Supplement of biochar and vermicompost amendments in coir and peat growing media improves N management and yields of leafy vegetables
Bibliographic record
Abstract
A greenhouse trial assessed the effects of biochar and vermicompost as partial substitutes of conventional growing media on leafy vegetables’ yields and changes of NH4+-N and NO3−-N in growing medium and leachates. Six growing media mixtures [(a) coir, (b) coir + biochar, (c) coir + vermicompost, (d) peat, (e) peat +vermicompost, (f) peat + biochar] combined with three nitrogen (N) rates [0% (0 g N·pot−1), 50% (0.5 g N·pot−1), and 100% (1.0 g N·pot−1) commercial recommendation] were arranged in a split-plot design with three replicates. On average, the yield gap between 100% N and 50% N was improved when biochar and vermicompost were used as substitutes of coir (32% and 28% vs. 49%) and peat (14% and 18% vs. 27%). The concentrations of NH4+-N in the leachates for peat + biochar varied between 17.20 and 1.00 mg·L−1. The concentrations of NO3−-N in the leachates varied between 130.0 and 1.0 mg·L−1 for coir + vermicompost, and 60 and 1.0 mg·L−1 for peat + vermicompost. The residual NO3−-N in peat + biochar growing media and the leachates did not match the changes observed for NH4+-N, and the much lower residual NH4+-N indicates possible NH4+-N retention by biochar and loss through volatilization in the early growth stages. Our results show that partial substitution of peat with biochar and coir with vermicompost maintained acceptable crop yield at 50% N due probably to N supply by vermicompost and decreased residual mineral N and loss by biochar in the leachates which could be beneficial for the environment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".