Effects of Seed Soaking with Sewage Sludge Extract and Rare Earth Lanthanum on Seed Germination and Seedling Growth of Turfgrass
Bibliographic record
Abstract
Seeds of Lolium perenne L.and Festuca arundinacea L.were soaked with sewage sludge extract and rare earth lanthanum,and seed germination and seedling growth of two turfgrasses were investigated.The results showed that seed soaking with sludge extract and lanthanum promoted seed germination and seedling growth of two turfgrasses.The seed vigor index of L.perenne reached the maximum at treatment of 200 mg/L lanthanum+sludge extract,which was enhanced by 71.4% as compared with the control and that of F.arundinacea reached the maximum at 100 mg/L lanthanum+sludge extract.Moreover,seed soaking with sludge extract and lanthanum significantly promoted plant height growth of two turfgrasses.Compared with control,seedling height of L.perenne and F.arundinacea increased by 33.4% and 24.7% at 200 mg/L lanthanum+sludge extract,respectively at 5 d after sowing.The maximum of above ground biomass was found at 300 mg/L lanthanum+sludge extract for L.perenne and at 200 mg/L lanthanum+sludge extract for F.arundinacea.Chlorophyll content reached the maxium at 300 mg/L lanthanum+sludge extracts.Chlorophyll a and total chlorophyll contents of L.perenne highest were 20.6% and 18.4% higher than the control.For F.arundinacea,they were 43.7% and 34.4% higher than the control.
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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".