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Record W1942480121 · doi:10.5539/enrr.v5n4p41

The Influence of Different Retting Processes on the Strength of Fibres obtained from Poliostigma raticulatum, Grewia mollis, Cissus populnea and Hibiscus sabdariffa

2015· article· en· W1942480121 on OpenAlexvenueno aff
Peter Michael Dass, Ayodele Akinterinwa, Jibrin Ndahi Adamu, Shamsu Abba

Bibliographic record

VenueEnvironment and Natural Resources Research · 2015
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsnot available
Fundersnot available
KeywordsRettingGrewiaHibiscus sabdariffaBast fibreUltimate tensile strengthChemistryMucilageBotanyHorticultureFood scienceMaterials scienceBiologyComposite material

Abstract

fetched live from OpenAlex

<p class="1Body">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 <em>Poliostigma reticulatum</em>, <em>Grewia mollis,</em> <em>Cissus populnea</em> and<em> Hibiscus sabdariffa</em> were extracted by water and chemical retting. In chemical retting different concentrations of NaOH and NH<sub>4</sub>OH 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% NH<sub>4</sub>OH and 15% NaOH are clearer and lustrous for all sample except those from Kargo<em>.</em></p>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.271
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2015
Admission routes1
Has abstractyes

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