Production of Levan by Bacillus licheniformis for Use as a Soil Sealant in Earthen Manure Storage Structures
Bibliographic record
Abstract
Manure application is not permitted on frozen land in Canada and therefore, manure management and storage are the primary issues facing the agri-food industry. Low-cost, effective and environmentally safe earthen manure storage (EMS) facilities will lower costs and help make the livestock industry more competitive and efficient. The goal of this study was to develop a biological sealing technology for earthen manure storages. The results showed that it is feasible to use a growing culture of Bacillus licheniformis to produce a non viscous water insoluble levan. Levan can only be produced by Bacillus licheniformis during the growth mode. No levan was produced during the death phase. About 0.36 g of levan was produced per gram of sucrose which is 91.1% of theoretical yield. The polymer can be used as a plugging agent to plug the pores of high permeability soils. From the biological and biochemical characteristics of the Bacillus licheniformis, it appears that the organism is capable of producing levan from sucrose under most field and soil conditions. As a soil organism, Bacillus licheniformis should be able to compete with most common soil species such as Arthrobacter and Bacillus. The bacteria could be grown either in the non-polysaccharide producing mode or in the polysaccharide producing mode. The first would permit distribution of the bacteria to the lower soil layers but would delay the production of the polysaccharide due to the lag period required to produce the enzyme (levansucrase). Upon production of levan, pore spaces would close and hence, the hydraulic conductivity would be substantially reduced.
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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".