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Record W6998675249

Application of electro-technologies in the processing of flax and hemp stems

2014· dissertation· en· W6998675249 on OpenAlexfundaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2014
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicFood Drying and Modeling
Canadian institutionsnot available
FundersMcGill University
KeywordsRettingHemicellulosePectinHuskDewateringThreshingMicrowaveLigninGreen wood
DOInot available

Abstract

fetched live from OpenAlex

Plant based natural fibers are extracted from various parts of the plants such as leaf, inner bark and fruit/seed. Flax (Linum usitatissimum) and hemp (Cannabis sativa) stems were selected for the research because both flax and hemp are important crops in Canada.The main objectives of this study were: 1) To develop a novel retting method for the processing of pre- soaked flax and hemp stems by the application of microwave energy to the flax water mixture; 2) To evaluate the efficiency of retting in relation to the changes in compounds present in the fibers such as cellulose, hemicellulose, lignin and pectin through chemical analysis and 3) To develop an effective electro- osmotic dewatering system for the high moisture retted flax and hemp stems using a bench type roller press at various applied voltages.After the initial analysis of water retted flax stems, a novel retting method was introduced by applying microwave energy and studies were conducted to establish the effect on pre- soaked flax stems. The combined effect of pre- soaking, microwave volumetric heating and the non- thermal effect of microwave energy resulted in retted flax stem. Retting efficiency was observed at various combinations of pre-soaking, microwave treatment times and microwave energy levels. The microwave- assisted retting was repeated on the hemp stems to investigate the acceptability of this method in hemp varieties. NIR analysis and diameter distribution analysis were performed to study the efficiency of retting. Microwave- assisted retting on flax and hemp was proved to be efficient from the analysis of the compounds (lignin, hemicellulose and cellulose) presented in the fibers and its diameter distribution. After establishing the microwave- assisted retting of flax and hemp stems, the next step was to study the chemical changes occurring in the fibers during microwave assisted retting, and flax stem was selected for the analysis and studies were performed by gravimetric methods. Cellulose, hemicellulose, lignin and pectin concentrations and the sugar content in the solution obtained after the treatment were investigated. Cellulose percentage in the fiber was increased significantly with the increase of microwave power, which proved the release of cellulosic fiber with the application of microwave energy during retting. Hemicellulose, lignin and pectin concentrations decreased significantly after microwave-assisted retting which explained the degree of retting with the help of microwave energy. Fully soaked flax and hemp stems after microwave- assisted retting was collected at very high moisture level and those stems have to be dried to a lower moisture level of around 10% for further decortication to separate the fibers or to 4% for storage. To ease the drying process, an electro- osmotic bench type roller press system was introduced for the dewatering of retted flax and hemp stems. Since the pre- soaked stems are slightly charged, water molecules moved towards the anode when the stems were subjected to electro- osmosis between two electrodes. The applied pressure between two electrodes, the applied voltage and the pre- soaking time of the stems were the factors affecting the electro-osmotic dewatering. The stems after dewatering were subjected to short term microwave- assisted drying at controlled temperature and then moved to a fiber processing facility where the retted stems were decorticated to biofibers. Effectively retted stems with appropriate electro- technology produces high quality fibers whereas non- retted, under retted and overly retted stems lead to the production of low quality fibers.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score0.423

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.228
Teacher spread0.212 · 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

Citations0
Published2014
Admission routes2
Has abstractyes

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