Sulfur-enriched biochar as a potential soil amendment and fertiliser
Bibliographic record
Abstract
Hydrogen sulfide (H2S) is a highly toxic and corrosive contaminant gas co-generated during anaerobic digestion. Studies have shown that biochars have the potential to adsorb H2S and to promote its oxidisation. To date, no studies have investigated the bioavailabilty to plants of the sulfur (S) contained in biochar when used as an S fertiliser. Biochar was packed into the biogas emissions stream to adsorb the H2S being generated. The resulting sulfur-enriched biochar (SulfaChar) and synthetic S fertiliser (control treatment) were amended to potting soils and the growth response of corn (Zea mays L.) and soybeans [Glycine max (L.) Merr.] and nutrient uptake were measured after a 90-day greenhouse study. SulfaChar contained 36.5% S (S element and SO42–), confirming it adsorbed significant amounts of H2S. Compared with the control treatment, SulfaChar amendment significantly increased corn plant biomass, ranging from 31% to 49% but only a slight increase in soybean biomass (4 to 14%). SulfaChar also increased corn plant uptake of S and other macro- (N, P, K, Ca, and Mg) and micro-nutrients (Zn, Mn and B). Our results show that SulfaChar was a source of plant available S, suggesting that SulfaChar is either a supplier of these nutrients or that it promoted their uptake.
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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 | 0.000 |
| 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".