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Record W2071785673 · doi:10.1139/b02-091

Lignification of spruce tracheid secondary cell walls related to longitudinal hardness and modulus of elasticity using nano-indentation

2002· article· en· W2071785673 on OpenAlexvenueno aff
Wolfgang Gindl‐Altmutter, Himadri S. Gupta, C. Grünwald

Bibliographic record

VenueCanadian Journal of Botany · 2002
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsnot available
Fundersnot available
KeywordsLigninTracheidCell wallHemicelluloseSecondary cell wallCelluloseYoung's modulusNanoindentationComposite materialMicrofibrilChemistryElasticity (physics)Elastic modulusMaterials scienceBotanyXylemBiochemistryOrganic chemistryBiology

Abstract

fetched live from OpenAlex

The lignin content and the mechanical properties of lignifying and fully lignified spruce tracheid secondary cell walls were determined using UV microscopy and nano-indentation, respectively. The average lignin content of developing tracheids was 0.10 g·g –1 , as compared with 0.21 g·g –1 in mature tracheids. The modulus of elasticity of developing cells was on average 22% lower than the one measured in mature, fully lignified cells. For the longitudinal hardness, a larger difference of 26% was observed. As lignifying cells in the cambial zone are undergoing cell wall development, spaces in the cellulose–hemicellulose structure are filled with lignin and the density of the cell wall is believed to increase. It is therefore suggested that the observed difference in modulus of elasticity between developing and fully lignified cell walls is due to the filling of spaces with lignin and an increase of the packing density of the cell wall during lignification. Although remarkably less stiff than the composite polysaccharide structure in the secondary cell wall, lignin may be considered equally hard. Therefore, the observed increase in lignin content may contribute directly to the measured increase of hardness.Key words: secondary cell wall, hardness, lignin, modulus of elasticity, wood formation.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.014
GPT teacher head0.196
Teacher spread0.182 · 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

Citations95
Published2002
Admission routes1
Has abstractyes

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