The Influence of Different Retting Processes on the Strength of Fibres obtained from Poliostigma raticulatum, Grewia mollis, Cissus populnea and Hibiscus sabdariffa
Bibliographic record
Abstract
The extraction of vegetable fibres from different parts of plants has been a major focal point in the search for natural fibres that would substitute synthetic fibres. Fibres from Poliostigma reticulatum, Grewia mollis, Cissus populnea and Hibiscus sabdariffa were extracted by water and chemical retting. In chemical retting different concentrations of NaOH and NH4OH were used. The extracted fibres were further purified and their tensile strength measured. The pH of water was measured as retting progresses and observed to increase as the retting time increases. This was ascribed to the secretion of enzymes by microorganisms as they acted on the mucilaginous matter of the bast with the resultant loosening of the fibres. The tensile strength of the fibres was determined using the Shirley Testometric 220D and was observed to gradual decline as the retting time increases. This was attributed to the continual removal of non-fibrous matter and the freeing of the fibres in the composite. However, beyond the fifth week of retting, no appreciable change in tensile strength was observed. This suggested that most of the non-fibrous matter have been solublized and utilized as source of nutrients and energy by the microorganisms. Acidic metabolites were produced due to microbial activities may have changed the pH of the medium and subsequently hindered their growth. In chemical retting, as the concentration of the medium increases the strength of the fibres decreases to a minimum then remain constant. This was accredited to the breakdown of inter- molecular bonds between non-fibrous substances and the fibres. And subsequently, the non-fibrous components separate from the fibres and dissolved in the medium revealing the actual fibres strength. It was therefore, opined that retted fibres in water, 5% NH4OH and 15% NaOH are clearer and lustrous for all sample except those from Kargo.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".