−1) amendment. According to results, plant biomass was significantly higher under wastewater than groundwater irrigation. Biochar amendment increased significantly the aboveground plant biomass and root biomass and promoted water use efficiency (WUE). Under groundwater irrigation, biochar amendment at 10% application rate, increased the leaf area index (P < 0.05), while amendment of biochar at all application rates significantly reduced leaf area index under wastewater irrigation (P < 0.05). Application of biochar also reduced accumulation of rhizosphere soil around roots under wastewater irrigation, indicating less exudate production in the rhizosphere of plants. Biochar significantly reduced the concentration of copper (Cu) in under wastewater irrigation. Biochar increased the nutrient use efficiency (NUE) of plants for zinc (Zn) and Cu under wastewater irrigation.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".